WorldWideScience

Sample records for machine tool intelligent

  1. Tool path strategy and cutting process monitoring in intelligent machining

    Science.gov (United States)

    Chen, Ming; Wang, Chengdong; An, Qinglong; Ming, Weiwei

    2018-06-01

    Intelligent machining is a current focus in advanced manufacturing technology, and is characterized by high accuracy and efficiency. A central technology of intelligent machining—the cutting process online monitoring and optimization—is urgently needed for mass production. In this research, the cutting process online monitoring and optimization in jet engine impeller machining, cranio-maxillofacial surgery, and hydraulic servo valve deburring are introduced as examples of intelligent machining. Results show that intelligent tool path optimization and cutting process online monitoring are efficient techniques for improving the efficiency, quality, and reliability of machining.

  2. Development and evaluation of intelligent machine tools based on knowledge evolution in M2M environment

    International Nuclear Information System (INIS)

    Kim, Dong Hoon; Song, Jun Yeob; Lee, Jong Hyun; Cha, Suk Keun

    2009-01-01

    In the near future, the foreseen improvement in machine tools will be in the form of a knowledge evolution-based intelligent device. The goal of this study is to develop intelligent machine tools having knowledge-evolution capability in Machine to Machine (M2M) wired and wireless environment. The knowledge evolution-based intelligent machine tools are expected to be capable of gathering knowledge autonomously, producing knowledge, understanding knowledge, applying reasoning to knowledge, making new decisions, dialoguing with other machines, etc. The concept of the knowledge-evolution intelligent machine originated from the process of machine control operation by the sense, dialogue and decision of a human expert. The structure of knowledge evolution in M2M and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, and work-offset compensation from thermal change and recommendation of cutting condition are performed on-line for knowledge-evolution verification

  3. Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools

    Science.gov (United States)

    Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu

    2018-03-01

    Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.

  4. Machine listening intelligence

    Science.gov (United States)

    Cella, C. E.

    2017-05-01

    This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

  5. An intelligent condition monitoring system for on-line classification of machine tool wear

    Energy Technology Data Exchange (ETDEWEB)

    Pan, Fu; Hope, A D; Javed, M [Systems Engineering Faculty, Southampton Institute (United Kingdom)

    1998-12-31

    The development of intelligent tool condition monitoring systems is a necessary requirement for successful automation of manufacturing processes. This presentation introduces a tool wear monitoring system for milling operations. The system utilizes power, force, acoustic emission and vibration sensors to monitor tool condition comprehensively. Features relevant to tool wear are drawn from time and frequency domain signals and a fuzzy pattern recognition technique is applied to combine the multisensor information and provide reliable classification results of tool wear states. (orig.) 10 refs.

  6. An intelligent condition monitoring system for on-line classification of machine tool wear

    Energy Technology Data Exchange (ETDEWEB)

    Fu Pan; Hope, A.D.; Javed, M. [Systems Engineering Faculty, Southampton Institute (United Kingdom)

    1997-12-31

    The development of intelligent tool condition monitoring systems is a necessary requirement for successful automation of manufacturing processes. This presentation introduces a tool wear monitoring system for milling operations. The system utilizes power, force, acoustic emission and vibration sensors to monitor tool condition comprehensively. Features relevant to tool wear are drawn from time and frequency domain signals and a fuzzy pattern recognition technique is applied to combine the multisensor information and provide reliable classification results of tool wear states. (orig.) 10 refs.

  7. Quo vadis, Intelligent Machine?

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2010-09-01

    Full Text Available Artificial Intelligence (AI is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this is no task easy to be solved. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in future. The goal is to mediate an understanding for the developments and changes in thinking in course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

  8. Are there intelligent Turing machines?

    OpenAIRE

    Bátfai, Norbert

    2015-01-01

    This paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines. Like universal Turing machines, orchestrated machines are also designed to simulate Turing machines but they can also modify the original operation of the included Turing machines to create a new layer of some kind of collective behavior. Using this new model we can define some interested notions related to cooperation ability of Turing machines such as the intelligence quo...

  9. Electricity of machine tool

    International Nuclear Information System (INIS)

    Gijeon media editorial department

    1977-10-01

    This book is divided into three parts. The first part deals with electricity machine, which can taints from generator to motor, motor a power source of machine tool, electricity machine for machine tool such as switch in main circuit, automatic machine, a knife switch and pushing button, snap switch, protection device, timer, solenoid, and rectifier. The second part handles wiring diagram. This concludes basic electricity circuit of machine tool, electricity wiring diagram in your machine like milling machine, planer and grinding machine. The third part introduces fault diagnosis of machine, which gives the practical solution according to fault diagnosis and the diagnostic method with voltage and resistance measurement by tester.

  10. Machine tool structures

    CERN Document Server

    Koenigsberger, F

    1970-01-01

    Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c

  11. Nanocomposites for Machining Tools

    Directory of Open Access Journals (Sweden)

    Daria Sidorenko

    2017-10-01

    Full Text Available Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance.

  12. On-line Cutting Tool Condition Monitoring in Machining Processes Using Artificial Intelligence

    OpenAIRE

    Vallejo, Antonio J.; Morales-Menéndez, Rub&#;n; Alique, J.R.

    2008-01-01

    This chapter presented new ideas for monitoring and diagnosis of the cutting tool condition with two different algorithms for pattern recognition: HMM, and ANN. The monitoring and diagnosis system was implemented for peripheral milling process in HSM, where several Aluminium alloys and cutting tools were used. The flank wear (VB) was selected as the criterion to evaluate the tool's life and four cutting tool conditions were defined to be recognized: New, half new, half worn, and worn conditio...

  13. Nanocomposites for Machining Tools

    DEFF Research Database (Denmark)

    Sidorenko, Daria; Loginov, Pavel; Mishnaevsky, Leon

    2017-01-01

    Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials...

  14. Elementary epistemological features of machine intelligence

    OpenAIRE

    Horvat, Marko

    2008-01-01

    Theoretical analysis of machine intelligence (MI) is useful for defining a common platform in both theoretical and applied artificial intelligence (AI). The goal of this paper is to set canonical definitions that can assist pragmatic research in both strong and weak AI. Described epistemological features of machine intelligence include relationship between intelligent behavior, intelligent and unintelligent machine characteristics, observable and unobservable entities and classification of in...

  15. Machine intelligence and knowledge bases

    Energy Technology Data Exchange (ETDEWEB)

    Furukawa, K

    1981-09-01

    The basic functions necessary in machine intelligence are a knowledge base and a logic programming language such as PROLOG using deductive reasoning. Recently inductive reasoning based on meta knowledge and default reasoning have been developed. The creative thought model of Lenit is reviewed and the concept of knowledge engineering is introduced. 17 references.

  16. Reliability analysis in intelligent machines

    Science.gov (United States)

    Mcinroy, John E.; Saridis, George N.

    1990-01-01

    Given an explicit task to be executed, an intelligent machine must be able to find the probability of success, or reliability, of alternative control and sensing strategies. By using concepts for information theory and reliability theory, new techniques for finding the reliability corresponding to alternative subsets of control and sensing strategies are proposed such that a desired set of specifications can be satisfied. The analysis is straightforward, provided that a set of Gaussian random state variables is available. An example problem illustrates the technique, and general reliability results are presented for visual servoing with a computed torque-control algorithm. Moreover, the example illustrates the principle of increasing precision with decreasing intelligence at the execution level of an intelligent machine.

  17. Machine intelligence and signal processing

    CERN Document Server

    Vatsa, Mayank; Majumdar, Angshul; Kumar, Ajay

    2016-01-01

    This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning – instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning). And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intel...

  18. Machine Tool Software

    Science.gov (United States)

    1988-01-01

    A NASA-developed software package has played a part in technical education of students who major in Mechanical Engineering Technology at William Rainey Harper College. Professor Hack has been using (APT) Automatically Programmed Tool Software since 1969 in his CAD/CAM Computer Aided Design and Manufacturing curriculum. Professor Hack teaches the use of APT programming languages for control of metal cutting machines. Machine tool instructions are geometry definitions written in APT Language to constitute a "part program." The part program is processed by the machine tool. CAD/CAM students go from writing a program to cutting steel in the course of a semester.

  19. The machine intelligence Hex project

    Science.gov (United States)

    Chalup, Stephan K.; Mellor, Drew; Rosamond, Fran

    2005-12-01

    Hex is a challenging strategy board game for two players. To enhance students’ progress in acquiring understanding and practical experience with complex machine intelligence and programming concepts we developed the Machine Intelligence Hex (MIHex) project. The associated undergraduate student assignment is about designing and implementing Hex players and evaluating them in an automated tournament of all programs developed by the class. This article surveys educational aspects of the MIHex project. Additionally, fundamental techniques for game programming as well as specific concepts for Hex board evaluation are reviewed. The MIHex game server and possibilities of tournament organisation are described. We summarise and discuss our experiences from running the MIHex project assignment over four consecutive years. The impact on student motivation and learning benefits are evaluated using questionnaires and interviews.

  20. Machine tool evaluation

    International Nuclear Information System (INIS)

    Lunsford, B.E.

    1976-01-01

    Continued improvement in numerical control (NC) units and the mechanical components used in the construction of today's machine tools, necessitate the use of more precise instrumentation to calibrate and determine the capabilities of these systems. It is now necessary to calibrate most tape-control lathes to a tool-path positioning accuracy of +-300 microinches in the full slide travel and, on some special turning and boring machines, a capability of +-100 microinches must be achieved. The use of a laser interferometer to determine tool-path capabilities is described

  1. Chatter and machine tools

    CERN Document Server

    Stone, Brian

    2014-01-01

    Focussing on occurrences of unstable vibrations, or Chatter, in machine tools, this book gives important insights into how to eliminate chatter with associated improvements in product quality, surface finish and tool wear. Covering a wide range of machining processes, including turning, drilling, milling and grinding, the author uses his research expertise and practical knowledge of vibration problems to provide solutions supported by experimental evidence of their effectiveness. In addition, this book contains links to supplementary animation programs that help readers to visualise the ideas detailed in the text. Advancing knowledge in chatter avoidance and suggesting areas for new innovations, Chatter and Machine Tools serves as a handbook for those desiring to achieve significant reductions in noise, longer tool and grinding wheel life and improved product finish.

  2. Analysis of machining and machine tools

    CERN Document Server

    Liang, Steven Y

    2016-01-01

    This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

  3. Machine learning an artificial intelligence approach

    CERN Document Server

    Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

    1983-01-01

    Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

  4. Art in the Age of Machine Intelligence

    Directory of Open Access Journals (Sweden)

    Blaise Agüera y Arcas

    2017-09-01

    Full Text Available In this wide‐ranging essay, the leader of Google’s Seattle AI group and founder of the Artists and Machine Intelligence program discusses the long‐standing and complex relationship between art and technology. The transformation of artistic practice and theory that attended the 19th century photographic revolution is explored as a parallel for the current revolution in machine intelligence, which promises not only to mechanize (or democratize the means of reproduction, but also of production.

  5. A computer architecture for intelligent machines

    Science.gov (United States)

    Lefebvre, D. R.; Saridis, G. N.

    1992-01-01

    The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

  6. Slide system for machine tools

    Science.gov (United States)

    Douglass, Spivey S.; Green, Walter L.

    1982-01-01

    The present invention relates to a machine tool which permits the machining of nonaxisymmetric surfaces on a workpiece while rotating the workpiece about a central axis of rotation. The machine tool comprises a conventional two-slide system (X-Y) with one of these slides being provided with a relatively short travel high-speed auxiliary slide which carries the material-removing tool. The auxiliary slide is synchronized with the spindle speed and the position of the other two slides and provides a high-speed reciprocating motion required for the displacement of the cutting tool for generating a nonaxisymmetric surface at a selected location on the workpiece.

  7. Intelligent Tools and Instructional Simulations

    National Research Council Canada - National Science Library

    Murray, William R; Sams, Michelle; Belleville, Michael

    2001-01-01

    This intelligent tools and instructional simulations project was an investigation into the utility of a knowledge-based performance support system to support learning and on-task performance for using...

  8. From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

    Science.gov (United States)

    Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

    2017-11-01

    Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Recent advances in intelligent machine technologies

    International Nuclear Information System (INIS)

    Bartholet, T.G.

    1987-01-01

    Further developments in intelligent machine technologies have recently been accomplished under sponsorship by the Department of Energy (DOE), the Electric Power Research Institute (EPRI), the U.S. Army and NASA. This paper describes these developments and presents actual results achieved and demonstrated. These projects encompass new developments in manipulators, vision and walking machines. Continuing developments will add increasing degrees of autonomy as appropriate to applications in the fields of nuclear power, space, defense and industrial or commercial marketplaces

  10. Probabilistic machine learning and artificial intelligence.

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-28

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  11. Probabilistic machine learning and artificial intelligence

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-01

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  12. Tool grinding machine

    Science.gov (United States)

    Dial, Sr., Charles E.

    1980-01-01

    The present invention relates to an improved tool grinding mechanism for grinding single point diamond cutting tools to precise roundness and radius specifications. The present invention utilizes a tool holder which is longitudinally displaced with respect to the remainder of the grinding system due to contact of the tool with the grinding surface with this displacement being monitored so that any variation in the grinding of the cutting surface such as caused by crystal orientation or tool thickness may be compensated for during the grinding operation to assure the attainment of the desired cutting tool face specifications.

  13. Improved tool grinding machine

    Science.gov (United States)

    Dial, C.E. Sr.

    The present invention relates to an improved tool grinding mechanism for grinding single point diamond cutting tools to precise roundness and radius specifications. The present invention utilizes a tool holder which is longitudinally displaced with respect to the remainder of the grinding system due to contact of the tool with the grinding surface with this displacement being monitored so that any variation in the grinding of the cutting surface such as caused by crystal orientation or tool thicknesses may be compensated for during the grinding operation to assure the attainment of the desired cutting tool face specifications.

  14. Intelligent Machine Learning Approaches for Aerospace Applications

    Science.gov (United States)

    Sathyan, Anoop

    Machine Learning is a type of artificial intelligence that provides machines or networks the ability to learn from data without the need to explicitly program them. There are different kinds of machine learning techniques. This thesis discusses the applications of two of these approaches: Genetic Fuzzy Logic and Convolutional Neural Networks (CNN). Fuzzy Logic System (FLS) is a powerful tool that can be used for a wide variety of applications. FLS is a universal approximator that reduces the need for complex mathematics and replaces it with expert knowledge of the system to produce an input-output mapping using If-Then rules. The expert knowledge of a system can help in obtaining the parameters for small-scale FLSs, but for larger networks we will need to use sophisticated approaches that can automatically train the network to meet the design requirements. This is where Genetic Algorithms (GA) and EVE come into the picture. Both GA and EVE can tune the FLS parameters to minimize a cost function that is designed to meet the requirements of the specific problem. EVE is an artificial intelligence developed by Psibernetix that is trained to tune large scale FLSs. The parameters of an FLS can include the membership functions and rulebase of the inherent Fuzzy Inference Systems (FISs). The main issue with using the GFS is that the number of parameters in a FIS increase exponentially with the number of inputs thus making it increasingly harder to tune them. To reduce this issue, the FLSs discussed in this thesis consist of 2-input-1-output FISs in cascade (Chapter 4) or as a layer of parallel FISs (Chapter 7). We have obtained extremely good results using GFS for different applications at a reduced computational cost compared to other algorithms that are commonly used to solve the corresponding problems. In this thesis, GFSs have been designed for controlling an inverted double pendulum, a task allocation problem of clustering targets amongst a set of UAVs, a fire

  15. Tool path in torus tool CNC machining

    Directory of Open Access Journals (Sweden)

    XU Ying

    2016-10-01

    Full Text Available This paper is about tool path in torus tool CNC machining.The mathematical model of torus tool is established.The tool path planning algorithm is determined through calculation of the cutter location,boundary discretization,calculation of adjacent tool path and so on,according to the conversion formula,the cutter contact point will be converted to the cutter location point and then these points fit a toolpath.Lastly,the path planning algorithm is implemented by using Matlab programming.The cutter location points for torus tool are calculated by Matlab,and then fit these points to a toolpath.While using UG software,another tool path of free surface is simulated of the same data.It is drew compared the two tool paths that using torus tool is more efficient.

  16. The role of soft computing in intelligent machines.

    Science.gov (United States)

    de Silva, Clarence W

    2003-08-15

    An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.

  17. Complementary Machine Intelligence and Human Intelligence in Virtual Teaching Assistant for Tutoring Program Tracing

    Science.gov (United States)

    Chou, Chih-Yueh; Huang, Bau-Hung; Lin, Chi-Jen

    2011-01-01

    This study proposes a virtual teaching assistant (VTA) to share teacher tutoring tasks in helping students practice program tracing and proposes two mechanisms of complementing machine intelligence and human intelligence to develop the VTA. The first mechanism applies machine intelligence to extend human intelligence (teacher answers) to evaluate…

  18. [Algorithms, machine intelligence, big data : general considerations].

    Science.gov (United States)

    Radermacher, F J

    2015-08-01

    We are experiencing astonishing developments in the areas of big data and artificial intelligence. They follow a pattern that we have now been observing for decades: according to Moore's Law,the performance and efficiency in the area of elementary arithmetic operations increases a thousand-fold every 20 years. Although we have not achieved the status where in the singular sense machines have become as "intelligent" as people, machines are becoming increasingly better. The Internet of Things has again helped to massively increase the efficiency of machines. Big data and suitable analytics do the same. If we let these processes simply continue, our civilization may be endangerd in many instances. If the "containment" of these processes succeeds in the context of a reasonable political global governance, a worldwide eco-social market economy, andan economy of green and inclusive markets, many desirable developments that are advantageous for our future may result. Then, at some point in time, the constant need for more and faster innovation may even stop. However, this is anything but certain. We are facing huge challenges.

  19. Syndrome Diagnosis: Human Intuition or Machine Intelligence?

    Science.gov (United States)

    Braaten, Øivind; Friestad, Johannes

    2008-01-01

    The aim of this study was to investigate whether artificial intelligence methods can represent objective methods that are essential in syndrome diagnosis. Most syndromes have no external criterion standard of diagnosis. The predictive value of a clinical sign used in diagnosis is dependent on the prior probability of the syndrome diagnosis. Clinicians often misjudge the probabilities involved. Syndromology needs objective methods to ensure diagnostic consistency, and take prior probabilities into account. We applied two basic artificial intelligence methods to a database of machine-generated patients - a ‘vector method’ and a set method. As reference methods we ran an ID3 algorithm, a cluster analysis and a naive Bayes’ calculation on the same patient series. The overall diagnostic error rate for the the vector algorithm was 0.93%, and for the ID3 0.97%. For the clinical signs found by the set method, the predictive values varied between 0.71 and 1.0. The artificial intelligence methods that we used, proved simple, robust and powerful, and represent objective diagnostic methods. PMID:19415142

  20. Intelligent Machine Parts with Surface Embedded Sensors

    OpenAIRE

    Østbø, Niels Peter

    2009-01-01

    A surface embedded temperature sensor has successfully been fabricated on a customized industrial bolt. The aluminum substrate of the bolt was electrically isolated by plasma electrolytic oxidation followed by the fabrication of a type T thermocouple and finally covered by a wear resistant DLC coating. This bolt is part of our work to develop smart machine parts that are capable of reporting their current physical status under real working conditions enabling both new tools for condition base...

  1. Nonvolatile Memory Materials for Neuromorphic Intelligent Machines.

    Science.gov (United States)

    Jeong, Doo Seok; Hwang, Cheol Seong

    2018-04-18

    Recent progress in deep learning extends the capability of artificial intelligence to various practical tasks, making the deep neural network (DNN) an extremely versatile hypothesis. While such DNN is virtually built on contemporary data centers of the von Neumann architecture, physical (in part) DNN of non-von Neumann architecture, also known as neuromorphic computing, can remarkably improve learning and inference efficiency. Particularly, resistance-based nonvolatile random access memory (NVRAM) highlights its handy and efficient application to the multiply-accumulate (MAC) operation in an analog manner. Here, an overview is given of the available types of resistance-based NVRAMs and their technological maturity from the material- and device-points of view. Examples within the strategy are subsequently addressed in comparison with their benchmarks (virtual DNN in deep learning). A spiking neural network (SNN) is another type of neural network that is more biologically plausible than the DNN. The successful incorporation of resistance-based NVRAM in SNN-based neuromorphic computing offers an efficient solution to the MAC operation and spike timing-based learning in nature. This strategy is exemplified from a material perspective. Intelligent machines are categorized according to their architecture and learning type. Also, the functionality and usefulness of NVRAM-based neuromorphic computing are addressed. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Tool wear and breakage monitoring in machining

    International Nuclear Information System (INIS)

    Madl, J.

    1992-01-01

    Risk minimization of metal cutting operations is one of the main problems of metal cutting technology. This paper describes some aspects in monitoring and control of machining processes. Tool monitoring is the fokus of machining process monitoring. Tool breakage and tool life recognition are the main problems of tool monitoring. All problems of this type of monitoring have not yet been fully solved. (orig.)

  3. Prediction of Machine Tool Condition Using Support Vector Machine

    International Nuclear Information System (INIS)

    Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

    2011-01-01

    Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

  4. Machine Ethics: Creating an Ethical Intelligent Agent

    OpenAIRE

    Anderson, Michael; Anderson, Susan Leigh

    2007-01-01

    The newly emerging field of machine ethics (Anderson and Anderson 2006) is concerned with adding an ethical dimension to machines. Unlike computer ethics -- which has traditionally focused on ethical issues surrounding humans' use of machines -- machine ethics is concerned with ensuring that the behavior of machines toward human users, and perhaps other machines as well, is ethically acceptable. In this article we discuss the importance of machine ethics, the need for machines that represent ...

  5. Tool set for distributed real-time machine control

    Science.gov (United States)

    Carrott, Andrew J.; Wright, Christopher D.; West, Andrew A.; Harrison, Robert; Weston, Richard H.

    1997-01-01

    Demands for increased control capabilities require next generation manufacturing machines to comprise intelligent building elements, physically located at the point where the control functionality is required. Networks of modular intelligent controllers are increasingly designed into manufacturing machines and usable standards are slowly emerging. To implement a control system using off-the-shelf intelligent devices from multi-vendor sources requires a number of well defined activities, including (a) the specification and selection of interoperable control system components, (b) device independent application programming and (c) device configuration, management, monitoring and control. This paper briefly discusses the support for the above machine lifecycle activities through the development of an integrated computing environment populated with an extendable software toolset. The toolset supports machine builder activities such as initial control logic specification, logic analysis, machine modeling, mechanical verification, application programming, automatic code generation, simulation/test, version control, distributed run-time support and documentation. The environment itself consists of system management tools and a distributed object-oriented database which provides storage for the outputs from machine lifecycle activities and specific target control solutions.

  6. Memory Based Machine Intelligence Techniques in VLSI hardware

    OpenAIRE

    James, Alex Pappachen

    2012-01-01

    We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...

  7. Improving Tools in Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-01-01

    Full Text Available The historical origin of the Artificial Intelligence (AI is usually established in the Dartmouth Conference, of 1956. But we can find many more arcane origins [1]. Also, we can consider, in more recent times, very great thinkers, as Janos Neumann (then, John von Neumann, arrived in USA, Norbert Wiener, Alan Mathison Turing, or Lofti Zadeh, for instance [12, 14]. Frequently AI requires Logic. But its Classical version shows too many insufficiencies. So, it was necessary to introduce more sophisticated tools, as Fuzzy Logic, Modal Logic, Non-Monotonic Logic and so on [1, 2]. Among the things that AI needs to represent are categories, objects, properties, relations between objects, situations, states, time, events, causes and effects, knowledge about knowledge, and so on. The problems in AI can be classified in two general types [3, 5], search problems and representation problems. On this last "peak", there exist different ways to reach their summit. So, we have [4] Logics, Rules, Frames, Associative Nets, Scripts, and so on, many times connected among them. We attempt, in this paper, a panoramic vision of the scope of application of such representation methods in AI. The two more disputable questions of both modern philosophy of mind and AI will be perhaps the Turing Test and the Chinese Room Argument. To elucidate these very difficult questions, see our final note.

  8. Analysis on machine tool systems using spindle vibration monitoring for automatic tool changer

    OpenAIRE

    Shang-Liang Chen; Yin-Ting Cheng; Chin-Fa Su

    2015-01-01

    Recently, the intelligent systems of technology have become one of the major items in the development of machine tools. One crucial technology is the machinery status monitoring function, which is required for abnormal warnings and the improvement of cutting efficiency. During processing, the mobility act of the spindle unit determines the most frequent and important part such as automatic tool changer. The vibration detection system includes the development of hardware and software, such as ...

  9. Human Functions, Machine Tools, and the Role of the Analyst

    Directory of Open Access Journals (Sweden)

    Gordon R. Middleton

    2015-09-01

    Full Text Available In an era of rapidly increasing technical capability, the intelligence focus is often on the modes of collection and tools of analysis rather than the analyst themselves. Data are proliferating and so are tools to help analysts deal with the flood of data and the increasingly demanding timeline for intelligence production, but the role of the analyst in such a data-driven environment needs to be understood in order to support key management decisions (e.g., training and investment priorities. This paper describes a model of the analytic process, and analyzes the roles played by humans and machine tools in each process element. It concludes that human analytic functions are as critical in the intelligence process as they have ever been, and perhaps even more so due to the advance of technology in the intelligence business. Human functions performed by analysts are critical in nearly every step in the process, particularly at the front end of the analytic process, in defining and refining the problem statement, and at the end of the process, in generating knowledge, presenting the story in understandable terms, tailoring the presentation of the results of the analysis to various audiences, as well as in determining when to initiate iterative loops in the process. The paper concludes with observations on the necessity of enabling expert analysts, tools to deal with big data, developing analysts with advanced analytic methods as well as with techniques for optimal use of advanced tools, and suggestions for further quantitative research.

  10. Calibration apparatus for a machine-tool

    International Nuclear Information System (INIS)

    Crespin, G.

    1985-01-01

    The invention proposes a calibration apparatus for a machine-tool comprising a torque measuring device, where the tool is driven by a motor of which supply electric current is proportional to the torque applied upon the tool and can be controlled and measured, a housing having an aperture through which the rotatable tool can pass. This device alloys to apply a torque on the tool and to measure it from the supply current of the motor. The invention applies, more particularly to the screwing machines used for the mounting of the core containment plates [fr

  11. Self-Adaptive Systems for Machine Intelligence

    CERN Document Server

    He, Haibo

    2011-01-01

    This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide application

  12. Integrated human-machine intelligence in space systems

    Science.gov (United States)

    Boy, Guy A.

    1992-01-01

    The integration of human and machine intelligence in space systems is outlined with respect to the contributions of artificial intelligence. The current state-of-the-art in intelligent assistant systems (IASs) is reviewed, and the requirements of some real-world applications of the technologies are discussed. A concept of integrated human-machine intelligence is examined in the contexts of: (1) interactive systems that tolerate human errors; (2) systems for the relief of workloads; and (3) interactive systems for solving problems in abnormal situations. Key issues in the development of IASs include the compatibility of the systems with astronauts in terms of inputs/outputs, processing, real-time AI, and knowledge-based system validation. Real-world applications are suggested such as the diagnosis, planning, and control of enginnered systems.

  13. Transition Towards Energy Efficient Machine Tools

    CERN Document Server

    Zein, André

    2012-01-01

    Energy efficiency represents a cost-effective and immediate strategy of a sustainable development. Due to substantial environmental and economic implications, a strong emphasis is put on the electrical energy requirements of machine tools for metalworking processes. The improvement of energy efficiency is however confronted with diverse barriers, which sustain an energy efficiency gap of unexploited potential. The deficiencies lie in the lack of information about the actual energy requirements of machine tools, a minimum energy reference to quantify improvement potential and the possible actions to improve the energy demand. Therefore, a comprehensive concept for energy performance management of machine tools is developed which guides the transition towards energy efficient machine tools. It is structured in four innovative concept modules, which are embedded into step-by-step workflow models. The capability of the performance management concept is demonstrated in an automotive manufacturing environment. The ...

  14. Machine learning \\& artificial intelligence in the quantum domain

    OpenAIRE

    Dunjko, Vedran; Briegel, Hans J.

    2017-01-01

    Quantum information technologies, and intelligent learning systems, are both emergent technologies that will likely have a transforming impact on our society. The respective underlying fields of research -- quantum information (QI) versus machine learning (ML) and artificial intelligence (AI) -- have their own specific challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question to what extent th...

  15. 6th International Conference on Pattern Recognition and Machine Intelligence

    CERN Document Server

    Gawrysiak, Piotr; Kryszkiewicz, Marzena; Rybiński, Henryk

    2016-01-01

    This book presents valuable contributions devoted to practical applications of Machine Intelligence and Big Data in various branches of the industry. All the contributions are extended versions of presentations delivered at the Industrial Session the 6th International Conference on Pattern Recognition and Machine Intelligence (PREMI 2015) held in Warsaw, Poland at June 30- July 3, 2015, which passed through a rigorous reviewing process. The contributions address real world problems and show innovative solutions used to solve them. This volume will serve as a bridge between researchers and practitioners, as well as between different industry branches, which can benefit from sharing ideas and results.

  16. The Properties of Intelligent Human-Machine Interface

    Directory of Open Access Journals (Sweden)

    Alexander Alfimtsev

    2012-04-01

    Full Text Available Intelligent human-machine interfaces based on multimodal interaction are developed separately in different application areas. No unified opinion exists about the issue of what properties should these interfaces have to provide an intuitive and natural interaction. Having carried out an analytical survey of the papers that deal with intelligent interfaces a set of properties are presented, which are necessary for intelligent interface between an information system and a human: absolute response, justification, training, personification, adaptiveness, collectivity, security, hidden persistence, portability, filtering.

  17. LARA. Localization of an automatized refueling machine by acoustical sounding in breeder reactors - implementation of artificial intelligence techniques

    International Nuclear Information System (INIS)

    Lhuillier, C.; Malvache, P.

    1987-01-01

    The automatic control of the machine which handles the nuclear subassemblies in fast neutron reactors requires autonomous perception and decision tools. An acoustical device allows the machine to position in the work area. Artificial intelligence techniques are implemented to interpret the data: pattern recognition, scene analysis. The localization process is managed by an expert system. 6 refs.; 8 figs

  18. Transition towards energy efficient machine tools

    Energy Technology Data Exchange (ETDEWEB)

    Zein, Andre [Technische Univ. Braunschweig (Germany). Inst. fuer Werkzeugmaschinen und Fertigungstechnik

    2012-07-01

    Provides unique data about industrial trends affecting the energy demand of machine tools. Presents a comprehensive methodology to assess the energy efficiency of machining processes. Contains an integrated management concept to implement energy performance measures into existing industrial systems. Includes an industrial case study with two exemplary applications. Energy efficiency represents a cost-effective and immediate strategy of a sustainable development. Due to substantial environmental and economic implications, a strong emphasis is put on the electrical energy requirements of machine tools for metalworking processes. The improvement of energy efficiency is however confronted with diverse barriers, which sustain an energy efficiency gap of unexploited potential. The deficiencies lie in the lack of information about the actual energy requirements of machine tools, a minimum energy reference to quantify improvement potential and the possible actions to improve the energy demand. Therefore, a comprehensive concept for energy performance management of machine tools is developed which guides the transition towards energy efficient machine tools. It is structured in four innovative concept modules, which are embedded into step-by-step workflow models. The capability of the performance management concept is demonstrated in an automotive manufacturing environment. The target audience primarily comprises researchers and practitioners challenged to enhance energy efficiency in manufacturing. The book may also be beneficial for graduate students who want to specialize in this field.

  19. Machine Translation Tools - Tools of The Translator's Trade

    DEFF Research Database (Denmark)

    Kastberg, Peter

    2012-01-01

    In this article three of the more common types of translation tools are presented, discussed and critically evaluated. The types of translation tools dealt with in this article are: Fully Automated Machine Translation (or FAMT), Human Aided Machine Translation (or HAMT) and Machine Aided Human...... Translation (or MAHT). The strengths and weaknesses of the different types of tools are discussed and evaluated by means of a number of examples. The article aims at two things: at presenting a sort of state of the art of what is commonly referred to as “machine translation” as well as at providing the reader...... with a sound basis for considering what translation tool (if any) is the most appropriate in order to meet his or her specific translation needs....

  20. Diamond turning on advanced machine tool prototypes

    International Nuclear Information System (INIS)

    Arnold, J.B.; Steger, P.J.

    1975-01-01

    Specular-quality metal mirrors are being machined for use in laser optical systems. The fabrication process incorporates special quality diamond tools and specially constructed turning machines. The machines are controlled by advanced control techniques and are housed in an environmentally controlled laboratory to insure ultimate machine stability and positional accuracy. The materials from which these mirrors are primarily produced are the softer face-center-cubic structure metals, such as gold, silver, copper, and aluminum. Mirror manufacturing by the single-point diamond machining process is in an early stage of development, but it is anticipated that this method will become the most economical way for producing high-quality metal mirrors. (U.S.)

  1. Confirmation of Thermal Images and Vibration Signals for Intelligent Machine Fault Diagnostics

    Directory of Open Access Journals (Sweden)

    Achmad Widodo

    2012-01-01

    Full Text Available This paper deals with the maintenance technique for industrial machinery using the artificial neural network so-called self-organizing map (SOM. The aim of this work is to develop intelligent maintenance system for machinery based on an alternative way, namely, thermal images instead of vibration signals. SOM is selected due to its simplicity and is categorized as an unsupervised algorithm. Following the SOM training, machine fault diagnostics is performed by using the pattern recognition technique of machine conditions. The data used in this work are thermal images and vibration signals, which were acquired from machine fault simulator (MFS. It is a reliable tool and is able to simulate several conditions of faulty machine such as unbalance, misalignment, looseness, and rolling element bearing faults (outer race, inner race, ball, and cage defects. Data acquisition were conducted simultaneously by infrared thermography camera and vibration sensors installed in the MFS. The experimental data are presented as thermal image and vibration signal in the time domain. Feature extraction was carried out to obtain salient features sensitive to machine conditions from thermal images and vibration signals. These features are then used to train the SOM for intelligent machine diagnostics process. The results show that SOM can perform intelligent fault diagnostics with plausible accuracies.

  2. A linear maglev guide for machine tools

    Energy Technology Data Exchange (ETDEWEB)

    Tieste, K D [Inst. of Mechanics, Univ. of Hannover (Germany); Popp, K [Inst. of Mechanics, Univ. of Hannover (Germany)

    1996-12-31

    Machine tools require linear guides with high slide velocity and very high position accuracy. The three tasks of a linear guide - supporting, guiding and driving - shall be realised by means of active magnetic bearings (AMB). The resulting linear magnetically levitated (maglev) guide has to accomplish the following characteristics: High stiffness, good damping and low noise as well as low heat production. First research on a one degree-of-freedom (DOF) support magnet unit aimed at the development of components and efficient control strategies for the linear maglev guide. The actual research is directed to realise a five DOF linear maglev guide for machine tools without drive to answer the question whether the maglev principle can be used for a linear axis in a machine tool. (orig.)

  3. Sine-Bar Attachment For Machine Tools

    Science.gov (United States)

    Mann, Franklin D.

    1988-01-01

    Sine-bar attachment for collets, spindles, and chucks helps machinists set up quickly for precise angular cuts that require greater precision than provided by graduations of machine tools. Machinist uses attachment to index head, carriage of milling machine or lathe relative to table or turning axis of tool. Attachment accurate to 1 minute or arc depending on length of sine bar and precision of gauge blocks in setup. Attachment installs quickly and easily on almost any type of lathe or mill. Requires no special clamps or fixtures, and eliminates many trial-and-error measurements. More stable than improvised setups and not jarred out of position readily.

  4. Program Design Report of the CNC Machine Tool(II)

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jong Kiun; Youm, K. U.; Kim, K. S.; Lee, I. B.; Yoon, K. B.; Lee, C. K.; Youm, J. H

    2007-06-15

    The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology.

  5. Program Design Report of the CNC Machine Tool(II)

    International Nuclear Information System (INIS)

    Kim, Jong Kiun; Youm, K. U.; Kim, K. S.; Lee, I. B.; Yoon, K. B.; Lee, C. K.; Youm, J. H.

    2007-06-01

    The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology

  6. Program Design Report of the CNC Machine Tool(III)

    International Nuclear Information System (INIS)

    Kim, Jong Kiun; Youm, K. U.; Kim, K. S.; Lee, I. B.; Yoon, K. B.; Lee, C. K.; Youm, J. H.

    2008-08-01

    The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology

  7. Program Design Report of the CNC Machine Tool(IV)

    International Nuclear Information System (INIS)

    Youm, Ki Un; Lee, I. B.; Youm, J. H.

    2009-09-01

    The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology

  8. Program Design Report of the CNC Machine Tool (I)

    International Nuclear Information System (INIS)

    Kim, Jong Kiun; Youm, K. U.; Kim, K. S.

    2006-08-01

    The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology

  9. Machine Learning-based Intelligent Formal Reasoning and Proving System

    Science.gov (United States)

    Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia

    2018-03-01

    The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.

  10. Firearm microstamping technology: counterinsurgency intelligence gathering tool

    Science.gov (United States)

    Lizotte, Todd E.; Ohar, Orest P.

    2009-05-01

    Warfare relies on effective, accurate and timely intelligence an especially critical task when conducting a counterinsurgency operation [1]. Simply stated counterinsurgency is an intelligence war. Both insurgents and counterinsurgents need effective intelligence capabilities to be successful. Insurgents and counterinsurgents therefore attempt to create and maintain intelligence networks and fight continuously to neutralize each other's intelligence capabilities [1][2]. In such an environment it is obviously an advantage to target or proactively create opportunities to track and map an insurgent movement. Quickly identifying insurgency intelligence assets (Infiltrators) within a host government's infrastructure is the goal. Infiltrators can occupy various areas of government such as security personnel, national police force, government offices or military units. Intentional Firearm Microstamping offers such opportunities when implemented into firearms. Outfitted within firearms purchased and distributed to the host nation's security forces (civilian and military), Intentional Firearm Microstamping (IFM) marks bullet cartridge casings with codes as they are fired from the firearm. IFM is incorporated onto optimum surfaces with the firearm mechanism. The intentional microstamp tooling marks can take the form of alphanumeric codes or encoded geometric codes that identify the firearm. As the firearm is discharged the intentional tooling marks transfer a code to the cartridge casing which is ejected out of the firearm. When recovered at the scene of a firefight or engagement, the technology will provide forensic intelligence allowing the mapping and tracking of small arms traffic patterns within the host nation or identify insurgency force strength and pinpoint firearm sources, such as corrupt/rogue military units or police force. Intentional Firearm Microstamping is a passive mechanical trace technology that can be outfitted or retrofitted to semiautomatic handguns and

  11. Semantics and artificial intelligence in machine translation

    Energy Technology Data Exchange (ETDEWEB)

    King, M

    1981-01-01

    The author exemplifies three types of ambiguity that the introduction of semantics or of AI methods might be expected to solve: word sense, structural, and referential ambiguity. From this point of view she examines the works of Schank, Riesbeck, Minsky, Charniak, and Wilks, and she comes to the conclusion that the systems described will not be of much help for the development of operational MT-systems, except within a well-defined, constrained world. The latter aspect is illustrated by the author by means of a description of the Edinburgh Mecho-project. But, as the vast majority of texts destined for MT does not come from a constrained world, such systems will hardly be used as MT production systems. Still, MT-systems like Eurotra give the chance of making intelligent use of AI ideas. 16 references.

  12. Developing an Intelligent Diagnosis and Assessment E-Learning Tool for Introductory Programming

    Science.gov (United States)

    Huang, Chenn-Jung; Chen, Chun-Hua; Luo, Yun-Cheng; Chen, Hong-Xin; Chuang, Yi-Ta

    2008-01-01

    Recently, a lot of open source e-learning platforms have been offered for free in the Internet. We thus incorporate the intelligent diagnosis and assessment tool into an open software e-learning platform developed for programming language courses, wherein the proposed learning diagnosis assessment tools based on text mining and machine learning…

  13. Robotic edge machining using elastic abrasive tool

    Science.gov (United States)

    Sidorova, A. V.; Semyonov, E. N.; Belomestnykh, A. S.

    2018-03-01

    The article describes a robotic center designed for automation of finishing operations, and analyzes technological aspects of an elastic abrasive tool applied for edge machining. Based on the experimental studies, practical recommendations on the application of the robotic center for finishing operations were developed.

  14. Material Choice for spindle of machine tools

    Science.gov (United States)

    Gouasmi, S.; Merzoug, B.; Abba, G.; Kherredine, L.

    2012-02-01

    The requirements of contemporary industry and the flashing development of modern sciences impose restrictions on the majority of the elements of machines; the resulting financial constraints can be satisfied by a better output of the production equipment. As for those concerning the design, the resistance and the correct operation of the product, these require the development of increasingly precise parts, therefore the use of increasingly powerful tools [5]. The precision of machining and the output of the machine tools are generally determined by the precision of rotation of the spindle, indeed, more this one is large more the dimensions to obtain are in the zone of tolerance and the defects of shape are minimized. During the development of the machine tool, the spindle which by definition is a rotating shaft receiving and transmitting to the work piece or the cutting tool the rotational movement, must be designed according to certain optimal parameters to be able to ensure the precision required. This study will be devoted to the choice of the material of the spindle fulfilling the imposed requirements of precision.

  15. Material Choice for spindle of machine tools

    International Nuclear Information System (INIS)

    Gouasmi, S; Merzoug, B; Kherredine, L; Abba, G

    2012-01-01

    The requirements of contemporary industry and the flashing development of modern sciences impose restrictions on the majority of the elements of machines; the resulting financial constraints can be satisfied by a better output of the production equipment. As for those concerning the design, the resistance and the correct operation of the product, these require the development of increasingly precise parts, therefore the use of increasingly powerful tools [5]. The precision of machining and the output of the machine tools are generally determined by the precision of rotation of the spindle, indeed, more this one is large more the dimensions to obtain are in the zone of tolerance and the defects of shape are minimized. During the development of the machine tool, the spindle which by definition is a rotating shaft receiving and transmitting to the work piece or the cutting tool the rotational movement, must be designed according to certain optimal parameters to be able to ensure the precision required. This study will be devoted to the choice of the material of the spindle fulfilling the imposed requirements of precision.

  16. ANN Based Tool Condition Monitoring System for CNC Milling Machines

    Directory of Open Access Journals (Sweden)

    Mota-Valtierra G.C.

    2011-10-01

    Full Text Available Most of the companies have as objective to manufacture high-quality products, then by optimizing costs, reducing and controlling the variations in its production processes it is possible. Within manufacturing industries a very important issue is the tool condition monitoring, since the tool state will determine the quality of products. Besides, a good monitoring system will protect the machinery from severe damages. For determining the state of the cutting tools in a milling machine, there is a great variety of models in the industrial market, however these systems are not available to all companies because of their high costs and the requirements of modifying the machining tool in order to attach the system sensors. This paper presents an intelligent classification system which determines the status of cutt ers in a Computer Numerical Control (CNC milling machine. This tool state is mainly detected through the analysis of the cutting forces drawn from the spindle motors currents. This monitoring system does not need sensors so it is no necessary to modify the machine. The correct classification is made by advanced digital signal processing techniques. Just after acquiring a signal, a FIR digital filter is applied to the data to eliminate the undesired noisy components and to extract the embedded force components. A Wavelet Transformation is applied to the filtered signal in order to compress the data amount and to optimize the classifier structure. Then a multilayer perceptron- type neural network is responsible for carrying out the classification of the signal. Achieving a reliability of 95%, the system is capable of detecting breakage and a worn cutter.

  17. ATST telescope mount: telescope of machine tool

    Science.gov (United States)

    Jeffers, Paul; Stolz, Günter; Bonomi, Giovanni; Dreyer, Oliver; Kärcher, Hans

    2012-09-01

    The Advanced Technology Solar Telescope (ATST) will be the largest solar telescope in the world, and will be able to provide the sharpest views ever taken of the solar surface. The telescope has a 4m aperture primary mirror, however due to the off axis nature of the optical layout, the telescope mount has proportions similar to an 8 meter class telescope. The technology normally used in this class of telescope is well understood in the telescope community and has been successfully implemented in numerous projects. The world of large machine tools has developed in a separate realm with similar levels of performance requirement but different boundary conditions. In addition the competitive nature of private industry has encouraged development and usage of more cost effective solutions both in initial capital cost and thru-life operating cost. Telescope mounts move relatively slowly with requirements for high stability under external environmental influences such as wind buffeting. Large machine tools operate under high speed requirements coupled with high application of force through the machine but with little or no external environmental influences. The benefits of these parallel development paths and the ATST system requirements are being combined in the ATST Telescope Mount Assembly (TMA). The process of balancing the system requirements with new technologies is based on the experience of the ATST project team, Ingersoll Machine Tools who are the main contractor for the TMA and MT Mechatronics who are their design subcontractors. This paper highlights a number of these proven technologies from the commercially driven machine tool world that are being introduced to the TMA design. Also the challenges of integrating and ensuring that the differences in application requirements are accounted for in the design are discussed.

  18. BRAIN. Broad Research in Artificial Intelligence and Neuroscience-Are We Safe Enough in the Future of Artificial Intelligence? A Discussion on Machine Ethics and Artificial Intelligence Safety

    OpenAIRE

    Utku Köse

    2018-01-01

    Nowadays, there is a serious anxiety on the existence of dangerous intelligent systems and it is not just a science-fiction idea of evil machines like the ones in well-known Terminator movie or any other movies including intelligent robots – machines threatening the existence of humankind. So, there is a great interest in some alternative research works under the topics of Machine Ethics, Artificial Intelligence Safety and the associated research topics like Future of Artificial I...

  19. Machine tool metrology an industrial handbook

    CERN Document Server

    Smith, Graham T

    2016-01-01

    Maximizing reader insights into the key scientific disciplines of Machine Tool Metrology, this text will prove useful for the industrial-practitioner and those interested in the operation of machine tools. Within this current level of industrial-content, this book incorporates significant usage of the existing published literature and valid information obtained from a wide-spectrum of manufacturers of plant, equipment and instrumentation before putting forward novel ideas and methodologies. Providing easy to understand bullet points and lucid descriptions of metrological and calibration subjects, this book aids reader understanding of the topics discussed whilst adding a voluminous-amount of footnotes utilised throughout all of the chapters, which adds some additional detail to the subject. Featuring an extensive amount of photographic-support, this book will serve as a key reference text for all those involved in the field. .

  20. Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

    Science.gov (United States)

    Salehi, Mojtaba; Bahreininejad, Ardeshir

    2011-08-01

    Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

  1. Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

    Science.gov (United States)

    Asoodeh, Mojtaba; Bagheripour, Parisa

    2012-01-01

    Measurement of compressional, shear, and Stoneley wave velocities, carried out by dipole sonic imager (DSI) logs, provides invaluable data in geophysical interpretation, geomechanical studies and hydrocarbon reservoir characterization. The presented study proposes an improved methodology for making a quantitative formulation between conventional well logs and sonic wave velocities. First, sonic wave velocities were predicted from conventional well logs using artificial neural network, fuzzy logic, and neuro-fuzzy algorithms. Subsequently, a committee machine with intelligent systems was constructed by virtue of hybrid genetic algorithm-pattern search technique while outputs of artificial neural network, fuzzy logic and neuro-fuzzy models were used as inputs of the committee machine. It is capable of improving the accuracy of final prediction through integrating the outputs of aforementioned intelligent systems. The hybrid genetic algorithm-pattern search tool, embodied in the structure of committee machine, assigns a weight factor to each individual intelligent system, indicating its involvement in overall prediction of DSI parameters. This methodology was implemented in Asmari formation, which is the major carbonate reservoir rock of Iranian oil field. A group of 1,640 data points was used to construct the intelligent model, and a group of 800 data points was employed to assess the reliability of the proposed model. The results showed that the committee machine with intelligent systems performed more effectively compared with individual intelligent systems performing alone.

  2. Automated business process management – in times of digital transformation using machine learning or artificial intelligence

    Directory of Open Access Journals (Sweden)

    Paschek Daniel

    2017-01-01

    Full Text Available The continuous optimization of business processes is still a challenge for companies. In times of digital transformation, faster changing internal and external framework conditions and new customer expectations for fastest delivery and best quality of goods and many more, companies should set up their internal process at the best way. But what to do if framework conditions changed unexpectedly? The purpose of the paper is to analyse how the digital transformation will impact the Business Process Management (BPM while using methods like machine learning or artificial intelligence. Therefore, the core components will be explained, compared and set up in relation. To identify application areas interviews and analysis will be held up with digital companies. The finding of the paper will be recommendation for action in the field of BPM and process optimization through machine learning and artificial intelligence. The Approach of optimizing and management processes via machine learning and artificial intelligence will support companies to decide which tool will be the best for automated BPM.

  3. Machine learning based Intelligent cognitive network using fog computing

    Science.gov (United States)

    Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

    2017-05-01

    In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

  4. Time-series prediction and applications a machine intelligence approach

    CERN Document Server

    Konar, Amit

    2017-01-01

    This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at...

  5. An intelligent tool for activity data collection.

    Science.gov (United States)

    Sarkar, A M Jehad

    2011-01-01

    Activity recognition systems using simple and ubiquitous sensors require a large variety of real-world sensor data for not only evaluating their performance but also training the systems for better functioning. However, a tremendous amount of effort is required to setup an environment for collecting such data. For example, expertise and resources are needed to design and install the sensors, controllers, network components, and middleware just to perform basic data collections. It is therefore desirable to have a data collection method that is inexpensive, flexible, user-friendly, and capable of providing large and diverse activity datasets. In this paper, we propose an intelligent activity data collection tool which has the ability to provide such datasets inexpensively without physically deploying the testbeds. It can be used as an inexpensive and alternative technique to collect human activity data. The tool provides a set of web interfaces to create a web-based activity data collection environment. It also provides a web-based experience sampling tool to take the user's activity input. The tool generates an activity log using its activity knowledge and the user-given inputs. The activity knowledge is mined from the web. We have performed two experiments to validate the tool's performance in producing reliable datasets.

  6. NEW ASPECTS OF MANUFACTURING ON MACHINE TOOLS

    Directory of Open Access Journals (Sweden)

    Dorian ŞTEF

    2012-11-01

    Full Text Available In the paper are presented the modality to minimize the production time and increase the machining accuracy in the milling operations and to analyze different milling strategies. In this analyze the only on modification for face milling operation was to change the tool geometry by mounted a special shape insert WIPER, that have a different geometry, and for pocketing operations the changes was by using different milling strategies for manufacturing pockets. The application for this analyze is a simulation between the process technologies in virtual fabrication made using Esprit CAM (Computer Aided Manufacturing software.

  7. Keeping you safe by making machine tools safe

    CERN Multimedia

    2012-01-01

    CERN’s third safety objective for 2012 concerns the safety of equipment - and machine tools in particular.   There are three prerequisites for ensuring that a machine tool can be used safely: ·      the machine tool must comply with Directive 2009/104/EC, ·      the layout of the workshop must be compliant, and ·      everyone who uses the machine tool must be trained. Provided these conditions are met, the workshop head can grant authorisation to use the machine tool. To fulfil this objective, an inventory of the machine tools must be drawn up and the people responsible for them identified. The HSE Unit's Safety Inspection Service produces compliance reports for the machine tools. In order to meet the third objective set by the Director-General, the section has doubled its capacity to carry out inspections: ...

  8. Groundwater vulnerability indices conditioned by Supervised Intelligence Committee Machine (SICM).

    Science.gov (United States)

    Nadiri, Ata Allah; Gharekhani, Maryam; Khatibi, Rahman; Sadeghfam, Sina; Moghaddam, Asghar Asghari

    2017-01-01

    This research presents a Supervised Intelligent Committee Machine (SICM) model to assess groundwater vulnerability indices of an aquifer. SICM uses Artificial Neural Networks (ANN) to overarch three Artificial Intelligence (AI) models: Support Vector Machine (SVM), Neuro-Fuzzy (NF) and Gene Expression Programming (GEP). Each model uses the DRASTIC index, the acronym of 7 geological, hydrological and hydrogeological parameters, which collectively represents intrinsic (or natural) vulnerability and gives a sense of contaminants, such as nitrate-N, penetrating aquifers from the surface. These models are trained to modify or condition their DRASTIC index values by measured nitrate-N concentration. The three AI-techniques often perform similarly but have differences as well and therefore SICM exploits the situation to improve the modeled values by producing a hybrid modeling results through selecting better performing SVM, NF and GEP components. The models of the study area at Ardabil aquifer show that the vulnerability indices by the DRASTIC framework produces sharp fronts but AI models smoothen the fronts and reflect a better correlation with observed nitrate values; SICM improves on the performances of three AI models and cope well with heterogeneity and uncertain parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. An Intelligent Tool for Activity Data Collection

    Directory of Open Access Journals (Sweden)

    A. M. Jehad Sarkar

    2011-04-01

    Full Text Available Activity recognition systems using simple and ubiquitous sensors require a large variety of real-world sensor data for not only evaluating their performance but also training the systems for better functioning. However, a tremendous amount of effort is required to setup an environment for collecting such data. For example, expertise and resources are needed to design and install the sensors, controllers, network components, and middleware just to perform basic data collections. It is therefore desirable to have a data collection method that is inexpensive, flexible, user-friendly, and capable of providing large and diverse activity datasets. In this paper, we propose an intelligent activity data collection tool which has the ability to provide such datasets inexpensively without physically deploying the testbeds. It can be used as an inexpensive and alternative technique to collect human activity data. The tool provides a set of web interfaces to create a web-based activity data collection environment. It also provides a web-based experience sampling tool to take the user’s activity input. The tool generates an activity log using its activity knowledge and the user-given inputs. The activity knowledge is mined from the web. We have performed two experiments to validate the tool’s performance in producing reliable datasets.

  10. Coordinate measurement machines as an alignment tool

    International Nuclear Information System (INIS)

    Wand, B.T.

    1991-03-01

    In February of 1990 the Stanford Linear Accelerator Center (SLAC) purchased a LEITZ PM 12-10-6 CMM (Coordinate measurement machine). The machine is shared by the Quality Control Team and the Alignment Team. One of the alignment tasks in positioning beamline components in a particle accelerator is to define the component's magnetic centerline relative to external fiducials. This procedure, called fiducialization, is critical to the overall positioning tolerance of a magnet. It involves the definition of the magnetic center line with respect to the mechanical centerline and the transfer of the mechanical centerline to the external fiducials. To perform the latter a magnet coordinate system has to be established. This means defining an origin and the three rotation angles of the magnet. The datum definition can be done by either optical tooling techniques or with a CMM. As optical tooling measurements are very time consuming, not automated and are prone to errors, it is desirable to use the CMM fiducialization method instead. The establishment of a magnet coordinate system based on the mechanical center and the transfer to external fiducials will be discussed and presented with 2 examples from the Stanford Linear Collider (SLC). 7 figs

  11. Advances in Intelligent Modelling and Simulation Simulation Tools and Applications

    CERN Document Server

    Oplatková, Zuzana; Carvalho, Marco; Kisiel-Dorohinicki, Marek

    2012-01-01

    The human capacity to abstract complex systems and phenomena into simplified models has played a critical role in the rapid evolution of our modern industrial processes and scientific research. As a science and an art, Modelling and Simulation have been one of the core enablers of this remarkable human trace, and have become a topic of great importance for researchers and practitioners. This book was created to compile some of the most recent concepts, advances, challenges and ideas associated with Intelligent Modelling and Simulation frameworks, tools and applications. The first chapter discusses the important aspects of a human interaction and the correct interpretation of results during simulations. The second chapter gets to the heart of the analysis of entrepreneurship by means of agent-based modelling and simulations. The following three chapters bring together the central theme of simulation frameworks, first describing an agent-based simulation framework, then a simulator for electrical machines, and...

  12. Social Intelligence in a Human-Machine Collaboration System

    Science.gov (United States)

    Nakajima, Hiroshi; Morishima, Yasunori; Yamada, Ryota; Brave, Scott; Maldonado, Heidy; Nass, Clifford; Kawaji, Shigeyasu

    In this information society of today, it is often argued that it is necessary to create a new way of human-machine interaction. In this paper, an agent with social response capabilities has been developed to achieve this goal. There are two kinds of information that is exchanged by two entities: objective and functional information (e.g., facts, requests, states of matters, etc.) and subjective information (e.g., feelings, sense of relationship, etc.). Traditional interactive systems have been designed to handle the former kind of information. In contrast, in this study social agents handling the latter type of information are presented. The current study focuses on sociality of the agent from the view point of Media Equation theory. This article discusses the definition, importance, and benefits of social intelligence as agent technology and argues that social intelligence has a potential to enhance the user's perception of the system, which in turn can lead to improvements of the system's performance. In order to implement social intelligence in the agent, a mind model has been developed to render affective expressions and personality of the agent. The mind model has been implemented in a human-machine collaborative learning system. One differentiating feature of the collaborative learning system is that it has an agent that performs as a co-learner with which the user interacts during the learning session. The mind model controls the social behaviors of the agent, thus making it possible for the user to have more social interactions with the agent. The experiment with the system suggested that a greater degree of learning was achieved when the students worked with the co-learner agent and that the co-learner agent with the mind model that expressed emotions resulted in a more positive attitude toward the system.

  13. INFLUENCE OF STRUCTURE COMPONENTS ON MACHINE TOOL ACCURACY

    Directory of Open Access Journals (Sweden)

    ConstantinSANDU

    2017-11-01

    Full Text Available For machine tools, the accuracy of the parts of the machine tool structure (after roughing should be subject to relief and natural or artificial aging. The performance of the current accuracy of machine tools as linearity or flatness was higher than 5 μm/m. Under this value there are great difficulties. The performance of the structure of the machine tools in the manufacture of structural parts of machine tools, with a flatness accuracy that the linearity of about 2 μm/m, are significant deviations form of their half-finished. This article deals with the influence of errors of form of semifinished and machined parts on them, on their shape and especially what happens to structure machine tools when the components of the structure were assembling this.

  14. Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

    CERN Document Server

    Hu, Fei

    2012-01-01

    Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

  15. On Intelligent Design and Planning Method of Process Route Based on Gun Breech Machining Process

    Science.gov (United States)

    Hongzhi, Zhao; Jian, Zhang

    2018-03-01

    The paper states an approach of intelligent design and planning of process route based on gun breech machining process, against several problems, such as complex machining process of gun breech, tedious route design and long period of its traditional unmanageable process route. Based on gun breech machining process, intelligent design and planning system of process route are developed by virtue of DEST and VC++. The system includes two functional modules--process route intelligent design and its planning. The process route intelligent design module, through the analysis of gun breech machining process, summarizes breech process knowledge so as to complete the design of knowledge base and inference engine. And then gun breech process route intelligently output. On the basis of intelligent route design module, the final process route is made, edited and managed in the process route planning module.

  16. Analysis on machine tool systems using spindle vibration monitoring for automatic tool changer

    Directory of Open Access Journals (Sweden)

    Shang-Liang Chen

    2015-12-01

    Full Text Available Recently, the intelligent systems of technology have become one of the major items in the development of machine tools. One crucial technology is the machinery status monitoring function, which is required for abnormal warnings and the improvement of cutting efficiency. During processing, the mobility act of the spindle unit determines the most frequent and important part such as automatic tool changer. The vibration detection system includes the development of hardware and software, such as vibration meter, signal acquisition card, data processing platform, and machine control program. Meanwhile, based on the difference between the mechanical configuration and the desired characteristics, it is difficult for a vibration detection system to directly choose the commercially available kits. For this reason, it was also selected as an item for self-development research, along with the exploration of a significant parametric study that is sufficient to represent the machine characteristics and states. However, we also launched the development of functional parts of the system simultaneously. Finally, we entered the conditions and the parameters generated from both the states and the characteristics into the developed system to verify its feasibility.

  17. Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines

    OpenAIRE

    Soori, Mohsen; Arezoo, Behrooz; Habibi, Mohsen

    2014-01-01

    Virtual manufacturing systems can provide useful means for products to be manufactured without the need of physical testing on the shop floor. As a result, the time and cost of part production can be decreased. There are different error sources in machine tools such as tool deflection, geometrical deviations of moving axis and thermal distortions of machine tool structures. Some of these errors can be decreased by controlling the machining process and environmental parameters. However other e...

  18. Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines

    OpenAIRE

    Soori, Mohsen; Arezoo, Behrooz; Habibi, Mohsen

    2016-01-01

    Virtual manufacturing systems can provide useful means for products to be manufactured without the need of physical testing on the shop floor. As a result, the time and cost of part production can be decreased. There are different error sources in machine tools such as tool deflection, geometrical deviations of moving axis and thermal distortions of machine tool structures. Some of these errors can be decreased by controlling the machining process and environmental parameters. However other e...

  19. Research on intelligent machine self-perception method based on LSTM

    Science.gov (United States)

    Wang, Qiang; Cheng, Tao

    2018-05-01

    In this paper, we use the advantages of LSTM in feature extraction and processing high-dimensional and complex nonlinear data, and apply it to the autonomous perception of intelligent machines. Compared with the traditional multi-layer neural network, this model has memory, can handle time series information of any length. Since the multi-physical domain signals of processing machines have a certain timing relationship, and there is a contextual relationship between states and states, using this deep learning method to realize the self-perception of intelligent processing machines has strong versatility and adaptability. The experiment results show that the method proposed in this paper can obviously improve the sensing accuracy under various working conditions of the intelligent machine, and also shows that the algorithm can well support the intelligent processing machine to realize self-perception.

  20. Design of a Three-Axis Machine Tool Module

    National Research Council Canada - National Science Library

    Childers, Marshal

    2003-01-01

    This report documents the design improvement process of the components in a tool module for a three-axis machine tool, which occurred during the period of March-April 2002 in support of a critical U.S...

  1. Stochastic Distribution of Wear of Carbide Tools during Machining ...

    African Journals Online (AJOL)

    Journal of the Nigerian Association of Mathematical Physics ... The stochastic point model was used to determine the rate of wear distribution of the carbide tool ... Keywords: cutting speed, feed rate, machining time, tool life, reliability, wear.

  2. Design principles of metal-cutting machine tools

    CERN Document Server

    Koenigsberger, F

    1964-01-01

    Design Principles of Metal-Cutting Machine Tools discusses the fundamentals aspects of machine tool design. The book covers the design consideration of metal-cutting machine, such as static and dynamic stiffness, operational speeds, gearboxes, manual, and automatic control. The text first details the data calculation and the general requirements of the machine tool. Next, the book discusses the design principles, which include stiffness and rigidity of the separate constructional elements and their combined behavior under load, as well as electrical, mechanical, and hydraulic drives for the op

  3. Ecological Design of Cooperative Human-Machine Interfaces for Safety of Intelligent Transport Systems

    Directory of Open Access Journals (Sweden)

    Orekhov Aleksandr

    2016-01-01

    Full Text Available The paper describes research results in the domain of cooperative intelligent transport systems. The requirements for human-machine interface considering safety issue of for intelligent transport systems (ITSare analyzed. Profiling of the requirements to cooperative human-machine interface (CHMI for such systems including requirements to usability and safety is based on a set of standards for ITSs. An approach and design technique of cooperative human-machine interface for ITSs are suggested. The architecture of cloud-based CHMI for intelligent transport systems has been developed. The prototype of software system CHMI4ITSis described.

  4. Market for multiaxis laser machine tools

    Science.gov (United States)

    Ream, Stanley L.

    1991-03-01

    While it's true that this is an exciting topic, it niay be more exciting than profitable, but it certainly has captured the attention of a lot of us laser folks, and it keeps growing almost because it wants to. First of all let me comment briefly with a word from our sponsor that GE Fanuc is one of the several ways the Fanuc laser product gets into the United States. We market it, GM Fanuc also markets it, and of course it shows up on Japanese machine tool built products. The information in this little presentation came from discussions with you folks wherever possible. In some cases I was unable to make contact with the horse's mouth as it were, but we got roundabout information so it's not gospel, but it's close. We've also had some updated information at the show here updated rumors maybe that suggest that some of the numbers may be high or low. I think in the aggregate it's not too far off.

  5. An expert machine tools selection system for turning operation

    NARCIS (Netherlands)

    Tan, C.F.; Khalil, S.N.; Karjanto, J.; Wahidin, L.S.; Chen, W.; Rauterberg, G.W.M.

    2015-01-01

    The turning machining process is an important process in the manufacturing industry. It is important to select the right tool for the turning process so that the manufacturing cost will be decreased. The main objective of this research is to select the most suitable machine tools with respect to

  6. Development and Experimental Evaluation of Machine-Learning Techniques for an Intelligent Hairy Scalp Detection System

    Directory of Open Access Journals (Sweden)

    Wei-Chien Wang

    2018-05-01

    Full Text Available Deep learning has become the most popular research subject in the fields of artificial intelligence (AI and machine learning. In October 2013, MIT Technology Review commented that deep learning was a breakthrough technology. Deep learning has made progress in voice and image recognition, image classification, and natural language processing. Prior to deep learning, decision tree, linear discriminant analysis (LDA, support vector machines (SVM, k-nearest neighbors algorithm (K-NN, and ensemble learning were popular in solving classification problems. In this paper, we applied the previously mentioned and deep learning techniques to hairy scalp images. Hairy scalp problems are usually diagnosed by non-professionals in hair salons, and people with such problems may be advised by these non-professionals. Additionally, several common scalp problems are similar; therefore, non-experts may provide incorrect diagnoses. Hence, scalp problems have worsened. In this work, we implemented and compared the deep-learning method, the ImageNet-VGG-f model Bag of Words (BOW, with machine-learning classifiers, and histogram of oriented gradients (HOG/pyramid histogram of oriented gradients (PHOG with machine-learning classifiers. The tools from the classification learner apps were used for hairy scalp image classification. The results indicated that deep learning can achieve an accuracy of 89.77% when the learning rate is 1 × 10−4, and this accuracy is far higher than those achieved by BOW with SVM (80.50% and PHOG with SVM (53.0%.

  7. Thermal Analysis for Condition Monitoring of Machine Tool Spindles

    International Nuclear Information System (INIS)

    Clough, D; Fletcher, S; Longstaff, A P; Willoughby, P

    2012-01-01

    Decreasing tolerances on parts manufactured, or inspected, on machine tools increases the requirement to have a greater understanding of machine tool capabilities, error sources and factors affecting asset availability. Continuous usage of a machine tool during production processes causes heat generation typically at the moving elements, resulting in distortion of the machine structure. These effects, known as thermal errors, can contribute a significant percentage of the total error in a machine tool. There are a number of design solutions available to the machine tool builder to reduce thermal error including, liquid cooling systems, low thermal expansion materials and symmetric machine tool structures. However, these can only reduce the error not eliminate it altogether. It is therefore advisable, particularly in the production of high value parts, for manufacturers to obtain a thermal profile of their machine, to ensure it is capable of producing in tolerance parts. This paper considers factors affecting practical implementation of condition monitoring of the thermal errors. In particular is the requirement to find links between temperature, which is easily measureable during production and the errors which are not. To this end, various methods of testing including the advantages of thermal images are shown. Results are presented from machines in typical manufacturing environments, which also highlight the value of condition monitoring using thermal analysis.

  8. Research on the tool holder mode in high speed machining

    Science.gov (United States)

    Zhenyu, Zhao; Yongquan, Zhou; Houming, Zhou; Xiaomei, Xu; Haibin, Xiao

    2018-03-01

    High speed machining technology can improve the processing efficiency and precision, but also reduce the processing cost. Therefore, the technology is widely regarded in the industry. With the extensive application of high-speed machining technology, high-speed tool system has higher and higher requirements on the tool chuck. At present, in high speed precision machining, several new kinds of clip heads are as long as there are heat shrinkage tool-holder, high-precision spring chuck, hydraulic tool-holder, and the three-rib deformation chuck. Among them, the heat shrinkage tool-holder has the advantages of high precision, high clamping force, high bending rigidity and dynamic balance, etc., which are widely used. Therefore, it is of great significance to research the new requirements of the machining tool system. In order to adapt to the requirement of high speed machining precision machining technology, this paper expounds the common tool holder technology of high precision machining, and proposes how to select correctly tool clamping system in practice. The characteristics and existing problems are analyzed in the tool clamping system.

  9. Study of on-machine error identification and compensation methods for micro machine tools

    International Nuclear Information System (INIS)

    Wang, Shih-Ming; Yu, Han-Jen; Lee, Chun-Yi; Chiu, Hung-Sheng

    2016-01-01

    Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results

  10. Data Mining Practical Machine Learning Tools and Techniques

    CERN Document Server

    Witten, Ian H; Hall, Mark A

    2011-01-01

    Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place

  11. Intelligent Human Machine Interface Design for Advanced Product Life Cycle Management Systems

    OpenAIRE

    Ahmed, Zeeshan

    2010-01-01

    Designing and implementing an intelligent and user friendly human machine interface for any kind of software or hardware oriented application is always be a challenging task for the designers and developers because it is very difficult to understand the psychology of the user, nature of the work and best suit of the environment. This research paper is basically about to propose an intelligent, flexible and user friendly machine interface for Product Life Cycle Management products or PDM Syste...

  12. Responding to the will of the machine: Leadership in the age of artificial intelligence

    OpenAIRE

    NAQVI, Al

    2017-01-01

    Abstract. The advent of artificial intelligence in the modern economy will revolutionize the workplace of tomorrow. It will alsocreate never-seen-before challenges for leadership. The current leadership theory is extensive but it does not address on how to lead in a workplace composed of intelligent machines. However, it can be observed that leadership theory tends to develop in tandem with the developments in technology - metaphorically termed as will of the machine in this article. Specific...

  13. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  14. Implementing Machine Learning in the PCWG Tool

    Energy Technology Data Exchange (ETDEWEB)

    Clifton, Andrew; Ding, Yu; Stuart, Peter

    2016-12-13

    The Power Curve Working Group (www.pcwg.org) is an ad-hoc industry-led group to investigate the performance of wind turbines in real-world conditions. As part of ongoing experience-sharing exercises, machine learning has been proposed as a possible way to predict turbine performance. This presentation provides some background information about machine learning and how it might be implemented in the PCWG exercises.

  15. Traceability of On-Machine Tool Measurement: A Review

    Science.gov (United States)

    Gomez-Acedo, Eneko; Kortaberria, Gorka; Olarra, Aitor

    2017-01-01

    Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand. PMID:28696358

  16. New active machine tool drive mounting on the frame

    Directory of Open Access Journals (Sweden)

    Švéda J.

    2007-10-01

    Full Text Available The paper deals with the new active mounting of the machine tool drives. The commonly used machine tools are at this time mainly equipped with fix-mounting of the feed drives. This structure causes full transmission of the force shocks to the machine bed and thereby restricts the dynamic properties of the motion axis and the whole machine. The spring-mounting of the feed drives is one of the possibilities how to partially suppress the vibrations. The force that reacts to the machine tool bed is transformed thereby the vibrations are lightly reduced. Unfortunately the transformation is not fully controlled. The new active mounting of the machine tool drives allows to fully control the force behaviour that react to the machine body. Thereby the number of excited frequencies on the machine tool bed is significantly reduced. The active variant of the feed drive mounting is characterized by the synergistic cooperation between two series-connected actuators (“motor on motor”. The paper briefly describes design, control techniques and optimization of the feed drives with the new active mounting conception.

  17. Traceability of On-Machine Tool Measurement: A Review.

    Science.gov (United States)

    Mutilba, Unai; Gomez-Acedo, Eneko; Kortaberria, Gorka; Olarra, Aitor; Yagüe-Fabra, Jose A

    2017-07-11

    Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand.

  18. Artificial intelligence tool development and applications to nuclear power

    International Nuclear Information System (INIS)

    Naser, J.A.

    1987-01-01

    Two parallel efforts are being performed at the Electric Power Research Institute (EPRI) to help the electric utility industry take advantage of the expert system technology. The first effort is the development of expert system building tools, which are tailored to electric utility industry applications. The second effort is the development of expert system applications. These two efforts complement each other. The application development tests the tools and identifies additional tool capabilities that are required. The tool development helps define the applications that can be successfully developed. Artificial intelligence, as demonstrated by the developments described is being established as a credible technological tool for the electric utility industry. The challenge to transferring artificial intelligence technology and an understanding of its potential to the electric utility industry is to gain an understanding of the problems that reduce power plant performance and identify which can be successfully addressed using artificial intelligence

  19. A Method for Design of Modular Reconfigurable Machine Tools

    Directory of Open Access Journals (Sweden)

    Zhengyi Xu

    2017-02-01

    Full Text Available Presented in this paper is a method for the design of modular reconfigurable machine tools (MRMTs. An MRMT is capable of using a minimal number of modules through reconfiguration to perform the required machining tasks for a family of parts. The proposed method consists of three steps: module identification, module determination, and layout synthesis. In the first step, the module components are collected from a family of general-purpose machines to establish a module library. In the second step, for a given family of parts to be machined, a set of needed modules are selected from the module library to construct a desired reconfigurable machine tool. In the third step, a final machine layout is decided though evaluation by considering a number of performance indices. Based on this method, a software package has been developed that can design an MRMT for a given part family.

  20. VIRTUAL MODELING OF A NUMERICAL CONTROL MACHINE TOOL USED FOR COMPLEX MACHINING OPERATIONS

    Directory of Open Access Journals (Sweden)

    POPESCU Adrian

    2015-11-01

    Full Text Available This paper presents the 3D virtual model of the numerical control machine Modustar 100, in terms of machine elements. This is a CNC machine of modular construction, all components allowing the assembly in various configurations. The paper focused on the design of the subassemblies specific to the axes numerically controlled by means of CATIA v5, which contained different drive kinematic chains of different translation modules that ensures translation on X, Y and Z axis. Machine tool development for high speed and highly precise cutting demands employment of advanced simulation techniques witch it reflect on cost of total development of the machine.

  1. Integrating human factors and artificial intelligence in the development of human-machine cooperation

    NARCIS (Netherlands)

    Maanen, P.P. van; Lindenberg, J.; Neericx, M.A.

    2005-01-01

    Increasing machine intelligence leads to a shift from a mere interactive to a much more complex cooperative human-machine relation requiring a multidisciplinary development approach. This paper presents a generic multidisciplinary cognitive engineering method CE+ for the integration of human factors

  2. Simulation Tools for Electrical Machines Modelling: Teaching and ...

    African Journals Online (AJOL)

    Simulation tools are used both for research and teaching to allow a good comprehension of the systems under study before practical implementations. This paper illustrates the way MATLAB is used to model non-linearites in synchronous machine. The machine is modeled in rotor reference frame with currents as state ...

  3. Cyclic machine scheduling with tool transportation - additional calculations

    NARCIS (Netherlands)

    Kuijpers, C.M.H.

    2001-01-01

    In the PhD Thesis of Kuijpers a cyclic machine scheduling problem with tool transportation is considered. For the problem with two machines, it is shown that there always exists an optimal schedule with a certain structure. This is done by means of an elaborate case study. For a number of cases some

  4. Job Grading Standard for Machine Tool Operator, WG-3431.

    Science.gov (United States)

    Civil Service Commission, Washington, DC. Bureau of Policies and Standards.

    The standard covers nonsupervisory work involved in the set up, adjustment, and operation of conventional machine tools to perform machining operations in the manufacture and repair of castings, forgings, or parts from raw stock made of various metals, metal alloys, and other materials. A general description of the job at both the WG-8 and WG-9…

  5. Artificial intelligence tools decision support systems in condition monitoring and diagnosis

    CERN Document Server

    Galar Pascual, Diego

    2015-01-01

    Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

  6. Design of a novel parallel reconfigurable machine tool

    CSIR Research Space (South Africa)

    Modungwa, D

    2008-06-01

    Full Text Available of meeting the demands for high mechanical dexterity adaptation as well as high stiffness necessary for mould and die re-conditioning. This paper presents, the design of parallel reconfigurable machine tool (PRMT) based on both application...

  7. A Survey of Open Source Tools for Business Intelligence

    DEFF Research Database (Denmark)

    Thomsen, Christian; Pedersen, Torben Bach

    2009-01-01

    The industrial use of open source Business Intelligence (BI) tools is becoming more common, but is still not as widespread as for other types of software. It is therefore of interest to explore which possibilities are available for open source BI and compare the tools. In this survey paper, we co...

  8. Some Notes About Artificial Intelligence as New Mathematical Tool

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-04-01

    Full Text Available Mathematics is a mere instance of First-Order Predicate Calculus. Therefore it belongs to applied Monotonic Logic. So, we found the limitations of classical logic reasoning and the clear advantages of Fuzzy Logic and many other new interesting tools. We present here some of the more usefulness tools of this new field of Mathematics so-called Artificial Intelligence.

  9. Practical implementation of machine tool metrology and maintenance management systems

    International Nuclear Information System (INIS)

    Perkins, C; Longstaff, A P; Fletcher, S; Willoughby, P

    2012-01-01

    Maximising asset utilisation and minimising downtime and waste are becoming increasingly important to all manufacturing facilities as competition increases and profits decrease. The tools to assist with monitoring these machining processes are becoming more and more in demand. A system designed to fulfil the needs of machine tool operators and supervisors has been developed and its impact on the precision manufacturing industry is being considered. The benefits of implementing this system, compared to traditional methods, will be discussed here.

  10. PECULIARITIES OF THE TECHNOLOGY OF CONTINUOUS CASTING OF SLUGS OF MACHINE- AND MACHINE-TOOL-BUILDING

    OpenAIRE

    E. B. Demchenko; E. I. Marukovich

    2006-01-01

    The peculiarities of technology of continuous casting of ingots of machine- and machine tool building are shown. At development of technology it is necessary to subject the nomenclature of ingots to analysis in order to reveal expediency of their production by means of continuous casting.

  11. Case study of virtual reality in CNC machine tool exhibition

    Directory of Open Access Journals (Sweden)

    Kao Yung-Chou

    2017-01-01

    Full Text Available Exhibition and demonstration are generally used in the promotion and sale-assistance of manufactured products. However, the transportation cost of the real goods from the vender factory to the exposition venue is generally expensive for huge and heavy commodity. With the advancement of computing, graphics, mobile apps, and mobile hardware the 3D visibility technology is getting more and more popular to be adopted in visual-assisted communication such as amusement games. Virtual reality (VR technology has therefore being paid great attention in emulating expensive small and/or huge and heavy equipment. Virtual reality can be characterized as 3D extension with Immersion, Interaction and Imagination. This paper was then be focused on the study of virtual reality in the assistance of CNC machine tool demonstration and exhibition. A commercial CNC machine tool was used in this study to illustrate the effectiveness and usability of using virtual reality for an exhibition. The adopted CNC machine tool is a large and heavy mill-turn machine with the width up to eleven meters and weighted about 35 tons. A head-mounted display (HMD was attached to the developed VR CNC machine tool for the immersion viewing. A user can see around the 3D scene of the large mill-turn machine and the operation of the virtual CNC machine can be actuated by bare hand. Coolant was added to demonstrate more realistic operation while collision detection function was also added to remind the operator. The developed VR demonstration system has been presented in the 2017 Taipei International Machine Tool Show (TIMTOS 2017. This case study has shown that young engineers and/or students are very impressed by the VR-based demonstration while elder persons could not adapt themselves easily to the VR-based scene because of eyesight issues. However, virtual reality has successfully being adopted and integrated with the CNC machine tool in an international show. Another machine tool on

  12. Development of Dual-Axis MEMS Accelerometers for Machine Tools Vibration Monitoring

    Directory of Open Access Journals (Sweden)

    Chih-Yung Huang

    2016-07-01

    Full Text Available With the development of intelligent machine tools, monitoring the vibration by the accelerometer is an important issue. Accelerometers used for measuring vibration signals during milling processes require the characteristics of high sensitivity, high resolution, and high bandwidth. A commonly used accelerometer is the lead zirconate titanate (PZT type; however, integrating it into intelligent modules is excessively expensive and difficult. Therefore, the micro electro mechanical systems (MEMS accelerometer is an alternative with the advantages of lower price and superior integration. In the present study, we integrated two MEMS accelerometer chips into a low-pass filter and housing to develop a low-cost dual-axis accelerometer with a bandwidth of 5 kHz and a full scale range of ±50 g for measuring machine tool vibration. In addition, a platform for measuring the linearity, cross-axis sensitivity and frequency response of the MEMS accelerometer by using the back-to-back calibration method was also developed. Finally, cutting experiments with steady and chatter cutting were performed to verify the results of comparing the MEMS accelerometer with the PZT accelerometer in the time and frequency domains. The results demonstrated that the dual-axis MEMS accelerometer is suitable for monitoring the vibration of machine tools at low cost.

  13. Behavior Analysis and the Quest for Machine Intelligence.

    Science.gov (United States)

    Stephens, Kenneth R.; Hutchison, William R.

    1993-01-01

    Discusses three approaches to building intelligent systems: artificial intelligence, neural networks, and behavior analysis. BANKET, an object-oriented software system, is explained; a commercial application of BANKET is described; and a collaborative effort between the academic and business communities for the use of BANKET is discussed.…

  14. Assisting the Tooling and Machining Industry to Become Energy Efficient

    Energy Technology Data Exchange (ETDEWEB)

    Curry, Bennett [Arizona Commerce Authority, Phoenix, AZ (United States)

    2016-12-30

    The Arizona Commerce Authority (ACA) conducted an Innovation in Advanced Manufacturing Grant Competition to support and grow southern and central Arizona’s Aerospace and Defense (A&D) industry and its supply chain. The problem statement for this grant challenge was that many A&D machining processes utilize older generation CNC machine tool technologies that can result an inefficient use of resources – energy, time and materials – compared to the latest state-of-the-art CNC machines. Competitive awards funded projects to develop innovative new tools and technologies that reduce energy consumption for older generation machine tools and foster working relationships between industry small to medium-sized manufacturing enterprises and third-party solution providers. During the 42-month term of this grant, 12 competitive awards were made. Final reports have been included with this submission.

  15. Modelling Machine Tools using Structure Integrated Sensors for Fast Calibration

    Directory of Open Access Journals (Sweden)

    Benjamin Montavon

    2018-02-01

    Full Text Available Monitoring of the relative deviation between commanded and actual tool tip position, which limits the volumetric performance of the machine tool, enables the use of contemporary methods of compensation to reduce tolerance mismatch and the uncertainties of on-machine measurements. The development of a primarily optical sensor setup capable of being integrated into the machine structure without limiting its operating range is presented. The use of a frequency-modulating interferometer and photosensitive arrays in combination with a Gaussian laser beam allows for fast and automated online measurements of the axes’ motion errors and thermal conditions with comparable accuracy, lower cost, and smaller dimensions as compared to state-of-the-art optical measuring instruments for offline machine tool calibration. The development is tested through simulation of the sensor setup based on raytracing and Monte-Carlo techniques.

  16. Lathe tool bit and holder for machining fiberglass materials

    Science.gov (United States)

    Winn, L. E. (Inventor)

    1972-01-01

    A lathe tool and holder combination for machining resin impregnated fiberglass cloth laminates is described. The tool holder and tool bit combination is designed to accommodate a conventional carbide-tipped, round shank router bit as the cutting medium, and provides an infinite number of cutting angles in order to produce a true and smooth surface in the fiberglass material workpiece with every pass of the tool bit. The technique utilizes damaged router bits which ordinarily would be discarded.

  17. [Intelligent systems tools in the diagnosis of acute coronary syndromes: A systemic review].

    Science.gov (United States)

    Sprockel, John; Tejeda, Miguel; Yate, José; Diaztagle, Juan; González, Enrique

    2017-03-27

    Acute myocardial infarction is the leading cause of non-communicable deaths worldwide. Its diagnosis is a highly complex task, for which modelling through automated methods has been attempted. A systematic review of the literature was performed on diagnostic tests that applied intelligent systems tools in the diagnosis of acute coronary syndromes. A systematic review of the literature is presented using Medline, Embase, Scopus, IEEE/IET Electronic Library, ISI Web of Science, Latindex and LILACS databases for articles that include the diagnostic evaluation of acute coronary syndromes using intelligent systems. The review process was conducted independently by 2 reviewers, and discrepancies were resolved through the participation of a third person. The operational characteristics of the studied tools were extracted. A total of 35 references met the inclusion criteria. In 22 (62.8%) cases, neural networks were used. In five studies, the performances of several intelligent systems tools were compared. Thirteen studies sought to perform diagnoses of all acute coronary syndromes, and in 22, only infarctions were studied. In 21 cases, clinical and electrocardiographic aspects were used as input data, and in 10, only electrocardiographic data were used. Most intelligent systems use the clinical context as a reference standard. High rates of diagnostic accuracy were found with better performance using neural networks and support vector machines, compared with statistical tools of pattern recognition and decision trees. Extensive evidence was found that shows that using intelligent systems tools achieves a greater degree of accuracy than some clinical algorithms or scales and, thus, should be considered appropriate tools for supporting diagnostic decisions of acute coronary syndromes. Copyright © 2017 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

  18. A survey of open source tools for business intelligence

    DEFF Research Database (Denmark)

    Thomsen, Christian; Pedersen, Torben Bach

    2005-01-01

    The industrial use of open source Business Intelligence (BI) tools is not yet common. It is therefore of interest to explore which possibilities are available for open source BI and compare the tools. In this survey paper, we consider the capabilities of a number of open source tools for BI....... In the paper, we consider three Extract-Transform-Load (ETL) tools, three On-Line Analytical Processing (OLAP) servers, two OLAP clients, and four database management systems (DBMSs). Further, we describe the licenses that the products are released under. It is argued that the ETL tools are still not very...

  19. SIMULATION TOOLS FOR ELECTRICAL MACHINES MODELLING ...

    African Journals Online (AJOL)

    Dr Obe

    ABSTRACT. Simulation tools are used both for research and teaching to allow a good ... The solution provide an easy way of determining the dynamic .... incorporate an in-built numerical algorithm, ... to learn, versatile in application, enhanced.

  20. Process Damping and Cutting Tool Geometry in Machining

    Science.gov (United States)

    Taylor, C. M.; Sims, N. D.; Turner, S.

    2011-12-01

    Regenerative vibration, or chatter, limits the performance of machining processes. Consequences of chatter include tool wear and poor machined surface finish. Process damping by tool-workpiece contact can reduce chatter effects and improve productivity. Process damping occurs when the flank (also known as the relief face) of the cutting tool makes contact with waves on the workpiece surface, created by chatter motion. Tool edge features can act to increase the damping effect. This paper examines how a tool's edge condition combines with the relief angle to affect process damping. An analytical model of cutting with chatter leads to a two-section curve describing how process damped vibration amplitude changes with surface speed for radiussed tools. The tool edge dominates the process damping effect at the lowest surface speeds, with the flank dominating at higher speeds. A similar curve is then proposed regarding tools with worn edges. Experimental data supports the notion of the two-section curve. A rule of thumb is proposed which could be useful to machine operators, regarding tool wear and process damping. The question is addressed, should a tool of a given geometry, used for a given application, be considered as sharp, radiussed or worn regarding process damping.

  1. Process Damping and Cutting Tool Geometry in Machining

    International Nuclear Information System (INIS)

    Taylor, C M; Sims, N D; Turner, S

    2011-01-01

    Regenerative vibration, or chatter, limits the performance of machining processes. Consequences of chatter include tool wear and poor machined surface finish. Process damping by tool-workpiece contact can reduce chatter effects and improve productivity. Process damping occurs when the flank (also known as the relief face) of the cutting tool makes contact with waves on the workpiece surface, created by chatter motion. Tool edge features can act to increase the damping effect. This paper examines how a tool's edge condition combines with the relief angle to affect process damping. An analytical model of cutting with chatter leads to a two-section curve describing how process damped vibration amplitude changes with surface speed for radiussed tools. The tool edge dominates the process damping effect at the lowest surface speeds, with the flank dominating at higher speeds. A similar curve is then proposed regarding tools with worn edges. Experimental data supports the notion of the two-section curve. A rule of thumb is proposed which could be useful to machine operators, regarding tool wear and process damping. The question is addressed, should a tool of a given geometry, used for a given application, be considered as sharp, radiussed or worn regarding process damping.

  2. Stagnant zone formation on diamond cutting tools during machining

    International Nuclear Information System (INIS)

    Izman, S.; Tamin, M.N.; Mon, T.T.; Venkatesh, V.C.; Shaharoun, A.M.

    2007-01-01

    Formation of an intact region on the rake face of cutting tool during machining is quite common phenomenon but its significance in maintaining tool edge sharpness has not been recognized by many researchers. This region is sometimes called stagnant zone. It is believed that when an intact zone present on the rake face, it delays the crater wear progress and hence maintaining the tool edge sharpness longer. This paper investigates the effect of edge radius, surface roughness of the rake face and cutting parameters on the formation of stagnant zone on two different type of diamond tools i.e. polycrystalline diamond PCD-KD100 and diamond-coated inserts when machining titanium alloy. The used inserta and post-processed chips were examined under FESEM and optical microscope after cutting at three different conditions. Experimental results show that the speed and feel, the tool edge radius, and the tool rake surface roughness significantly affect the stagnant zone formation. (author)

  3. Imagining the thinking machine: technological myths and the rise of Artificial Intelligence

    OpenAIRE

    Natale, Simone; Ballatore, Andrea

    2017-01-01

    This article discusses the role of technological myths in the development of Artificial Intelligence (AI) technologies from 1950s to the early 1970s. It shows how the rise of AI was accompanied by the construction of a powerful cultural myth: the creation of a thinking machine, which would be able to perfectly simulate the cognitive faculties of the human mind. Based on a content analysis of articles on Artificial Intelligence published in two magazines, the Scientific American and the New Sc...

  4. Design of intelligent proximity detection zones to prevent striking and pinning fatalities around continuous mining machines.

    Science.gov (United States)

    Bissert, P T; Carr, J L; DuCarme, J P; Smith, A K

    2016-01-01

    The continuous mining machine is a key piece of equipment used in underground coal mining operations. Over the past several decades these machines have been involved in a number of mine worker fatalities. Proximity detection systems have been developed to avert hazards associated with operating continuous mining machines. Incorporating intelligent design into proximity detection systems allows workers greater freedom to position themselves to see visual cues or avoid other hazards such as haulage equipment or unsupported roof or ribs. However, intelligent systems must be as safe as conventional proximity detection systems. An evaluation of the 39 fatal accidents for which the Mine Safety and Health Administration has published fatality investigation reports was conducted to determine whether the accident may have been prevented by conventional or intelligent proximity. Multiple zone configurations for the intelligent systems were studied to determine how system performance might be affected by the zone configuration. Researchers found that 32 of the 39 fatalities, or 82 percent, may have been prevented by both conventional and intelligent proximity systems. These results indicate that, by properly configuring the zones of an intelligent proximity detection system, equivalent protection to a conventional system is possible.

  5. IT-tool Concept for Design and Intelligent Motion Control

    DEFF Research Database (Denmark)

    Conrad, Finn; Hansen, Poul Erik; Sørensen, Torben

    2000-01-01

    The paper presents results obtained from a Danish mechatronic research program focusing on intelligent motion control as well as results from the Esprit project SWING on IT-tools for rapid prototyping of fluid power components and systems. A mechatronic test facility with digital controllers for ....... Furthermore, a developed IT-tool concept for controller and system design utilising the ISO 10303 STEP Standard is proposed....

  6. High Accuracy Nonlinear Control and Estimation for Machine Tool Systems

    DEFF Research Database (Denmark)

    Papageorgiou, Dimitrios

    Component mass production has been the backbone of industry since the second industrial revolution, and machine tools are producing parts of widely varying size and design complexity. The ever-increasing level of automation in modern manufacturing processes necessitates the use of more...... sophisticated machine tool systems that are adaptable to different workspace conditions, while at the same time being able to maintain very narrow workpiece tolerances. The main topic of this thesis is to suggest control methods that can maintain required manufacturing tolerances, despite moderate wear and tear....... The purpose is to ensure that full accuracy is maintained between service intervals and to advice when overhaul is needed. The thesis argues that quality of manufactured components is directly related to the positioning accuracy of the machine tool axes, and it shows which low level control architectures...

  7. Tool management in manufacturing systems equipped with CNC machines

    Directory of Open Access Journals (Sweden)

    Giovanni Tani

    1997-12-01

    Full Text Available This work has been carried out for the purpose of realizing an automated system for the integrated management of tools within a company. By integrating planning, inspection and tool-room functions, automated tool management can ensure optimum utilization of tools on the selected machines, guaranteeing their effective availability. The first stage of the work consisted of defining and developing a Tool Management System whose central nucleus is a unified Data Base for all of the tools, forming part of the company's Technological Files (files on machines, materials, equipment, methods, etc., interfaceable with all of the company departments that require information on tools. The system assigns code numbers to the individual components of the tools and file them on the basis of their morphological and functional characteristics. The system is also designed to effect assemblies of tools, from which are obtained the "Tool Cards" required for compiling working cycles (CAPP, for CAM programming and for the Tool-room where the tools are physically prepared. Methods for interfacing with suitable systems for the aforesaid functions have also been devised

  8. Technique for Increasing Accuracy of Positioning System of Machine Tools

    Directory of Open Access Journals (Sweden)

    Sh. Ji

    2014-01-01

    Full Text Available The aim of research is to improve the accuracy of positioning and processing system using a technique for optimization of pressure diagrams of guides in machine tools. The machining quality is directly related to its accuracy, which characterizes an impact degree of various errors of machines. The accuracy of the positioning system is one of the most significant machining characteristics, which allow accuracy evaluation of processed parts.The literature describes that the working area of the machine layout is rather informative to characterize the effect of the positioning system on the macro-geometry of the part surfaces to be processed. To enhance the static accuracy of the studied machine, in principle, two groups of measures are possible. One of them points toward a decrease of the cutting force component, which overturns the slider moments. Another group of measures is related to the changing sizes of the guide facets, which may lead to their profile change.The study was based on mathematical modeling and optimization of the cutting zone coordinates. And we find the formula to determine the surface pressure of the guides. The selected parameters of optimization are vectors of the cutting force and values of slides and guides. Obtained results show that a technique for optimization of coordinates in the cutting zone was necessary to increase a processing accuracy.The research has established that to define the optimal coordinates of the cutting zone we have to change the sizes of slides, value and coordinates of applied forces, reaching the pressure equalization and improving the accuracy of positioning system of machine tools. In different points of the workspace a vector of forces is applied, pressure diagrams are found, which take into account the changes in the parameters of positioning system, and the pressure diagram equalization to provide the most accuracy of machine tools is achieved.

  9. A defect-driven diagnostic method for machine tool spindles.

    Science.gov (United States)

    Vogl, Gregory W; Donmez, M Alkan

    2015-01-01

    Simple vibration-based metrics are, in many cases, insufficient to diagnose machine tool spindle condition. These metrics couple defect-based motion with spindle dynamics; diagnostics should be defect-driven. A new method and spindle condition estimation device (SCED) were developed to acquire data and to separate system dynamics from defect geometry. Based on this method, a spindle condition metric relying only on defect geometry is proposed. Application of the SCED on various milling and turning spindles shows that the new approach is robust for diagnosing the machine tool spindle condition.

  10. Intelligent Vehicle Power Management Using Machine Learning and Fuzzy Logic

    National Research Council Canada - National Science Library

    Chen, ZhiHang; Masrur, M. A; Murphey, Yi L

    2008-01-01

    .... A machine learning algorithm, LOPPS, has been developed to learn about optimal power source combinations with respect to minimum power loss for all possible load requests and various system power states...

  11. High speed dry machining of MMCs with diamond tools

    International Nuclear Information System (INIS)

    Collins, J.L.

    2001-01-01

    The increasing use of metal matrix composites (MMCs) has raised new issues in their machining. Industrial demands for higher speed and dry machining of MMCs with improved component production to closer tolerances have driven the development of new tool materials. In particular, the wear characteristics of synthetic diamond tooling satisfy many of the requirements imposed in cutting these highly abrasive workpieces. The use of diamond tool materials, such as polycrystalline diamond (PCD), has resulted in tool life improvements which, allied with environmental considerations, show great potential for the development of dry cutting. This paper explores the wear characteristics of PCD, which is highly suited to the dry machining of particulate silicon carbide MMCs. Also, two further diamond tool materials are evaluated - chemical vapor deposition (CVD) thick layer diamond and synthetic single crystal diamond. Their suitability for the efficient machining of high volume fraction MMC materials is shown and their potential impact an the subsequent acceptance and integration of MMCs into engineering components is discussed. (author)

  12. Modelling of Tool Wear and Residual Stress during Machining of AISI H13 Tool Steel

    Science.gov (United States)

    Outeiro, José C.; Umbrello, Domenico; Pina, José C.; Rizzuti, Stefania

    2007-05-01

    Residual stresses can enhance or impair the ability of a component to withstand loading conditions in service (fatigue, creep, stress corrosion cracking, etc.), depending on their nature: compressive or tensile, respectively. This poses enormous problems in structural assembly as this affects the structural integrity of the whole part. In addition, tool wear issues are of critical importance in manufacturing since these affect component quality, tool life and machining cost. Therefore, prediction and control of both tool wear and the residual stresses in machining are absolutely necessary. In this work, a two-dimensional Finite Element model using an implicit Lagrangian formulation with an automatic remeshing was applied to simulate the orthogonal cutting process of AISI H13 tool steel. To validate such model the predicted and experimentally measured chip geometry, cutting forces, temperatures, tool wear and residual stresses on the machined affected layers were compared. The proposed FE model allowed us to investigate the influence of tool geometry, cutting regime parameters and tool wear on residual stress distribution in the machined surface and subsurface of AISI H13 tool steel. The obtained results permit to conclude that in order to reduce the magnitude of surface residual stresses, the cutting speed should be increased, the uncut chip thickness (or feed) should be reduced and machining with honed tools having large cutting edge radii produce better results than chamfered tools. Moreover, increasing tool wear increases the magnitude of surface residual stresses.

  13. Program Design Report of the CNC Machine Tool(V-1)

    International Nuclear Information System (INIS)

    Youm, Ki Un; Moon, J. S.; Lee, I. B.; Youn, J. H.

    2010-08-01

    The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology

  14. Artificial intelligence - New tools for aerospace project managers

    Science.gov (United States)

    Moja, D. C.

    1985-01-01

    Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

  15. Intelligent Tools for Building a Scientific Information Platform

    CERN Document Server

    Skonieczny, Lukasz; Rybiński, Henryk; Niezgodka, Marek

    2012-01-01

    This book is a selection of results obtained within one year of research performed under SYNAT - a nation-wide scientific project aiming to create an infrastructure for scientific content storage and sharing for academia, education and open knowledge society in Poland. The selection refers to the research in artificial intelligence, knowledge discovery and data mining, information retrieval and natural language processing, addressing the problems of implementing intelligent tools for building a scientific information platform. The idea of this book is based on the very successful SYNAT Project Conference and the SYNAT Workshop accompanying the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS 2011). The papers included in this book present an overview and insight into such topics as architecture of scientific information platforms, semantic clustering, ontology-based systems, as well as, multimedia data processing.

  16. The Total Energy Efficiency Index for machine tools

    International Nuclear Information System (INIS)

    Schudeleit, Timo; Züst, Simon; Weiss, Lukas; Wegener, Konrad

    2016-01-01

    Energy efficiency in industries is one of the dominating challenges of the 21st century. Since the release of the eco-design directive 2005/32/EC in 2005, great research effort has been spent on the energy efficiency assessment for energy using products. The ISO (International Organization for Standardization) standardization body (ISO/TC 39 WG 12) currently works on the ISO 14955 series in order to enable the assessment of energy efficient design of machine tools. A missing piece for completion of the ISO 14955 series is a metric to quantify the design of machine tools regarding energy efficiency based on the respective assembly of components. The metric needs to take into account each machine tool components' efficiency and the need-oriented utilization in combination with the other components while referring to efficiency limits. However, a state of the art review reveals that none of the existing metrics is feasible to adequately match this goal. This paper presents a metric that matches all these criteria to promote the development of the ISO 14955 series. The applicability of the metric is proven in a practical case study on a turning machine. - Highlights: • Study for pushing forward the standardization work on the ISO 14955 series. • Review of existing energy efficiency indicators regarding three basic strategies to foster sustainability. • Development of a metric comprising the three basic strategies to foster sustainability. • Metric application for quantifying the energy efficiency of a turning machine.

  17. Laser formed intentional firearm microstamping technology: counterinsurgency intelligence gathering tool

    Science.gov (United States)

    Lizotte, Todd E.; Ohar, Orest P.

    2009-09-01

    Warfare relies on effective, accurate and timely intelligence an especially critical task when conducting a counterinsurgency operation [1]. Simply stated counterinsurgency is an intelligence war. Both insurgents and counterinsurgents need effective intelligence capabilities to be successful. Insurgents and counterinsurgents therefore attempt to create and maintain intelligence networks and fight continuously to neutralize each other's intelligence capabilities [1][2]. In such an environment it is obviously an advantage to target or proactively create opportunities to track and map an insurgent movement. Quickly identifying insurgency intelligence assets (Infiltrators) within a host government's infrastructure is the goal. Infiltrators can occupy various areas of government such as security personnel, national police force, government offices or military units. Intentional Firearm Microstamping offers such opportunities when implemented into firearms. Outfitted within firearms purchased and distributed to the host nation's security forces (civilian and military), Intentional Firearm Microstamping (IFM) marks bullet cartridge casings with codes as they are fired from the firearm. IFM is incorporated onto optimum surfaces with the firearm mechanism. The intentional microstamp tooling marks can take the form of alphanumeric codes or encoded geometric codes that identify the firearm. As the firearm is discharged the intentional tooling marks transfer a code to the cartridge casing which is ejected out of the firearm. When recovered at the scene of a firefight or engagement, the technology will provide forensic intelligence allowing the mapping and tracking of small arms traffic patterns within the host nation or identify insurgency force strength and pinpoint firearm sources, such as corrupt/rogue military units or police force. Intentional Firearm Microstamping is a passive mechanical trace technology that can be outfitted or retrofitted to semiautomatic handguns and

  18. Effect of the Cutting Tool Geometry on the Tool Wear Resistance When Machining Inconel 625

    Directory of Open Access Journals (Sweden)

    Tomáš Zlámal

    2017-12-01

    Full Text Available The paper deals with the design of a suitable cutting geometry of a tool for the machining of the Inconel 625 nickel alloy. This alloy is among the hard-to-machine refractory alloys that cause very rapid wear on cutting tools. Therefore, SNMG and RCMT indexable cutting insert were used to machine the alloy. The selected insert geometry should prevent notch wear and extend tool life. The alloy was machined under predetermined cutting conditions. The angle of the main edge and thus the size and nature of the wear changed with the depth of the material layer being cut. The criterion for determining a more suitable cutting geometry was the tool’s durability and the roughness of the machined surface.

  19. Effect of the Cutting Tool Geometry on the Tool Wear Resistance when Machining Inconel 625

    Directory of Open Access Journals (Sweden)

    Tomáš Zlámal

    2018-03-01

    Full Text Available The paper deals with the design of a suitable cutting geometry of a tool for the machining of the Inconel 625 nickel alloy. This alloy is among the hard-to-machine refractory alloys that cause very rapid wear on cutting tools. Therefore, SNMG and RCMT indexable cutting insert were used to machine the alloy. The selected insert geometry should prevent notch wear and extend tool life. The alloy was machined under predetermined cutting conditions. The angle of the main edge and thus the size and nature of the wear changed with the depth of the material layer being cut. The criterion for determining a more suitable cutting geometry was the tool’s durability and the roughness of the machined surface.

  20. A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

    Science.gov (United States)

    Becker, Lee A.

    1987-01-01

    Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

  1. Social collective intelligence: combining the powers of humans and machines to build a smarter society

    NARCIS (Netherlands)

    Miorandi, Daniele; Maltese, Vincenzo; Rovatsos, Michael; Nijholt, Antinus; Stewart, James

    2014-01-01

    The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and

  2. An intelligent man-machine system for future nuclear power plants

    International Nuclear Information System (INIS)

    Takizawa, Yoji; Hattori, Yoshiaki; Itoh, Juichiro; Fukumoto, Akira

    1994-01-01

    The objective of the development of an intelligent man-machine system for future nuclear power plants is enhancement of operational reliability by applying recent advances in cognitive science, artificial intelligence, and computer technologies. To realize this objective, the intelligent man-machine system, aiming to support a knowledge-based decision making process in an operator's supervisory plant control tasks, consists of three main functions, i.e., a cognitive model-based advisor, a robust automatic sequence controller, and an ecological interface. These three functions have been integrated into a console-type nuclear power plant monitoring and control system as a validation test bed. The validation tests in which experienced operator crews participated were carried out in 1991 and 1992. The test results show the usefulness of the support functions and the validity of the system design approach

  3. A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    Grover Zurita

    2016-09-01

    Full Text Available In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bearings, and any method in order to improve the effectiveness, reliability, and accuracy of the bearing faults diagnosis ought to be evaluated. In order to perform machine diagnosis efficiently, researchers have extensively investigated different advanced digital signal processing techniques and artificial intelligence methods to accurately extract fault characteristics from vibration signals. The main goal of this article is to present the state-of-the-art development in vibration analysis for machine diagnosis based on artificial intelligence methods.

  4. From curve fitting to machine learning an illustrative guide to scientific data analysis and computational intelligence

    CERN Document Server

    Zielesny, Achim

    2016-01-01

    This successful book provides in its second edition an interactive and illustrative guide from two-dimensional curve fitting to multidimensional clustering and machine learning with neural networks or support vector machines. Along the way topics like mathematical optimization or evolutionary algorithms are touched. All concepts and ideas are outlined in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics. The major topics are extensively outlined with exploratory examples and applications. The primary goal is to be as illustrative as possible without hiding problems and pitfalls but to address them. The character of an illustrative cookbook is complemented with specific sections that address more fundamental questions like the relation between machine learning and human intelligence. All topics are completely demonstrated with the computing platform Mathematica and the Computational Intelligence Packages (CIP), a high-level function library developed with M...

  5. How artificial intelligence can help [man-machine interface

    International Nuclear Information System (INIS)

    Elm, W.C.

    1988-01-01

    The operator is ultimately responsible for the safe and economical operation of the plant, and must evaluate the accuracy of any system-recommended action or other output. Decision support systems offer a means to improve the man-machine interface by explicitly supporting operator problem solving, rather than complicating decision-making by the need to request an explanation of the rationale behind an expert system's advice during a high stress situation. (author)

  6. Using generic tool kits to build intelligent systems

    Science.gov (United States)

    Miller, David J.

    1994-01-01

    The Intelligent Systems and Robots Center at Sandia National Laboratories is developing technologies for the automation of processes associated with environmental remediation and information-driven manufacturing. These technologies, which focus on automated planning and programming and sensor-based and model-based control, are used to build intelligent systems which are able to generate plans of action, program the necessary devices, and use sensors to react to changes in the environment. By automating tasks through the use of programmable devices tied to computer models which are augmented by sensing, requirements for faster, safer, and cheaper systems are being satisfied. However, because of the need for rapid cost-effect prototyping and multi-laboratory teaming, it is also necessary to define a consistent approach to the construction of controllers for such systems. As a result, the Generic Intelligent System Controller (GISC) concept has been developed. This concept promotes the philosophy of producing generic tool kits which can be used and reused to build intelligent control systems.

  7. Visualization tool for human-machine interface designers

    Science.gov (United States)

    Prevost, Michael P.; Banda, Carolyn P.

    1991-06-01

    As modern human-machine systems continue to grow in capabilities and complexity, system operators are faced with integrating and managing increased quantities of information. Since many information components are highly related to each other, optimizing the spatial and temporal aspects of presenting information to the operator has become a formidable task for the human-machine interface (HMI) designer. The authors describe a tool in an early stage of development, the Information Source Layout Editor (ISLE). This tool is to be used for information presentation design and analysis; it uses human factors guidelines to assist the HMI designer in the spatial layout of the information required by machine operators to perform their tasks effectively. These human factors guidelines address such areas as the functional and physical relatedness of information sources. By representing these relationships with metaphors such as spring tension, attractors, and repellers, the tool can help designers visualize the complex constraint space and interacting effects of moving displays to various alternate locations. The tool contains techniques for visualizing the relative 'goodness' of a configuration, as well as mechanisms such as optimization vectors to provide guidance toward a more optimal design. Also available is a rule-based design checker to determine compliance with selected human factors guidelines.

  8. Business intelligence tools for radiology: creating a prototype model using open-source tools.

    Science.gov (United States)

    Prevedello, Luciano M; Andriole, Katherine P; Hanson, Richard; Kelly, Pauline; Khorasani, Ramin

    2010-04-01

    Digital radiology departments could benefit from the ability to integrate and visualize data (e.g. information reflecting complex workflow states) from all of their imaging and information management systems in one composite presentation view. Leveraging data warehousing tools developed in the business world may be one way to achieve this capability. In total, the concept of managing the information available in this data repository is known as Business Intelligence or BI. This paper describes the concepts used in Business Intelligence, their importance to modern Radiology, and the steps used in the creation of a prototype model of a data warehouse for BI using open-source tools.

  9. Social collective intelligence combining the powers of humans and machines to build a smarter society

    CERN Document Server

    Miorandi, Daniele; Rovatsos, Michael

    2014-01-01

    The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and storage capabilities of advanced ICT.Social Collective Intelligence opens a number of challenges for researchers in both computer science and social sciences; at the same time it provides an innovative approach to solve challenges in diverse application domains, ranging from health to education

  10. Integrating human and machine intelligence in galaxy morphology classification tasks

    Science.gov (United States)

    Beck, Melanie R.; Scarlata, Claudia; Fortson, Lucy F.; Lintott, Chris J.; Simmons, B. D.; Galloway, Melanie A.; Willett, Kyle W.; Dickinson, Hugh; Masters, Karen L.; Marshall, Philip J.; Wright, Darryl

    2018-06-01

    Quantifying galaxy morphology is a challenging yet scientifically rewarding task. As the scale of data continues to increase with upcoming surveys, traditional classification methods will struggle to handle the load. We present a solution through an integration of visual and automated classifications, preserving the best features of both human and machine. We demonstrate the effectiveness of such a system through a re-analysis of visual galaxy morphology classifications collected during the Galaxy Zoo 2 (GZ2) project. We reprocess the top-level question of the GZ2 decision tree with a Bayesian classification aggregation algorithm dubbed SWAP, originally developed for the Space Warps gravitational lens project. Through a simple binary classification scheme, we increase the classification rate nearly 5-fold classifying 226 124 galaxies in 92 d of GZ2 project time while reproducing labels derived from GZ2 classification data with 95.7 per cent accuracy. We next combine this with a Random Forest machine learning algorithm that learns on a suite of non-parametric morphology indicators widely used for automated morphologies. We develop a decision engine that delegates tasks between human and machine and demonstrate that the combined system provides at least a factor of 8 increase in the classification rate, classifying 210 803 galaxies in just 32 d of GZ2 project time with 93.1 per cent accuracy. As the Random Forest algorithm requires a minimal amount of computational cost, this result has important implications for galaxy morphology identification tasks in the era of Euclid and other large-scale surveys.

  11. The internet and intelligent machines: search engines, agents and robots

    International Nuclear Information System (INIS)

    Achenbach, S.; Alfke, H.

    2000-01-01

    The internet plays an important role in a growing number of medical applications. Finding relevant information is not always easy as the amount of available information on the Web is rising quickly. Even the best Search Engines can only collect links to a fraction of all existing Web pages. In addition, many of these indexed documents have been changed or deleted. The vast majority of information on the Web is not searchable with conventional methods. New search strategies, technologies and standards are combined in Intelligent Search Agents (ISA) an Robots, which can retrieve desired information in a specific approach. Conclusion: The article describes differences between ISAs and conventional Search Engines and how communication between Agents improves their ability to find information. Examples of existing ISAs are given and the possible influences on the current and future work in radiology is discussed. (orig.) [de

  12. BUSINESS INTELLIGENCE TOOLS FOR DATA ANALYSIS AND DECISION MAKING

    Directory of Open Access Journals (Sweden)

    DEJAN ZDRAVESKI

    2011-04-01

    Full Text Available Every business is dynamic in nature and is affected by various external and internal factors. These factors include external market conditions, competitors, internal restructuring and re-alignment, operational optimization and paradigm shifts in the business itself. New regulations and restrictions, in combination with the above factors, contribute to the constant evolutionary nature of compelling, business-critical information; the kind of information that an organization needs to sustain and thrive. Business intelligence (“BI” is broad term that encapsulates the process of gathering information pertaining to a business and the market it functions in. This information when collated and analyzed in the right manner, can provide vital insights into the business and can be a tool to improve efficiency, reduce costs, reduce time lags and bring many positive changes. A business intelligence application helps to achieve precisely that. Successful organizations maximize the use of their data assets through business intelligence technology. The first data warehousing and decision support tools introduced companies to the power and benefits of accessing and analyzing their corporate data. Business users at every level found new, more sophisticated ways to analyze and report on the information mined from their vast data warehouses.Choosing a Business Intelligence offering is an important decision for an enterprise, one that will have a significant impact throughout the enterprise. The choice of a BI offering will affect people up and down the chain of command (senior management, analysts, and line managers and across functional areas (sales, finance, and operations. It will affect business users, application developers, and IT professionals. BI applications include the activities of decision support systems (DSS, query and reporting, online analyticalprocessing (OLAP, statistical analysis, forecasting, and data mining. Another way of phrasing this is

  13. Prediction Of Abrasive And Diffusive Tool Wear Mechanisms In Machining

    Science.gov (United States)

    Rizzuti, S.; Umbrello, D.

    2011-01-01

    Tool wear prediction is regarded as very important task in order to maximize tool performance, minimize cutting costs and improve the quality of workpiece in cutting. In this research work, an experimental campaign was carried out at the varying of cutting conditions with the aim to measure both crater and flank tool wear, during machining of an AISI 1045 with an uncoated carbide tool P40. Parallel a FEM-based analysis was developed in order to study the tool wear mechanisms, taking also into account the influence of the cutting conditions and the temperature reached on the tool surfaces. The results show that, when the temperature of the tool rake surface is lower than the activation temperature of the diffusive phenomenon, the wear rate can be estimated applying an abrasive model. In contrast, in the tool area where the temperature is higher than the diffusive activation temperature, the wear rate can be evaluated applying a diffusive model. Finally, for a temperature ranges within the above cited values an adopted abrasive-diffusive wear model furnished the possibility to correctly evaluate the tool wear phenomena.

  14. An intelligent human-machine system based on an ecological interface design concept

    International Nuclear Information System (INIS)

    Naito, N.

    1995-01-01

    It seems both necessary and promising to develop an intelligent human-machine system, considering the objective of the human-machine system and the recent advance in cognitive engineering and artificial intelligence together with the ever-increasing importance of human factor issues in nuclear power plant operation and maintenance. It should support human operators in their knowledge-based behaviour and allow them to cope with unanticipated abnormal events, including recovery from erroneous human actions. A top-down design approach has been adopted based on cognitive work analysis, and (1) an ecological interface, (2) a cognitive model-based advisor and (3) a robust automatic sequence controller have been established. These functions have been integrated into an experimental control room. A validation test was carried out by the participation of experienced operators and engineers. The results showed the usefulness of this system in supporting the operator's supervisory plant control tasks. ((orig.))

  15. A Survey of Open Source Tools for Business Intelligence

    DEFF Research Database (Denmark)

    Thomsen, Christian; Pedersen, Torben Bach

    The industrial use of open source Business Intelligence (BI) tools is becoming more common, but is still not as widespread as for other types of software.  It is therefore of interest to explore which possibilities are available for open source BI and compare the tools. In this survey paper, we c......The industrial use of open source Business Intelligence (BI) tools is becoming more common, but is still not as widespread as for other types of software.  It is therefore of interest to explore which possibilities...... are available for open source BI and compare the tools. In this survey paper, we consider the capabilities of a number of open source tools for BI. In the paper, we consider a number of Extract‐Transform‐Load (ETL) tools, database management systems (DBMSs), On‐Line Analytical Processing (OLAP) servers, and OLAP clients. We find that, unlike the situation a few years ago, there now...

  16. Space applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 2: Space projects overview

    Science.gov (United States)

    Miller, R. H.; Minsky, M. L.; Smith, D. B. S.

    1982-01-01

    Applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities, and their related ground support functions are studied so that informed decisions can be made on which aspects of ARAMIS to develop. The space project breakdowns, which are used to identify tasks ('functional elements'), are described. The study method concentrates on the production of a matrix relating space project tasks to pieces of ARAMIS.

  17. Intelligent Machine Vision for Automated Fence Intruder Detection Using Self-organizing Map

    OpenAIRE

    Veldin A. Talorete Jr.; Sherwin A Guirnaldo

    2017-01-01

    This paper presents an intelligent machine vision for automated fence intruder detection. A series of still captured images that contain fence events using Internet Protocol cameras was used as input data to the system. Two classifiers were used; the first is to classify human posture and the second one will classify intruder location. The system classifiers were implemented using Self-Organizing Map after the implementation of several image segmentation processes. The human posture classifie...

  18. Integrating Human and Machine Intelligence in Galaxy Morphology Classification Tasks

    Science.gov (United States)

    Beck, Melanie Renee

    thus solved both the visual classification problem of time efficiency and improved accuracy by producing a distribution of independent classifications for each galaxy. While crowd-sourced galaxy classifications have proven their worth, challenges remain before establishing this method as a critical and standard component of the data processing pipelines for the next generation of surveys. In particular, though innovative, crowd-sourcing techniques do not have the capacity to handle the data volume and rates expected in the next generation of surveys. These algorithms will be delegated to handle the majority of the classification tasks, freeing citizen scientists to contribute their efforts on subtler and more complex assignments. This thesis presents a solution through an integration of visual and automated classifications, preserving the best features of both human and machine. We demonstrate the effectiveness of such a system through a re-analysis of visual galaxy morphology classifications collected during the Galaxy Zoo 2 (GZ2) project. We reprocess the top-level question of the GZ2 decision tree with a Bayesian classification aggregation algorithm dubbed SWAP, originally developed for the Space Warps gravitational lens project. Through a simple binary classification scheme we increase the classification rate nearly 5-fold classifying 226,124 galaxies in 92 days of GZ2 project time while reproducing labels derived from GZ2 classification data with 95.7% accuracy. We next combine this with a Random Forest machine learning algorithm that learns on a suite of non-parametric morphology indicators widely used for automated morphologies. We develop a decision engine that delegates tasks between human and machine and demonstrate that the combined system provides a factor of 11.4 increase in the classification rate, classifying 210,803 galaxies in just 32 days of GZ2 project time with 93.1% accuracy. As the Random Forest algorithm requires a minimal amount of computational

  19. System diagnostic builder: a rule-generation tool for expert systems that do intelligent data evaluation

    Science.gov (United States)

    Nieten, Joseph L.; Burke, Roger

    1993-03-01

    The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.

  20. ECO-INTELLIGENT TOOLS – A NECESSITY FOR SUSTAINABLE BUSINESSES

    Directory of Open Access Journals (Sweden)

    S. Nate

    2014-04-01

    Full Text Available Many of the challenges associated with sustainable development can be traced in the way modern society produces and consumes. Production, distribution and supply of goods and services require material and energy consumption, having an impact on natural resources both quantitatively and qualitatively, generating waste, pollution and disrupting ecosystems. Ecobusiness intelligence is the capacity of people, processes and applications / tools to organize business information, to facilitate consistent access to them and analyse them in order to improve management decisions, for better performance management of the organizations that are increasingly pressed to synchronize their processes and services with a sustainable development agenda, through the development, testing and implementation of decision support software. By adopting sustainable practices, eco – intelligent companies can gain added value, increase market share and boost shareholder value. Moreover, the growing demand for "green" products has created new markets and the visionary entrepreneurs already reap the rewards of approaching sustainability. Large and small companies are learning that sustainable business practices not only help the environment but also can improve profitability by pursuing higher efficiency, fewer harmful side-effects, and better relationships with the community and more. Gaining competitive advantage is a core concern of the companies and the existence of systems of identification, extraction and analysis of available data in a company, but also from the external environment, to provide real support for business decisions, is an essential ingredient of success. This paper highlights the necessity of eco-intelligent tools that help determining the organization's strategies, identifying the perceptions and capabilities of the competitors, analyzing the effectiveness of current operations, deploying long-term prospects for environmental action and establishing

  1. Information security system quality assessment through the intelligent tools

    Science.gov (United States)

    Trapeznikov, E. V.

    2018-04-01

    The technology development has shown the automated system information security comprehensive analysis necessity. The subject area analysis indicates the study relevance. The research objective is to develop the information security system quality assessment methodology based on the intelligent tools. The basis of the methodology is the information security assessment model in the information system through the neural network. The paper presents the security assessment model, its algorithm. The methodology practical implementation results in the form of the software flow diagram are represented. The practical significance of the model being developed is noted in conclusions.

  2. The SP Theory of Intelligence as a Foundation for the Development of a General, Human-Level Thinking Machine

    OpenAIRE

    Wolff, J Gerard

    2016-01-01

    This paper summarises how the "SP theory of intelligence" and its realisation in the "SP computer model" simplifies and integrates concepts across artificial intelligence and related areas, and thus provides a promising foundation for the development of a general, human-level thinking machine, in accordance with the main goal of research in artificial general intelligence. The key to this simplification and integration is the powerful concept of "multiple alignment", borrowed and adapted from...

  3. Soft computing in machine learning

    CERN Document Server

    Park, Jooyoung; Inoue, Atsushi

    2014-01-01

    As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train machines to perform some things, so that they can automatically detect, diagnose, and solve a variety of problems. The intelligent systems have made rapid progress in developing the state of the art in machine learning based on smart and deep perception. Using machine learning, the intelligent systems make widely applications in automated speech recognition, natural language processing, medical diagnosis, bioinformatics, and robot locomotion. This book aims at introducing how to treat a substantial amount of data, to teach machines and to improve decision making models. And this book specializes in the developments of advanced intelligent systems through machine learning. It...

  4. Automatic welding detection by an intelligent tool pipe inspection

    Science.gov (United States)

    Arizmendi, C. J.; Garcia, W. L.; Quintero, M. A.

    2015-07-01

    This work provide a model based on machine learning techniques in welds recognition, based on signals obtained through in-line inspection tool called “smart pig” in Oil and Gas pipelines. The model uses a signal noise reduction phase by means of pre-processing algorithms and attribute-selection techniques. The noise reduction techniques were selected after a literature review and testing with survey data. Subsequently, the model was trained using recognition and classification algorithms, specifically artificial neural networks and support vector machines. Finally, the trained model was validated with different data sets and the performance was measured with cross validation and ROC analysis. The results show that is possible to identify welding automatically with an efficiency between 90 and 98 percent.

  5. Method and apparatus for characterizing and enhancing the functional performance of machine tools

    Science.gov (United States)

    Barkman, William E; Babelay, Jr., Edwin F; Smith, Kevin Scott; Assaid, Thomas S; McFarland, Justin T; Tursky, David A; Woody, Bethany; Adams, David

    2013-04-30

    Disclosed are various systems and methods for assessing and improving the capability of a machine tool. The disclosure applies to machine tools having at least one slide configured to move along a motion axis. Various patterns of dynamic excitation commands are employed to drive the one or more slides, typically involving repetitive short distance displacements. A quantification of a measurable merit of machine tool response to the one or more patterns of dynamic excitation commands is typically derived for the machine tool. Examples of measurable merits of machine tool performance include workpiece surface finish, and the ability to generate chips of the desired length.

  6. Support Vector Machines as tools for mortality graduation

    Directory of Open Access Journals (Sweden)

    Alberto Olivares

    2011-01-01

    Full Text Available A topic of interest in demographic and biostatistical analysis as well as in actuarial practice,is the graduation of the age-specific mortality pattern. A classical graduation technique is to fit parametric models. Recently, particular emphasis has been given to graduation using nonparametric techniques. Support Vector Machines (SVM is an innovative methodology that could be utilized for mortality graduation purposes. This paper evaluates SVM techniques as tools for graduating mortality rates. We apply SVM to empirical death rates from a variety of populations and time periods. For comparison, we also apply standard graduation techniques to the same data.

  7. Laser beam machining of polycrystalline diamond for cutting tool manufacturing

    Science.gov (United States)

    Wyszyński, Dominik; Ostrowski, Robert; Zwolak, Marek; Bryk, Witold

    2017-10-01

    The paper concerns application of DPSS Nd: YAG 532nm pulse laser source for machining of polycrystalline WC based diamond inserts (PCD). The goal of the research was to determine optimal laser cutting parameters for cutting tool shaping. Basic criteria to reach the goal was cutting edge quality (minimalization of finishing operations), material removal rate (time and cost efficiency), choice of laser beam characteristics (polarization, power, focused beam diameter). The research was planned and realised and analysed according to design of experiment rules (DOE). The analysis of the cutting edge was prepared with use of Alicona Infinite Focus measurement system.

  8. Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agent’s Location Using Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Cédric Beaulac

    2017-01-01

    Full Text Available We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile agent’s position using the forward algorithm. Second, it uses the Baum–Welch algorithm as a statistical learning tool to gain knowledge of the mobile target. Finally, an experimental environment is proposed, namely, a video game that we use to test our artificial intelligence. We present statistical and graphical results to illustrate the efficiency of our method.

  9. THE CONFORMITY OF MACHINE TOOLS WITH RESPECT TO EUROPEAN SAFETY STANDARDS

    CERN Multimedia

    TIS/TE

    2001-01-01

    European regulations require that all motorized machine tools conform to the latest safety standards by the end of the year 2000. CERN must follow these regulations and has already modified most of its machine tools accordingly. However, there is still a small number of machine tools which have not yet been modified as required. These machines should not be used until they are brought up to the required safety standards, failing which the machines should be discarded. One can recognise which machine tools conform with the latest standards by the indication 'CS' on the identification plate of the machine, see foto below. In cases of doubt about the status of a machine tool you should contact K. Altherr/EST or C. Margaroli/TIS for advice.

  10. THE CONFORMITY OF MACHINE TOOLS WITH RESPECT TO EUROPEAN SAFETY STANDARDS

    CERN Multimedia

    TIS/TE

    2000-01-01

    European regulations require that all motorized machine tools conform to the latest safety standards by the end of the year 2000. CERN must follow these regulations and has already modified most of its machine tools accordingly. However, there is still a small number of machine tools which have not yet been modified as required. These machines should not be used until they are brought up to the required safety standards, failing which the machines should be discarded. One can recognise which machine tools conform with the latest standards by the indication 'CS' on the identification plate of the machine, see foto below. In cases of doubt about the status of a machine tool you should contact K. Altherr/EST or C. Margaroli/TIS for advice.

  11. Process Machine Interactions Predicition and Manipulation of Interactions between Manufacturing Processes and Machine Tool Structures

    CERN Document Server

    Hollmann, Ferdinand

    2013-01-01

    This contributed volume collects the scientific results of the DFG Priority Program 1180 Prediction and Manipulation of Interactions between Structure and Process. The research program has been conducted during the years 2005 and 2012, whereas the primary goal was the analysis of the interactions between processes and structures in modern production facilities. This book presents the findings of the 20 interdisciplinary subprojects, focusing on different manufacturing processes such as high performance milling, tool grinding or metal forming. It contains experimental investigations as well as mathematical modeling of production processes and machine interactions. New experimental advancements and novel simulation approaches are also included.

  12. Intelligent machines in the twenty-first century: foundations of inference and inquiry.

    Science.gov (United States)

    Knuth, Kevin H

    2003-12-15

    The last century saw the application of Boolean algebra to the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines, in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. Recent advances in our understanding of the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we recently identified the algebra of questions as the free distributive algebra, which will now allow us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper, we examine the foundations of inference and inquiry. We begin with a history of inferential reasoning, highlighting key concepts that have led to the automation of inference in modern machine-learning systems. We then discuss the foundations of inference in more detail using a modern viewpoint that relies on the mathematics of partially ordered sets and the scaffolding of lattice theory. This new viewpoint allows us to develop the logic of inquiry and introduce a measure describing the relevance of a proposed question to an unresolved issue. Last, we will demonstrate the automation of inference, and discuss how this new logic of inquiry will enable intelligent machines to ask questions. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them not only to make inferences from data, but also to decide which question to ask, which experiment to perform, or which measurement to take given what they have

  13. Study on intelligent processing system of man-machine interactive garment frame model

    Science.gov (United States)

    Chen, Shuwang; Yin, Xiaowei; Chang, Ruijiang; Pan, Peiyun; Wang, Xuedi; Shi, Shuze; Wei, Zhongqian

    2018-05-01

    A man-machine interactive garment frame model intelligent processing system is studied in this paper. The system consists of several sensor device, voice processing module, mechanical parts and data centralized acquisition devices. The sensor device is used to collect information on the environment changes brought by the body near the clothes frame model, the data collection device is used to collect the information of the environment change induced by the sensor device, voice processing module is used for speech recognition of nonspecific person to achieve human-machine interaction, mechanical moving parts are used to make corresponding mechanical responses to the information processed by data collection device.it is connected with data acquisition device by a means of one-way connection. There is a one-way connection between sensor device and data collection device, two-way connection between data acquisition device and voice processing module. The data collection device is one-way connection with mechanical movement parts. The intelligent processing system can judge whether it needs to interact with the customer, realize the man-machine interaction instead of the current rigid frame model.

  14. Application of a 16-bit microprocessor to the digital control of machine tools

    International Nuclear Information System (INIS)

    Issaly, Alain

    1979-01-01

    After an overview of machine tools (various types, definition standardization, associated technologies for motors and position sensors), this research thesis describes the principles of computer-based digital control: classification of machine tool command systems, machining programming, programming languages, dialog function, interpolation function, servo-control function, tool compensation function. The author reports the application of a 16-bit microprocessor to the computer-based digital control of a machine tool: feasibility, selection of microprocessor, hardware presentation, software development and description, machining mode, translation-loading mode

  15. Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

    Energy Technology Data Exchange (ETDEWEB)

    Jha, Sumit Kumar [University of Central Florida, Orlando; Pullum, Laura L [ORNL; Ramanathan, Arvind [ORNL

    2016-01-01

    Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.

  16. Mechatronic System Design and Intelligent Motion Control of Hydraulic Robots and Machines

    DEFF Research Database (Denmark)

    Conrad, Finn; Sørensen, Torben

    2003-01-01

    The paper presents an approach and concept to mechatronic system design and intelligent motion control. The Information Technology (IT) offers software and hardware for improvement of R&D Mechatronic Teams to create products and solutions for industrial applications. The latest progress in IT makes...... integration of an overall design and manufacturing IT- concept feasible and commercially attractive. An IT-tool concept for modelling, simulation and design of mechatronic products and systems is proposed in this paper. It built on results from a Danish mechatronic research program on intelligent motion...

  17. Prediction of biochar yield from cattle manure pyrolysis via least squares support vector machine intelligent approach.

    Science.gov (United States)

    Cao, Hongliang; Xin, Ya; Yuan, Qiaoxia

    2016-02-01

    To predict conveniently the biochar yield from cattle manure pyrolysis, intelligent modeling approach was introduced in this research. A traditional artificial neural networks (ANN) model and a novel least squares support vector machine (LS-SVM) model were developed. For the identification and prediction evaluation of the models, a data set with 33 experimental data was used, which were obtained using a laboratory-scale fixed bed reaction system. The results demonstrated that the intelligent modeling approach is greatly convenient and effective for the prediction of the biochar yield. In particular, the novel LS-SVM model has a more satisfying predicting performance and its robustness is better than the traditional ANN model. The introduction and application of the LS-SVM modeling method gives a successful example, which is a good reference for the modeling study of cattle manure pyrolysis process, even other similar processes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Games and machine learning: a powerful combination in an artificial intelligence course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-03-01

    Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

  19. A new tool for man/machine integration

    International Nuclear Information System (INIS)

    Sommer, W.C.

    1981-01-01

    A popular term within the nuclear power industry today, as a result of TMI, is man/machine interface. It has been determined that greater acknowledgement of this interface is necessary within the industry to integrate the design and operational aspects of a system. What is required is an operational tool that can be used early in the engineering stages of a project and passed on later in time to those who will be responsible to operate that particular system. This paper discusses one such fundamental operations tool that is applied to a process system, its display devices, and its operator actions in a methodical fashion to integrate the machine for man's understanding and proper use. This new tool, referred to as an Operational Schematic, is shown and described. Briefly, it unites, in one location, the important operational display devices with the system process devices. A man can now see the beginning and end of each information and control loop to better understand its function within the system. A method is presented whereby in designing for operability, the schematic is utilized in three phases. The method results in two basic documents, one describes ''what'' is to be operated and the other ''how'' it is to be operated. This integration concept has now considered the hardware spectrum from sensor-to-display and operated the display (on paper) to confirm its operability. Now that the design aspects are complete, the later-in-time operational aspects need to be addressed for the man using the process system. Training personnel in operating and testing the process system is as important as the original design. To accomplish these activities, documents are prepared to instruct personnel how to operate (and test) the system under a variety of circumstances

  20. Tool wear of a single-crystal diamond tool in nano-groove machining of a quartz glass plate

    International Nuclear Information System (INIS)

    Yoshino, Masahiko; Nakajima, Satoshi; Terano, Motoki

    2015-01-01

    Tool wear characteristics of a diamond tool in ductile mode machining are presented in this paper. Nano-groove machining of a quartz glass plate was conducted to examine the tool wear rate of a single-crystal diamond tool. Effects of lubrication on the tool wear rate were also evaluated. A numerical simulation technique was developed to evaluate the tool temperature and normal stress acting on the wear surface. From the simulation results it was found that the tool temperature does not increase during the machining experiment. It is also demonstrated that tool wear is attributed to the abrasive wear mechanism, but the effect of the adhesion wear mechanism is minor in nano-groove machining. It is found that the tool wear rate is reduced by using water or kerosene as a lubricant. (paper)

  1. Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

    Science.gov (United States)

    Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

    2017-08-01

    This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

  2. Toward Augmented Radiologists: Changes in Radiology Education in the Era of Machine Learning and Artificial Intelligence.

    Science.gov (United States)

    Tajmir, Shahein H; Alkasab, Tarik K

    2018-06-01

    Radiology practice will be altered by the coming of artificial intelligence, and the process of learning in radiology will be similarly affected. In the short term, radiologists will need to understand the first wave of artificially intelligent tools, how they can help them improve their practice, and be able to effectively supervise their use. Radiology training programs will need to develop curricula to help trainees acquire the knowledge to carry out this new supervisory duty of radiologists. In the longer term, artificially intelligent software assistants could have a transformative effect on the training of residents and fellows, and offer new opportunities to bring learning into the ongoing practice of attending radiologists. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  3. Customer Data Analysis Model using Business Intelligence Tools in Telecommunication Companies

    Directory of Open Access Journals (Sweden)

    Monica LIA

    2015-10-01

    Full Text Available This article presents a customer data analysis model in a telecommunication company and business intelligence tools for data modelling, transforming, data visualization and dynamic reports building . For a mature market, knowing the information inside the data and making forecast for strategic decision become more important in Romanian Market. Business Intelligence tools are used in business organization as support for decision making.

  4. Machine Intelligence

    Science.gov (United States)

    2013-03-01

    angular velocity of the pole. There are three available actions; accelerate to the left, to the right, and to coast. We use a problem set of 20 different...the angular velocities of the beams, θ ′ 1 and θ ′ 2. Once again, time is discretized into small intervals, and during any such interval the learner...with a maximum of 200 generations of learning. Neuroevolution is provided by Another NEAT Java Implementation (ANJI) 2. We used the Sarsa(λ) learning

  5. Routine human-competitive machine intelligence by means of genetic programming

    Science.gov (United States)

    Koza, John R.; Streeter, Matthew J.; Keane, Martin

    2004-01-01

    Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper demonstrates that genetic programming (1) now routinely delivers high-return human-competitive machine intelligence; (2) is an automated invention machine; (3) can automatically create a general solution to a problem in the form of a parameterized topology; and (4) has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. Recent results involving the automatic synthesis of the topology and sizing of analog electrical circuits and controllers demonstrate these points.

  6. A study of an intelligent FME system for SFCR tools

    Energy Technology Data Exchange (ETDEWEB)

    Hassan, H.A., E-mail: Hassan.hassan@opg.com [Ontario Power Generation, Toronto, Ontario (Canada)

    2008-07-01

    In the nuclear field, the accurate identification, tracking and history documentation of every nuclear tool, equipment or component is a key to safety, operational and maintenance excellence, and security of the nuclear reactor. This paper offers a study of the possible development of the present Foreign Material Exclusion (FME) system using an Intelligent Nuclear Tools Identification System, (INTIS), that was created and customized for the Single Fuel Channel Replacement (SFCR) Tools. The conceptual design of the INTIS was presented comparing the current and the proposed systems in terms of the time, the cost and the radiation doses received by the employees during the SFCR maintenance jobs. A model was created to help better understand and analyze the effects of deployment of the INTIS on the time, performance, accuracy, received dose and finally the total cost. The model may be also extended to solve other nuclear applications problems. The INTIS is based on Radio Frequency Identification (RFID) Smart Tags which are networked with readers and service computers. The System software was designed to communicate with the network to provide the coordinate information for any component at any time. It also allows digital signatures for use and/or approval to use the components and automatically updates their Data Base Management Systems (DBMS) history in terms of the person performing the job, the time period and date of use. This feature together with the information of part's life span could be used in the planning process for the predictive and preventive maintenance. As a case study, the model was applied to a pilot project for SFCR Tools FME. The INTIS automatically records all the tools to be used inside the vault and make real time tracking of any misplaced tool. It also automatically performs a continuous check of all tools, sending an alarm if any of the tools was left inside the vault after the job is done. Finally, a discussion of the results of the

  7. A study of an intelligent FME system for SFCR tools

    International Nuclear Information System (INIS)

    Hassan, H.A.

    2008-01-01

    In the nuclear field, the accurate identification, tracking and history documentation of every nuclear tool, equipment or component is a key to safety, operational and maintenance excellence, and security of the nuclear reactor. This paper offers a study of the possible development of the present Foreign Material Exclusion (FME) system using an Intelligent Nuclear Tools Identification System, (INTIS), that was created and customized for the Single Fuel Channel Replacement (SFCR) Tools. The conceptual design of the INTIS was presented comparing the current and the proposed systems in terms of the time, the cost and the radiation doses received by the employees during the SFCR maintenance jobs. A model was created to help better understand and analyze the effects of deployment of the INTIS on the time, performance, accuracy, received dose and finally the total cost. The model may be also extended to solve other nuclear applications problems. The INTIS is based on Radio Frequency Identification (RFID) Smart Tags which are networked with readers and service computers. The System software was designed to communicate with the network to provide the coordinate information for any component at any time. It also allows digital signatures for use and/or approval to use the components and automatically updates their Data Base Management Systems (DBMS) history in terms of the person performing the job, the time period and date of use. This feature together with the information of part's life span could be used in the planning process for the predictive and preventive maintenance. As a case study, the model was applied to a pilot project for SFCR Tools FME. The INTIS automatically records all the tools to be used inside the vault and make real time tracking of any misplaced tool. It also automatically performs a continuous check of all tools, sending an alarm if any of the tools was left inside the vault after the job is done. Finally, a discussion of the results of the system

  8. The ethical intelligence: a tool guidance in the process of the negotiation

    Directory of Open Access Journals (Sweden)

    Cristina Seijo

    2014-08-01

    Full Text Available The present article is the result of a research, which has as object present a theoretical contrast that invites to the reflection on the ethical intelligence as a tool guidance in the negotiation. In the same one there are approached the different types of ethical intelligence; spatial intelligence, rational intelligence, emotional intelligence among others, equally one refers associative intelligence to the processes of negotiation and to the tactics of negotiation. In this respect, it is possible to deal to the ethical intelligence as the aptitude to examine the moral standards of the individual and of the society to decide between what this one correct or incorrect and to be able like that to solve the different problematic ones for which an individual or a society cross. For this reason, one invites to start mechanisms of transparency and participation by virtue of which the ethical intelligence is born in mind as the threshold that orientates this process of negotiation. 

  9. Modeling of tool path for the CNC sheet cutting machines

    Science.gov (United States)

    Petunin, Aleksandr A.

    2015-11-01

    In the paper the problem of tool path optimization for CNC (Computer Numerical Control) cutting machines is considered. The classification of the cutting techniques is offered. We also propose a new classification of toll path problems. The tasks of cost minimization and time minimization for standard cutting technique (Continuous Cutting Problem, CCP) and for one of non-standard cutting techniques (Segment Continuous Cutting Problem, SCCP) are formalized. We show that the optimization tasks can be interpreted as discrete optimization problem (generalized travel salesman problem with additional constraints, GTSP). Formalization of some constraints for these tasks is described. For the solution GTSP we offer to use mathematical model of Prof. Chentsov based on concept of a megalopolis and dynamic programming.

  10. The NASA Program Management Tool: A New Vision in Business Intelligence

    Science.gov (United States)

    Maluf, David A.; Swanson, Keith; Putz, Peter; Bell, David G.; Gawdiak, Yuri

    2006-01-01

    This paper describes a novel approach to business intelligence and program management for large technology enterprises like the U.S. National Aeronautics and Space Administration (NASA). Two key distinctions of the approach are that 1) standard business documents are the user interface, and 2) a "schema-less" XML database enables flexible integration of technology information for use by both humans and machines in a highly dynamic environment. The implementation utilizes patent-pending NASA software called the NASA Program Management Tool (PMT) and its underlying "schema-less" XML database called Netmark. Initial benefits of PMT include elimination of discrepancies between business documents that use the same information and "paperwork reduction" for program and project management in the form of reducing the effort required to understand standard reporting requirements and to comply with those reporting requirements. We project that the underlying approach to business intelligence will enable significant benefits in the timeliness, integrity and depth of business information available to decision makers on all organizational levels.

  11. Performance of Process Damping in Machining Titanium Alloys at Low Cutting Speed with Different Helix Tools

    International Nuclear Information System (INIS)

    Shaharun, M A; Yusoff, A R; Reza, M S; Jalal, K A

    2012-01-01

    Titanium is a strong, lustrous, corrosion-resistant and transition metal with a silver color to produce strong lightweight alloys for industrial process, automotive, medical instruments and other applications. However, it is very difficult to machine the titanium due to its poor machinability. When machining titanium alloys with the conventional tools, the wear rate of the tool is rapidly accelerate and it is generally difficult to achieve at high cutting speed. In order to get better understanding of machining titanium alloy, the interaction between machining structural system and the cutting process which result in machining instability will be studied. Process damping is a useful phenomenon that can be exploited to improve the limited productivity of low speed machining. In this study, experiments are performed to evaluate the performance of process damping of milling under different tool helix geometries. The results showed that the helix of 42° angle is significantly increase process damping performance in machining titanium alloy.

  12. Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation

    Science.gov (United States)

    Hu, Yao; Quinn, Christopher J.; Cai, Ximing; Garfinkle, Noah W.

    2017-11-01

    For agent-based modeling, the major challenges in deriving agents' behavioral rules arise from agents' bounded rationality and data scarcity. This study proposes a "gray box" approach to address the challenge by incorporating expert domain knowledge (i.e., human intelligence) with machine learning techniques (i.e., machine intelligence). Specifically, we propose using directed information graph (DIG), boosted regression trees (BRT), and domain knowledge to infer causal factors and identify behavioral rules from data. A case study is conducted to investigate farmers' pumping behavior in the Midwest, U.S.A. Results show that four factors identified by the DIG algorithm- corn price, underlying groundwater level, monthly mean temperature and precipitation- have main causal influences on agents' decisions on monthly groundwater irrigation depth. The agent-based model is then developed based on the behavioral rules represented by three DIGs and modeled by BRTs, and coupled with a physically-based groundwater model to investigate the impacts of agents' pumping behavior on the underlying groundwater system in the context of coupled human and environmental systems.

  13. Virtual reality solutions for the design of machine tools in practice

    OpenAIRE

    Zickner, H.; Neugebauer, Reimund; Weidlich, D.

    2006-01-01

    At the Virtual Reality Centre Production Engineering (VRCP) the Institute for Machine Tools and Production Processes (IWP) of the Chemnitz University of Technology and the Fraunhofer Institute for Machine Tools and Forming Technology (IWU) have developed several practical Virtual Reality (VR) based solutions for the industry. Some practical examples will show the benefits gained by the application of Virtual Reality techniques in the design process of machine tools and assembly lines.

  14. Small machine tools for small workpieces final report of the DFG priority program 1476

    CERN Document Server

    Sanders, Adam

    2017-01-01

    This contributed volume presents the research results of the program “Small machine tools for small work pieces” (SPP 1476), funded by the German Research Society (DFG). The book contains the final report of the priority program, presenting novel approached for size-adapted, reconfigurable micro machine tools. The target audience primarily comprises research experts and practitioners in the field of micro machine tools, but the book may also be beneficial for graduate students.

  15. Research on Key Technologies of Unit-Based CNC Machine Tool Assembly Design

    OpenAIRE

    Zhongqi Sheng; Lei Zhang; Hualong Xie; Changchun Liu

    2014-01-01

    Assembly is the part that produces the maximum workload and consumed time during product design and manufacturing process. CNC machine tool is the key basic equipment in manufacturing industry and research on assembly design technologies of CNC machine tool has theoretical significance and practical value. This study established a simplified ASRG for CNC machine tool. The connection between parts, semantic information of transmission, and geometric constraint information were quantified to as...

  16. Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

    Science.gov (United States)

    Yaratan, Huseyin

    2003-01-01

    An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

  17. CrN-based wear resistant hard coatings for machining and forming tools

    Energy Technology Data Exchange (ETDEWEB)

    Yang, S; Cooke, K E; Teer, D G [Teer Coatings Ltd, West Stone House, Berry Hill Industrial Estate, Droitwich, Worcestershire WR9 9AS (United Kingdom); Li, X [School of Metallurgy and Materials, University of Birmingham, Birmingham B15 2TT (United Kingdom); McIntosh, F [Rolls-Royce plc, Inchinnan, Renfrewshire PA4 9AF, Scotland (United Kingdom)

    2009-05-21

    Highly wear resistant multicomponent or multilayer hard coatings, based on CrN but incorporating other metals, have been developed using closed field unbalanced magnetron sputter ion plating technology. They are exploited in coated machining and forming tools cutting and forming of a wide range of materials in various application environments. These coatings are characterized by desirable properties including good adhesion, high hardness, high toughness, high wear resistance, high thermal stability and high machining capability for steel. The coatings appear to show almost universal working characteristics under operating conditions of low and high temperature, low and high machining speed, machining of ordinary materials and difficult to machine materials, and machining under lubricated and under minimum lubricant quantity or even dry conditions. These coatings can be used for cutting and for forming tools, for conventional (macro-) machining tools as well as for micromachining tools, either as a single coating or in combination with an advanced, self-lubricating topcoat.

  18. A Design to Digitalize Hydraulic Cylinder Control of a Machine Tool ...

    African Journals Online (AJOL)

    Conventionally hydraulic piston - cylinder servos are actuated using analogue controls for machine tool axis drives. In this paper a design of the axis control system of an NC milling machine which employs a small stepping motor to digitally actuated hydraulic piston - cylinder servo drives existing on the machines Y-axis is ...

  19. Assessing thermally induced errors of machine tools by 3D length measurements

    NARCIS (Netherlands)

    Florussen, G.H.J.; Delbressine, F.L.M.; Schellekens, P.H.J.

    2003-01-01

    A new measurement technique is proposed for the assessment of thermally induced errors of machine tools. The basic idea is to measure changes of length by a telescopic double ball bar (TDEB) at multiple locations in the machine's workspace while the machine is thermally excited. In addition thermal

  20. ANN-PSO Integrated Optimization Methodology for Intelligent Control of MMC Machining

    Science.gov (United States)

    Chandrasekaran, Muthumari; Tamang, Santosh

    2017-08-01

    Metal Matrix Composites (MMC) show improved properties in comparison with non-reinforced alloys and have found increased application in automotive and aerospace industries. The selection of optimum machining parameters to produce components of desired surface roughness is of great concern considering the quality and economy of manufacturing process. In this study, a surface roughness prediction model for turning Al-SiCp MMC is developed using Artificial Neural Network (ANN). Three turning parameters viz., spindle speed ( N), feed rate ( f) and depth of cut ( d) were considered as input neurons and surface roughness was an output neuron. ANN architecture having 3 -5 -1 is found to be optimum and the model predicts with an average percentage error of 7.72 %. Particle Swarm Optimization (PSO) technique is used for optimizing parameters to minimize machining time. The innovative aspect of this work is the development of an integrated ANN-PSO optimization method for intelligent control of MMC machining process applicable to manufacturing industries. The robustness of the method shows its superiority for obtaining optimum cutting parameters satisfying desired surface roughness. The method has better convergent capability with minimum number of iterations.

  1. Machining of AISI D2 Tool Steel with Multiple Hole Electrodes by EDM Process

    Science.gov (United States)

    Prasad Prathipati, R.; Devuri, Venkateswarlu; Cheepu, Muralimohan; Gudimetla, Kondaiah; Uzwal Kiran, R.

    2018-03-01

    In recent years, with the increasing of technology the demand for machining processes is increasing for the newly developed materials. The conventional machining processes are not adequate to meet the accuracy of the machining of these materials. The non-conventional machining processes of electrical discharge machining is one of the most efficient machining processes is being widely used to machining of high accuracy products of various industries. The optimum selection of process parameters is very important in machining processes as that of an electrical discharge machining as they determine surface quality and dimensional precision of the obtained parts, even though time consumption rate is higher for machining of large dimension features. In this work, D2 high carbon and chromium tool steel has been machined using electrical discharge machining with the multiple hole electrode technique. The D2 steel has several applications such as forming dies, extrusion dies and thread rolling. But the machining of this tool steel is very hard because of it shard alloyed elements of V, Cr and Mo which enhance its strength and wear properties. However, the machining is possible by using electrical discharge machining process and the present study implemented a new technique to reduce the machining time using a multiple hole copper electrode. In this technique, while machining with multiple holes electrode, fin like projections are obtained, which can be removed easily by chipping. Then the finishing is done by using solid electrode. The machining time is reduced to around 50% while using multiple hole electrode technique for electrical discharge machining.

  2. Eddy currents self-tuning dynamic vibration absorber for machine tool chatter suppression

    OpenAIRE

    Aguirre , Gorka; Gorostiaga , Mikel; Porchez , Thomas; Munoa , Jokin

    2013-01-01

    International audience; The current trend in machine tool design aims at stiffer machines with lowerinfluence of friction, leading to faster and more precise machines. However, this is atthe expense of reducing the machine damping, which is mainly produced by friction,and thus increasing the risk of suffering from a self-excited vibration named chatter,which limits the productivity of the process. Dynamic vibration absorbers (DVAs)offer a relatively simple and low cost solution to reduce chat...

  3. A comparative machining study of diamond-coated tools made by ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    adherent diamond films on WC–CO tools by all three deposition models and has allowed completion of the ..... cesses with hard turning machining will affect future demand for PCBN (and cBN coated) tools. 6. ... Business Communication Co.

  4. Effect of electrical discharge machining on surface characteristics and machining damage of AISI D2 tool steel

    International Nuclear Information System (INIS)

    Guu, Y.H.; Hocheng, H.; Chou, C.Y.; Deng, C.S.

    2003-01-01

    In this work the electrical discharge machining (EDM) of AISI D2 tool steel was investigated. The surface characteristics and machining damage caused by EDM were studied in terms of machining parameters. Based on the experimental data, an empirical model of the tool steel was also proposed. A new damage variable was used to study the EDM damage. The workpiece surface and re-solidified layers were examined by a scanning electron microscopy. Surface roughness was determined with a surface profilometer. The residual stress acting on the EDM specimen was measured by the X-ray diffraction technique. Experimental results indicate that the thickness of the recast layer, and surface roughness are proportional to the power input. The EDM process introduces tensile residual stress on the machined surface. The EDM damage leads to strength degradation

  5. Methodology Investigation of AI(Artificial Intelligence) Test Officer Support Tool. Volume 1

    Science.gov (United States)

    1989-03-01

    American Association for Artificial inteligence A! ............. Artificial inteliigence AMC ............ Unt:ed States Army Maeriel Comand ASL...block number) FIELD GROUP SUB-GROUP Artificial Intelligence, Expert Systems Automated Aids to Testing 9. ABSTRACT (Continue on reverse if necessary and...identify by block number) This report covers the application of Artificial Intelligence-Techniques to the problem of creating automated tools to

  6. Machine and Woodworking Tool Safety. Module SH-24. Safety and Health.

    Science.gov (United States)

    Center for Occupational Research and Development, Inc., Waco, TX.

    This student module on machine and woodworking tool safety is one of 50 modules concerned with job safety and health. This module discusses specific practices and precautions concerned with the efficient operation and use of most machine and woodworking tools in use today. Following the introduction, 13 objectives (each keyed to a page in the…

  7. Advancing Research in Second Language Writing through Computational Tools and Machine Learning Techniques: A Research Agenda

    Science.gov (United States)

    Crossley, Scott A.

    2013-01-01

    This paper provides an agenda for replication studies focusing on second language (L2) writing and the use of natural language processing (NLP) tools and machine learning algorithms. Specifically, it introduces a range of the available NLP tools and machine learning algorithms and demonstrates how these could be used to replicate seminal studies…

  8. A new accurate curvature matching and optimal tool based five-axis machining algorithm

    International Nuclear Information System (INIS)

    Lin, Than; Lee, Jae Woo; Bohez, Erik L. J.

    2009-01-01

    Free-form surfaces are widely used in CAD systems to describe the part surface. Today, the most advanced machining of free from surfaces is done in five-axis machining using a flat end mill cutter. However, five-axis machining requires complex algorithms for gouging avoidance, collision detection and powerful computer-aided manufacturing (CAM) systems to support various operations. An accurate and efficient method is proposed for five-axis CNC machining of free-form surfaces. The proposed algorithm selects the best tool and plans the tool path autonomously using curvature matching and integrated inverse kinematics of the machine tool. The new algorithm uses the real cutter contact tool path generated by the inverse kinematics and not the linearized piecewise real cutter location tool path

  9. Business Intelligence tools as an element of information supply system

    Directory of Open Access Journals (Sweden)

    Agnieszka Szmelter

    2013-12-01

    Full Text Available This paper aims to present theBusiness Intelligence toolsas an element improvingflow of information withinthe management information systemand as atool to facilitate theachieving the objectives ofinformation supply system.In the firstpart of the paperthe author presents the issuesrelatedto the specific character of information as a kind of resource and functioning ofthe information supply systemin the enterprise. The secondpart of the articleincludethe characteristics ofBusiness Intelligence systems. The thirdpart deals withthe impact ofBusiness Intelligence toolsto the ongoingactivities ofinformation supply system.

  10. Profiling nonhuman intelligence: An exercise in developing unbiased tools for describing other "types" of intelligence on earth

    Science.gov (United States)

    Herzing, Denise L.

    2014-02-01

    Intelligence has historically been studied by comparing nonhuman cognitive and language abilities with human abilities. Primate-like species, which show human-like anatomy and share evolutionary lineage, have been the most studied. However, when comparing animals of non-primate origins our abilities to profile the potential for intelligence remains inadequate. Historically our measures for nonhuman intelligence have included a variety of tools: (1) physical measurements - brain to body ratio, brain structure/convolution/neural density, presence of artifacts and physical tools, (2) observational and sensory measurements - sensory signals, complexity of signals, cross-modal abilities, social complexity, (3) data mining - information theory, signal/noise, pattern recognition, (4) experimentation - memory, cognition, language comprehension/use, theory of mind, (5) direct interfaces - one way and two way interfaces with primates, dolphins, birds and (6) accidental interactions - human/animal symbiosis, cross-species enculturation. Because humans tend to focus on "human-like" attributes and measures and scientists are often unwilling to consider other "types" of intelligence that may not be human equated, our abilities to profile "types" of intelligence that differ on a variety of scales is weak. Just as biologists stretch their definitions of life to look at extremophiles in unusual conditions, so must we stretch our descriptions of types of minds and begin profiling, rather than equating, other life forms we may encounter.

  11. Use of Business Intelligence Tools in the DSN

    Science.gov (United States)

    Statman, Joseph I.; Zendejas, Silvino C.

    2010-01-01

    JPL has operated the Deep Space Network (DSN) on behalf of NASA since the 1960's. Over the last two decades, the DSN budget has generally declined in real-year dollars while the aging assets required more attention, and the missions became more complex. As a result, the DSN budget has been increasingly consumed by Operations and Maintenance (O&M), significantly reducing the funding wedge available for technology investment and for enhancing the DSN capability and capacity. Responding to this budget squeeze, the DSN launched an effort to improve the cost-efficiency of the O&M. In this paper we: elaborate on the methodology adopted to understand "where the time and money are used"-surprisingly, most of the data required for metrics development was readily available in existing databases-we have used commercial Business Intelligence (BI) tools to mine the databases and automatically extract the metrics (including trends) and distribute them weekly to interested parties; describe the DSN-specific effort to convert the intuitive understanding of "where the time is spent" into meaningful and actionable metrics that quantify use of resources, highlight candidate areas of improvement, and establish trends; and discuss the use of the BI-derived metrics-one of the most fascinating processes was the dramatic improvement in some areas of operations when the metrics were shared with the operators-the visibility of the metrics, and a self-induced competition, caused almost immediate improvement in some areas. While the near-term use of the metrics is to quantify the processes and track the improvement, these techniques will be just as useful in monitoring the process, e.g. as an input to a lean-six-sigma process.

  12. Machine learning & artificial intelligence in the quantum domain: a review of recent progress.

    Science.gov (United States)

    Dunjko, Vedran; Briegel, Hans J

    2018-03-05

    Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and

  13. Airline company management: 'Defining of necessary number of employees in airline by using artificial intelligence tools'

    OpenAIRE

    Petrović, Dragan M.; Puharic, Mirjana A.; Jovanović, Tomislav Ž.

    2015-01-01

    In this paper the model for preliminary estimation of number of employees in airline by using of artificial intelligence tools. It is assumed that the tools of artificial intelligence can be applied even for complex tasks such as defining the number of employees in the airline. The results obtained can be used for planning the number of employees, ie. planning the necessary financial investments in human resources, and may also be useful for a preliminary analysis of the airlines that choose ...

  14. Pathogenesis-based treatments in primary Sjogren's syndrome using artificial intelligence and advanced machine learning techniques: a systematic literature review.

    Science.gov (United States)

    Foulquier, Nathan; Redou, Pascal; Le Gal, Christophe; Rouvière, Bénédicte; Pers, Jacques-Olivier; Saraux, Alain

    2018-05-17

    Big data analysis has become a common way to extract information from complex and large datasets among most scientific domains. This approach is now used to study large cohorts of patients in medicine. This work is a review of publications that have used artificial intelligence and advanced machine learning techniques to study physio pathogenesis-based treatments in pSS. A systematic literature review retrieved all articles reporting on the use of advanced statistical analysis applied to the study of systemic autoimmune diseases (SADs) over the last decade. An automatic bibliography screening method has been developed to perform this task. The program called BIBOT was designed to fetch and analyze articles from the pubmed database using a list of keywords and Natural Language Processing approaches. The evolution of trends in statistical approaches, sizes of cohorts and number of publications over this period were also computed in the process. In all, 44077 abstracts were screened and 1017 publications were analyzed. The mean number of selected articles was 101.0 (S.D. 19.16) by year, but increased significantly over the time (from 74 articles in 2008 to 138 in 2017). Among them only 12 focused on pSS but none of them emphasized on the aspect of pathogenesis-based treatments. To conclude, medicine progressively enters the era of big data analysis and artificial intelligence, but these approaches are not yet used to describe pSS-specific pathogenesis-based treatment. Nevertheless, large multicentre studies are investigating this aspect with advanced algorithmic tools on large cohorts of SADs patients.

  15. Optimization of fuel exchange machine operation for boiling water reactors using an artificial intelligence technique

    International Nuclear Information System (INIS)

    Sekimizu, K.; Araki, T.; Tatemichi, S.I.

    1987-01-01

    Optimization of fuel assembly exchange machine movements during periodic refueling outage is discussed. The fuel assembly movements during a fuel shuffling were examined, and it was found that the fuel assembly movements consist of two different movement sequences;one is the ''PATH,'' which begins at a discharged fuel assembly and terminates at a fresh fuel assembly, and the other is the ''LOOP,'' where fuel assemblies circulate in the core. It is also shown that fuel-loading patterns during the fuel shuffling can be expressed by the state of each PATH, which is the number of elements already accomplished in the PATH actions. Based on this fact, a scheme to determine a fuel assembly movement sequence within the constraint was formulated using the artificial intelligence language PROLOG. An additional merit to the scheme is that it can simultaneously evaluate fuel assembly movement, due to the control rods and local power range monitor exchange, in addition to normal fuel shuffling. Fuel assembly movements, for fuel shuffling in a 540-MW(electric) boiling water reactor power plant, were calculated by this scheme. It is also shown that the true optimization to minimize the fuel exchange machine movements would be costly to obtain due to the number of alternatives that would need to be evaluated. However, a method to obtain a quasi-optimum solution is suggested

  16. MLBCD: a machine learning tool for big clinical data.

    Science.gov (United States)

    Luo, Gang

    2015-01-01

    Predictive modeling is fundamental for extracting value from large clinical data sets, or "big clinical data," advancing clinical research, and improving healthcare. Machine learning is a powerful approach to predictive modeling. Two factors make machine learning challenging for healthcare researchers. First, before training a machine learning model, the values of one or more model parameters called hyper-parameters must typically be specified. Due to their inexperience with machine learning, it is hard for healthcare researchers to choose an appropriate algorithm and hyper-parameter values. Second, many clinical data are stored in a special format. These data must be iteratively transformed into the relational table format before conducting predictive modeling. This transformation is time-consuming and requires computing expertise. This paper presents our vision for and design of MLBCD (Machine Learning for Big Clinical Data), a new software system aiming to address these challenges and facilitate building machine learning predictive models using big clinical data. The paper describes MLBCD's design in detail. By making machine learning accessible to healthcare researchers, MLBCD will open the use of big clinical data and increase the ability to foster biomedical discovery and improve care.

  17. Identification of Technological Parameters of Ni-Alloys When Machining by Monolithic Ceramic Milling Tool

    Science.gov (United States)

    Czán, Andrej; Kubala, Ondrej; Danis, Igor; Czánová, Tatiana; Holubják, Jozef; Mikloš, Matej

    2017-12-01

    The ever-increasing production and the usage of hard-to-machine progressive materials are the main cause of continual finding of new ways and methods of machining. One of these ways is the ceramic milling tool, which combines the pros of conventional ceramic cutting materials and pros of conventional coating steel-based insert. These properties allow to improve cutting conditions and so increase the productivity with preserved quality known from conventional tools usage. In this paper, there is made the identification of properties and possibilities of this tool when machining of hard-to-machine materials such as nickel alloys using in airplanes engines. This article is focused on the analysis and evaluation ordinary technological parameters and surface quality, mainly roughness of surface and quality of machined surface and tool wearing.

  18. An Intelligent and Interactive Simulation and Tutoring Environment for Exploring and Learning Simple Machines

    Science.gov (United States)

    Myneni, Lakshman Sundeep

    Students in middle school science classes have difficulty mastering physics concepts such as energy and work, taught in the context of simple machines. Moreover, students' naive conceptions of physics often remain unchanged after completing a science class. To address this problem, I developed an intelligent tutoring system, called the Virtual Physics System (ViPS), which coaches students through problem solving with one class of simple machines, pulley systems. The tutor uses a unique cognitive based approach to teaching simple machines, and includes innovations in three areas. (1) It employs a teaching strategy that focuses on highlighting links among concepts of the domain that are essential for conceptual understanding yet are seldom learned by students. (2) Concepts are taught through a combination of effective human tutoring techniques (e.g., hinting) and simulations. (3) For each student, the system identifies which misconceptions he or she has, from a common set of student misconceptions gathered from domain experts, and tailors tutoring to match the correct line of scientific reasoning regarding the misconceptions. ViPS was implemented as a platform on which students can design and simulate pulley system experiments, integrated with a constraint-based tutor that intervenes when students make errors during problem solving to teach them and to help them. ViPS has a web-based client-server architecture, and has been implemented using Java technologies. ViPS is different from existing physics simulations and tutoring systems due to several original features. (1). It is the first system to integrate a simulation based virtual experimentation platform with an intelligent tutoring component. (2) It uses a novel approach, based on Bayesian networks, to help students construct correct pulley systems for experimental simulation. (3) It identifies student misconceptions based on a novel decision tree applied to student pretest scores, and tailors tutoring to

  19. Intelligent controller of a flexible hybrid robot machine for ITER assembly and maintenance

    International Nuclear Information System (INIS)

    Al-saedi, Mazin I.; Wu, Huapeng; Handroos, Heikki

    2014-01-01

    Highlights: • Studying flexible multibody dynamic of hybrid parallel robot. • Investigating fuzzy-PD controller to control a hybrid flexible hydraulically driven robot. • Investigating ANFIS-PD controller to control a hybrid flexible robot. Compare to traditional PID this method gives better performance. • Using the equilibrium of reaction forces between the parallel and serial parts of hybrid robot to control the serial part hydraulically driven. - Abstract: The assembly and maintenance of International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. To fulfill the tasks in ITER application, this paper presents a hybrid redundant manipulator with four DOFs provided by serial kinematic axes and six DOFs by parallel mechanism. Thus, in machining, to achieve greater end-effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. In this paper, the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two control schemes have been investigated: (1) fuzzy-PID self tuning controller composed of the conventional PID control and with fuzzy logic; (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel robot based on rod position predictions. The obtained results of the fuzzy-PID and ANFIS-PID self tuning controller can reduce more tracking errors than the conventional PID controller. Subsequently, the serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should

  20. Intelligent controller of a flexible hybrid robot machine for ITER assembly and maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Al-saedi, Mazin I., E-mail: mazin.al-saedi@lut.fi; Wu, Huapeng; Handroos, Heikki

    2014-10-15

    Highlights: • Studying flexible multibody dynamic of hybrid parallel robot. • Investigating fuzzy-PD controller to control a hybrid flexible hydraulically driven robot. • Investigating ANFIS-PD controller to control a hybrid flexible robot. Compare to traditional PID this method gives better performance. • Using the equilibrium of reaction forces between the parallel and serial parts of hybrid robot to control the serial part hydraulically driven. - Abstract: The assembly and maintenance of International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. To fulfill the tasks in ITER application, this paper presents a hybrid redundant manipulator with four DOFs provided by serial kinematic axes and six DOFs by parallel mechanism. Thus, in machining, to achieve greater end-effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. In this paper, the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two control schemes have been investigated: (1) fuzzy-PID self tuning controller composed of the conventional PID control and with fuzzy logic; (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel robot based on rod position predictions. The obtained results of the fuzzy-PID and ANFIS-PID self tuning controller can reduce more tracking errors than the conventional PID controller. Subsequently, the serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should

  1. Intelligent tools for building a scientific information platform from research to implementation

    CERN Document Server

    Skonieczny, Łukasz; Rybiński, Henryk; Kryszkiewicz, Marzena; Niezgódka, Marek

    2014-01-01

    This book is a selection of results obtained within three years of research performed under SYNAT—a nation-wide scientific project aiming at creating an infrastructure for scientific content storage and sharing for academia, education and open knowledge society in Poland. The book is intended to be the last of the series related to the SYNAT project. The previous books, titled “Intelligent Tools for Building a Scientific Information Platform” and “Intelligent Tools for Building a Scientific Information Platform: Advanced Architectures and Solutions”, were published as volumes 390 and 467 in Springer's Studies in Computational Intelligence. Its contents is based on the SYNAT 2013 Workshop held in Warsaw. The papers included in this volume present an overview and insight into information retrieval, repository systems, text processing, ontology-based systems, text mining, multimedia data processing and advanced software engineering, addressing the problems of implementing intelligent tools for building...

  2. Adaptive control of mechatronic machine-tool equipment

    Directory of Open Access Journals (Sweden)

    R.G. Kudoyarov

    2015-09-01

    Full Text Available In this paper the method for designing a functional structure of mechatronic modules based on the developed classification of functional subsystems and the proposed turning machine modular structure is presented.

  3. Foam-machining tool with eddy-current transducer

    Science.gov (United States)

    Copper, W. P.

    1975-01-01

    Three-cutter machining system for foam-covered tanks incorporates eddy-current sensor. Sensor feeds signal to numerical controller which programs rotational and vertical axes of sensor travel, enabling cutterhead to profile around tank protrusions.

  4. Smart Cutting Tools and Smart Machining: Development Approaches, and Their Implementation and Application Perspectives

    Science.gov (United States)

    Cheng, Kai; Niu, Zhi-Chao; Wang, Robin C.; Rakowski, Richard; Bateman, Richard

    2017-09-01

    Smart machining has tremendous potential and is becoming one of new generation high value precision manufacturing technologies in line with the advance of Industry 4.0 concepts. This paper presents some innovative design concepts and, in particular, the development of four types of smart cutting tools, including a force-based smart cutting tool, a temperature-based internally-cooled cutting tool, a fast tool servo (FTS) and smart collets for ultraprecision and micro manufacturing purposes. Implementation and application perspectives of these smart cutting tools are explored and discussed particularly for smart machining against a number of industrial application requirements. They are contamination-free machining, machining of tool-wear-prone Si-based infra-red devices and medical applications, high speed micro milling and micro drilling, etc. Furthermore, implementation techniques are presented focusing on: (a) plug-and-produce design principle and the associated smart control algorithms, (b) piezoelectric film and surface acoustic wave transducers to measure cutting forces in process, (c) critical cutting temperature control in real-time machining, (d) in-process calibration through machining trials, (e) FE-based design and analysis of smart cutting tools, and (f) application exemplars on adaptive smart machining.

  5. Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

    Science.gov (United States)

    Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

    2015-01-01

    The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

  6. A review of designing machine tool for leanness

    Indian Academy of Sciences (India)

    Houshmand & Jamshidnezhad (2006) proposed a hierarchical structure to ... mentation of leanness in an organization but no such assessment system ... (v) Motion (walking or moving of people or equipment more than what is ..... software simulation based intelligent manufacturing system for a pilot CIM facility that could.

  7. Business intelligence as a tool in the management academic

    Directory of Open Access Journals (Sweden)

    Juan Jose Camargo Vega

    2016-06-01

    Full Text Available This paper presents a study, analyze and evaluate characteristics of existing data in the academic community, in order to recommend a model to apply Business Intelligence. It starts from the assumption that knowing the effects on the academic community, if you have a corporate strategy to facilitate decision-making in educational institutions. The results are based on a three dimensional cube, which are combining strong to make decisions with the information made. Finally, we come to different conclusions enabling give sufficient grounds to recommend a model that Integrate Business Intelligence in the academic environment.

  8. Direct numerical control of machine tools in a nuclear research center by the CAMAC system

    International Nuclear Information System (INIS)

    Zwoll, K.; Mueller, K.D.; Becks, B.; Erven, W.; Sauer, M.

    1977-01-01

    The production of mechanical parts in research centers can be improved by connecting several numerically controlled machine tools to a central process computer via a data link. The CAMAC Serial Highway with its expandable structure yields an economic and flexible system for this purpose. The CAMAC System also facilitates the development of modular components controlling the machine tools itself. A CAMAC installation controlling three different machine tools connected to a central computer (PDP11) via the CAMAC Serial Highway is described. Besides this application, part of the CAMAC hardware and software can also be used for a great variety of scientific experiments

  9. The relationships between ceramic tool life and different machining parameters

    International Nuclear Information System (INIS)

    El-Axir, M.H.; El-Masry, A.A.; Mashal, Y.A.H.

    2001-01-01

    With the increasing use of ceramic tool materials in applications, has come an increasing need for experimental data to assign the behavior of the life of these tool materials. Experimental results during turning operation show that it is possible to increase cutting tool life substantially by a proper variation of the cutting parameters used in this work. The tool lives (tool flank wear land length) of three different ceramic materials, namely; Silicon carbide (SiC), Alumina (Al/sub 2/O/sub 3/) and partially stabilized zirconia (PSZ) in addition to, Titanium carbide and high speed steel tools are investigated in this work. Also, The effect of varying the cutting speed, feed rate and tool rake angle on tool life of each tool material is studied. The experimental work was carried out utilizing one of the experimental design techniques based on response surface methodology. It was found that the SiC cutting tool showed the highest tool life among all materials tested in this work. It was also noticed that increasing the cutting speed has led to an increase in tool life for ceramic tools only. However, increasing the feed rate and tool rake angle resulted in a reduction in tool life in all materials examined in the present study. Further analysis conducted on SiC tool material to examine the effect of the interaction of cutting parameters on the tool life. (author)

  10. Intelligent Tutoring Systems for Collaborative Learning: Enhancements to Authoring Tools

    Science.gov (United States)

    Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol

    2013-01-01

    Collaborative and individual instruction may support different types of knowledge. Optimal instruction for a subject domain may therefore need to combine these two modes of instruction. There has not been much research, however, on combining individual and collaborative learning with Intelligent Tutoring Systems (ITSs). A first step is to expand…

  11. Sensor guided control and navigation with intelligent machines. Final technical report

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, Bijoy K.

    2001-03-26

    This item constitutes the final report on ''Visionics: An integrated approach to analysis and design of intelligent machines.'' The report discusses dynamical systems approach to problems in robust control of possibly time-varying linear systems, problems in vision and visually guided control, and, finally, applications of these control techniques to intelligent navigation with a mobile platform. Robust design of a controller for a time-varying system essentially deals with the problem of synthesizing a controller that can adapt to sudden changes in the parameters of the plant and can maintain stability. The approach presented is to design a compensator that simultaneously stabilizes each and every possible mode of the plant as the parameters undergo sudden and unexpected changes. Such changes can in fact be detected by a visual sensor and, hence, visually guided control problems are studied as a natural consequence. The problem here is to detect parameters of the plant and maintain st ability in the closed loop using a ccd camera as a sensor. The main result discussed in the report is the role of perspective systems theory that was developed in order to analyze such a detection and control problem. The robust control algorithms and the visually guided control algorithms are applied in the context of a PUMA 560 robot arm control where the goal is to visually locate a moving part on a mobile turntable. Such problems are of paramount importance in manufacturing with a certain lack of structure. Sensor guided control problems are extended to problems in robot navigation using a NOMADIC mobile platform with a ccd and a laser range finder as sensors. The localization and map building problems are studied with the objective of navigation in an unstructured terrain.

  12. A methodology for online visualization of the energy flow in a machine tool

    DEFF Research Database (Denmark)

    Mohammadi, Ali; Züst, Simon; Mayr, Josef

    2017-01-01

    the machining process and by this increasing its energy efficiency. This study intents to propose a method which has the capability of real-time monitoring of the entire energetic flows in a CNC machine tool including motors, pumps and cooling fluid. The structure of this approach is based on categorizing...

  13. Optimization of Surface Finish in Turning Operation by Considering the Machine Tool Vibration using Taguchi Method

    Directory of Open Access Journals (Sweden)

    Muhammad Munawar

    2012-01-01

    Full Text Available Optimization of surface roughness has been one of the primary objectives in most of the machining operations. Poor control on the desired surface roughness generates non conforming parts and results into increase in cost and loss of productivity due to rework or scrap. Surface roughness value is a result of several process variables among which machine tool condition is one of the significant variables. In this study, experimentation was carried out to investigate the effect of machine tool condition on surface roughness. Variable used to represent machine tool\\'s condition was vibration amplitude. Input parameters used, besides vibration amplitude, were feed rate and insert nose radius. Cutting speed and depth of cut were kept constant. Based on Taguchi orthogonal array, a series of experimentation was designed and performed on AISI 1040 carbon steel bar at default and induced machine tool\\'s vibration amplitudes. ANOVA (Analysis of Variance, revealed that vibration amplitude and feed rate had moderate effect on the surface roughness and insert nose radius had the highest significant effect on the surface roughness. It was also found that a machine tool with low vibration amplitude produced better surface roughness. Insert with larger nose radius produced better surface roughness at low feed rate.

  14. IDOCS: intelligent distributed ontology consensus system--the use of machine learning in retinal drusen phenotyping.

    Science.gov (United States)

    Thomas, George; Grassi, Michael A; Lee, John R; Edwards, Albert O; Gorin, Michael B; Klein, Ronald; Casavant, Thomas L; Scheetz, Todd E; Stone, Edwin M; Williams, Andrew B

    2007-05-01

    To use the power of knowledge acquisition and machine learning in the development of a collaborative computer classification system based on the features of age-related macular degeneration (AMD). A vocabulary was acquired from four AMD experts who examined 100 ophthalmoscopic images. The vocabulary was analyzed, hierarchically structured, and incorporated into a collaborative computer classification system called IDOCS. Using this system, three of the experts examined images from a second set of digital images compiled from more than 1000 patients with AMD. Images were annotated, and features were identified and defined. Decision trees, a machine learning method, were trained on the data collected and used to extract patterns. Interrelationships between the data from the different clinicians were investigated. Six drusen classes in the structured vocabulary were largely sufficient to describe all the identified features. The decision trees classified the data with 76.86% to 88.5% accuracy and distilled patterns in the form of hierarchical trees composed of 5 to 15 nodes. Experts were largely consistent in their characterization of soft, and to a lesser extent, hard drusen, but diverge in definition of other drusen. Size and crystalline morphology were the main determinants of drusen type across all experts. Machine learning is a powerful tool for the characterization of disease phenotypes. The creation of a defined feature set for AMD will facilitate the development of an IDOCS-based classification system.

  15. Integration of an intelligent systems behavior simulator and a scalable soldier-machine interface

    Science.gov (United States)

    Johnson, Tony; Manteuffel, Chris; Brewster, Benjamin; Tierney, Terry

    2007-04-01

    As the Army's Future Combat Systems (FCS) introduce emerging technologies and new force structures to the battlefield, soldiers will increasingly face new challenges in workload management. The next generation warfighter will be responsible for effectively managing robotic assets in addition to performing other missions. Studies of future battlefield operational scenarios involving the use of automation, including the specification of existing and proposed technologies, will provide significant insight into potential problem areas regarding soldier workload. The US Army Tank Automotive Research, Development, and Engineering Center (TARDEC) is currently executing an Army technology objective program to analyze and evaluate the effect of automated technologies and their associated control devices with respect to soldier workload. The Human-Robotic Interface (HRI) Intelligent Systems Behavior Simulator (ISBS) is a human performance measurement simulation system that allows modelers to develop constructive simulations of military scenarios with various deployments of interface technologies in order to evaluate operator effectiveness. One such interface is TARDEC's Scalable Soldier-Machine Interface (SMI). The scalable SMI provides a configurable machine interface application that is capable of adapting to several hardware platforms by recognizing the physical space limitations of the display device. This paper describes the integration of the ISBS and Scalable SMI applications, which will ultimately benefit both systems. The ISBS will be able to use the Scalable SMI to visualize the behaviors of virtual soldiers performing HRI tasks, such as route planning, and the scalable SMI will benefit from stimuli provided by the ISBS simulation environment. The paper describes the background of each system and details of the system integration approach.

  16. Support vector machine based diagnostic system for breast cancer using swarm intelligence.

    Science.gov (United States)

    Chen, Hui-Ling; Yang, Bo; Wang, Gang; Wang, Su-Jing; Liu, Jie; Liu, Da-You

    2012-08-01

    Breast cancer is becoming a leading cause of death among women in the whole world, meanwhile, it is confirmed that the early detection and accurate diagnosis of this disease can ensure a long survival of the patients. In this paper, a swarm intelligence technique based support vector machine classifier (PSO_SVM) is proposed for breast cancer diagnosis. In the proposed PSO-SVM, the issue of model selection and feature selection in SVM is simultaneously solved under particle swarm (PSO optimization) framework. A weighted function is adopted to design the objective function of PSO, which takes into account the average accuracy rates of SVM (ACC), the number of support vectors (SVs) and the selected features simultaneously. Furthermore, time varying acceleration coefficients (TVAC) and inertia weight (TVIW) are employed to efficiently control the local and global search in PSO algorithm. The effectiveness of PSO-SVM has been rigorously evaluated against the Wisconsin Breast Cancer Dataset (WBCD), which is commonly used among researchers who use machine learning methods for breast cancer diagnosis. The proposed system is compared with the grid search method with feature selection by F-score. The experimental results demonstrate that the proposed approach not only obtains much more appropriate model parameters and discriminative feature subset, but also needs smaller set of SVs for training, giving high predictive accuracy. In addition, Compared to the existing methods in previous studies, the proposed system can also be regarded as a promising success with the excellent classification accuracy of 99.3% via 10-fold cross validation (CV) analysis. Moreover, a combination of five informative features is identified, which might provide important insights to the nature of the breast cancer disease and give an important clue for the physicians to take a closer attention. We believe the promising result can ensure that the physicians make very accurate diagnostic decision in

  17. Winding machine and tools for the ISR Superconducting Quadrupole Prototype

    CERN Multimedia

    1975-01-01

    The picture shows the rotating and rocking winding machine with its "light" clamping system to keep the conductor turns in place during winding.At the back left one sees the conductor spool with its electromagnetic brake and the "heavy" clamping system used during curing. See also 7510217X, 7702690X.

  18. Support vector machine: a tool for mapping mineral prospectivity

    NARCIS (Netherlands)

    Zuo, R.; Carranza, E.J.M

    2011-01-01

    In this contribution, we describe an application of support vector machine (SVM), a supervised learning algorithm, to mineral prospectivity mapping. The free R package e1071 is used to construct a SVM with sigmoid kernel function to map prospectivity for Au deposits in western Meguma Terrain of Nova

  19. Towards a Tool for Computer Supported Configuring of Machine Systems

    DEFF Research Database (Denmark)

    Hansen, Claus Thorp

    1996-01-01

    An engineering designer designing a product determines not only the product's component structure, but also a set of different structures which carry product behaviour and performance and make the product suited for its life phases. Whereas the nature of the elements of a machine system is fairly...

  20. Big Data Analytics and Machine Intelligence Capability Development at NASA Langley Research Center: Strategy, Roadmap, and Progress

    Science.gov (United States)

    Ambur, Manjula Y.; Yagle, Jeremy J.; Reith, William; McLarney, Edward

    2016-01-01

    In 2014, a team of researchers, engineers and information technology specialists at NASA Langley Research Center developed a Big Data Analytics and Machine Intelligence Strategy and Roadmap as part of Langley's Comprehensive Digital Transformation Initiative, with the goal of identifying the goals, objectives, initiatives, and recommendations need to develop near-, mid- and long-term capabilities for data analytics and machine intelligence in aerospace domains. Since that time, significant progress has been made in developing pilots and projects in several research, engineering, and scientific domains by following the original strategy of collaboration between mission support organizations, mission organizations, and external partners from universities and industry. This report summarizes the work to date in Data Intensive Scientific Discovery, Deep Content Analytics, and Deep Q&A projects, as well as the progress made in collaboration, outreach, and education. Recommendations for continuing this success into future phases of the initiative are also made.

  1. Artificial Intelligence as a Business Forecasting and Error Handling Tool

    OpenAIRE

    Md. Tabrez Quasim; Rupak Chattopadhyay

    2015-01-01

     Any business enterprise must rely a lot on how well it can predict the future happenings. To cope up with the modern global customer demand, technological challenges, market competitions etc., any organization is compelled to foresee the future having maximum impact and least chances of errors. The traditional forecasting approaches have some limitations. That is why the business world is adopting the modern Artificial Intelligence based forecasting techniques. This paper has tried to presen...

  2. Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information

    OpenAIRE

    Kinch, Martin W.; Melis, Wim J.C.; Keates, Simeon

    2017-01-01

    This paper will consider the current state of Machine Learning for Artificial Intelligence, more specifically for applications, such as: Speech Recognition, Game Playing and Image Processing. The artificial world tends to make limited use of context in comparison to what currently happens in human life, while it would benefit from improvements in this area. Additionally, the process of transferring knowledge between application domains is another important area where artificial system can imp...

  3. A systematic approach to the application of Automation, Robotics, and Machine Intelligence Systems /ARAMIS/ to future space projects

    Science.gov (United States)

    Smith, D. B. S.

    1982-01-01

    The potential applications of Automation, Robotics, and Machine Intelligence Systems (ARAMIS) to space projects are investigated, through a systematic method. In this method selected space projects are broken down into space project tasks, and 69 of these tasks are selected for study. Candidate ARAMIS options are defined for each task. The relative merits of these options are evaluated according to seven indices of performance. Logical sequences of ARAMIS development are also defined. Based on this data, promising applications of ARAMIS are

  4. Machining of high performance workpiece materials with CBN coated cutting tools

    International Nuclear Information System (INIS)

    Uhlmann, E.; Fuentes, J.A. Oyanedel; Keunecke, M.

    2009-01-01

    The machining of high performance workpiece materials requires significantly harder cutting materials. In hard machining, the early tool wear occurs due to high process forces and temperatures. The hardest known material is the diamond, but steel materials cannot be machined with diamond tools because of the reactivity of iron with carbon. Cubic boron nitride (cBN) is the second hardest of all known materials. The supply of such PcBN indexable inserts, which are only geometrically simple and available, requires several work procedures and is cost-intensive. The development of a cBN coating for cutting tools, combine the advantages of a thin film system and of cBN. Flexible cemented carbide tools, in respect to the geometry can be coated. The cBN films with a thickness of up to 2 μm on cemented carbide substrates show excellent mechanical and physical properties. This paper describes the results of the machining of various workpiece materials in turning and milling operations regarding the tool life, resultant cutting force components and workpiece surface roughness. In turning tests of Inconel 718 and milling tests of chrome steel the high potential of cBN coatings for dry machining was proven. The results of the experiments were compared with common used tool coatings for the hard machining. Additionally, the wear mechanisms adhesion, abrasion, surface fatigue and tribo-oxidation were researched in model wear experiments.

  5. Intelligent Control of UPFC for Enhancing Transient Stability on Multi-Machine Power Systems

    Directory of Open Access Journals (Sweden)

    Hassan Barati

    2010-01-01

    Full Text Available One of the benefit of FACTS devices is increase of stability in power systems with control active and reactive power at during the fault in power system. Although, the power system stabilizers (PSSs have been one of the most common controls used to damp out oscillations, this device may not produce enough damping especially to inter-area mode and therefore, there is an increasing interest in using FACTS devices to aid in damping of these oscillations. In This paper, UPFC is used for damping oscillations and to enhance the transient stability performance of power systems. The controller parameters are designed using an efficient version of the Takagi-Sugeno fuzzy control scheme. The function based Takagi-Sugeno-Kang (TSK fuzzy controller uses. For optimization parameters of fuzzy PI controller, the GA, PSO and HGAPSO algorithms are used. The computer simulation results, the effect of UPFC with conventional PI controller, fuzzy PI controller and intelligent controllers (GA, PSO and HGAPSO for damping the local-mode and inter-area mode of under large and small disturbances in the four-machine two-area power system evaluated and compared.

  6. Intelligent Machine Vision for Automated Fence Intruder Detection Using Self-organizing Map

    Directory of Open Access Journals (Sweden)

    Veldin A. Talorete Jr.

    2017-03-01

    Full Text Available This paper presents an intelligent machine vision for automated fence intruder detection. A series of still captured images that contain fence events using Internet Protocol cameras was used as input data to the system. Two classifiers were used; the first is to classify human posture and the second one will classify intruder location. The system classifiers were implemented using Self-Organizing Map after the implementation of several image segmentation processes. The human posture classifier is in charge of classifying the detected subject’s posture patterns from subject’s silhouette. Moreover, the Intruder Localization Classifier is in charge of classifying the detected pattern’s location classifier will estimate the location of the intruder with respect to the fence using geometric feature from images as inputs. The system is capable of activating the alarm, display the actual image and depict the location of the intruder when an intruder is detected. In detecting intruder posture, the system’s success rate of 88%. Overall system accuracy for day-time intruder localization is 83% and an accuracy of 88% for night-time intruder localization

  7. Preliminary Development of Real Time Usage-Phase Monitoring System for CNC Machine Tools with a Case Study on CNC Machine VMC 250

    Science.gov (United States)

    Budi Harja, Herman; Prakosa, Tri; Raharno, Sri; Yuwana Martawirya, Yatna; Nurhadi, Indra; Setyo Nogroho, Alamsyah

    2018-03-01

    The production characteristic of job-shop industry at which products have wide variety but small amounts causes every machine tool will be shared to conduct production process with dynamic load. Its dynamic condition operation directly affects machine tools component reliability. Hence, determination of maintenance schedule for every component should be calculated based on actual usage of machine tools component. This paper describes study on development of monitoring system to obtaining information about each CNC machine tool component usage in real time approached by component grouping based on its operation phase. A special device has been developed for monitoring machine tool component usage by utilizing usage phase activity data taken from certain electronics components within CNC machine. The components are adaptor, servo driver and spindle driver, as well as some additional components such as microcontroller and relays. The obtained data are utilized for detecting machine utilization phases such as power on state, machine ready state or spindle running state. Experimental result have shown that the developed CNC machine tool monitoring system is capable of obtaining phase information of machine tool usage as well as its duration and displays the information at the user interface application.

  8. AFM surface imaging of AISI D2 tool steel machined by the EDM process

    International Nuclear Information System (INIS)

    Guu, Y.H.

    2005-01-01

    The surface morphology, surface roughness and micro-crack of AISI D2 tool steel machined by the electrical discharge machining (EDM) process were analyzed by means of the atomic force microscopy (AFM) technique. Experimental results indicate that the surface texture after EDM is determined by the discharge energy during processing. An excellent machined finish can be obtained by setting the machine parameters at a low pulse energy. The surface roughness and the depth of the micro-cracks were proportional to the power input. Furthermore, the AFM application yielded information about the depth of the micro-cracks is particularly important in the post treatment of AISI D2 tool steel machined by EDM

  9. AFM surface imaging of AISI D2 tool steel machined by the EDM process

    Science.gov (United States)

    Guu, Y. H.

    2005-04-01

    The surface morphology, surface roughness and micro-crack of AISI D2 tool steel machined by the electrical discharge machining (EDM) process were analyzed by means of the atomic force microscopy (AFM) technique. Experimental results indicate that the surface texture after EDM is determined by the discharge energy during processing. An excellent machined finish can be obtained by setting the machine parameters at a low pulse energy. The surface roughness and the depth of the micro-cracks were proportional to the power input. Furthermore, the AFM application yielded information about the depth of the micro-cracks is particularly important in the post treatment of AISI D2 tool steel machined by EDM.

  10. Using Machine Learning for Land Suitability Classification

    African Journals Online (AJOL)

    User

    West African Journal of Applied Ecology, vol. ... evidence for the utility of machine learning methods in land suitability classification especially MCS methods. ... Artificial intelligence tools. ..... Numerical values of index for the various classes.

  11. Support Vector Machine Based Tool for Plant Species Taxonomic Classification

    OpenAIRE

    Manimekalai .K; Vijaya.MS

    2014-01-01

    Plant species are living things and are generally categorized in terms of Domain, Kingdom, Phylum, Class, Order, Family, Genus and name of Species in a hierarchical fashion. This paper formulates the taxonomic leaf categorization problem as the hierarchical classification task and provides a suitable solution using a supervised learning technique namely support vector machine. Features are extracted from scanned images of plant leaves and trained using SVM. Only class, order, family of plants...

  12. Study on Dynamic Characteristics of Heavy Machine Tool-Composite Pile Foundation-Soil

    Directory of Open Access Journals (Sweden)

    CAI Li-Gang

    2014-09-01

    Full Text Available Heavy duty computer numerical control machine tools have characteristics of large self-weight, load and. The insufficiency of foundation bearing capacity leads to deformation of lathe bed, which effects machining accuracy. A combined-layer foundation model is created to describe the pile group foundation of multi-soil layer in this paper. Considering piles and soil in pile group as transversely isotropic material, equivalent constitutive relationship of composite foundation is constructed. A mathematical model is established by the introduction of boundary conditions, which is based on heavy duty computer numerical control machine tools-composite pile foundation-soil interaction system. And then, the response of different soil and pile depth is studied by a case. The model improves motion accuracy of machine tools.

  13. Forensic drug intelligence: an important tool in law enforcement.

    Science.gov (United States)

    Esseiva, Pierrre; Ioset, Sylvain; Anglada, Frédéric; Gasté, Laëtitia; Ribaux, Olivier; Margot, Pierre; Gallusser, Alain; Biedermann, Alex; Specht, Yves; Ottinger, Edmond

    2007-04-11

    Organised criminality is a great concern for national/international security. The demonstration of complex crimes is increasingly dependant on knowledge distributed within law-enforcement agencies and scientific disciplines. This separation of knowledge creates difficulties in reconstructing and prosecuting such crimes. Basic interdisciplinary research in drug intelligence combined with crime analysis, forensic intelligence, and traditional law enforcement investigation is leading to important advances in crime investigation support. Laboratory results constitute one highly dependable source of information that is both reliable and testable. Their operational use can support investigation and even provide undetected connections or organisation of structure. The foremost difficulties encountered by drug analysts are not principally of a chemical or analytical nature, but methodologies to extract parameters or features that are deemed to be crucial for handling and contextualising drug profiling data. An organised memory has been developed in order to provide accurate, timely, useful and meaningful information for linking spatially and temporally distinct events on a national and international level (including cross-border phenomena). Literature has already pointed out that forensic case data are amenable for use in an intelligence perspective if data and knowledge of specialised actors are appropriately organised, shared and processed. As a particular form of forensic case data, the authors' research focuses on parameters obtained through the systematic physical and chemical profiling of samples of illicit drugs. The procedure is used to infer and characterise links between samples that originate from the same and different seizures. The discussion will not, however, focus on how samples are actually analysed and compared as substantial literature on this topic already exists. Rather, attention is primarily drawn to an active and close collaboration between

  14. New tool holder design for cryogenic machining of Ti6Al4V

    Science.gov (United States)

    Bellin, Marco; Sartori, Stefano; Ghiotti, Andrea; Bruschi, Stefania

    2017-10-01

    The renewed demand of increasing the machinability of the Ti6Al4V titanium alloy to produce biomedical and aerospace parts working at high temperature has recently led to the application of low-temperature coolants instead of conventional cutting fluids to increase both the tool life and the machined surface integrity. In particular, the liquid nitrogen directed to the tool rake face has shown a great capability of reducing the temperature at the chip-tool interface, as well as the chemical interaction between the tool coating and the titanium to be machined, therefore limiting the tool crater wear, and improving, at the same time, the chip breakability. Furthermore, the nitrogen is a safe, non-harmful, non-corrosive, odorless, recyclable, non-polluting and abundant gas, characteristics that further qualify it as an environmental friendly coolant to be applied to machining processes. However, the behavior of the system composed by the tool and the tool holder, exposed to the cryogenics temperatures may represent a critical issue in order to obtain components within the required geometrical tolerances. On this basis, the paper aims at presenting the design of an innovative tool holder installed on a CNC lathe, which includes the cryogenic coolant provision system, and which is able to hinder the part possible distortions due to the liquid nitrogen adduction by stabilizing its dimensions through the use of heating cartridges and appropriate sensors to monitor the temperature evolution of the tool holder.

  15. Application of new tool material for electrical discharge machining ...

    Indian Academy of Sciences (India)

    Administrator

    MST Division, National Metallurgical Laboratory, Jamshedpur 831 007, India. MS received 8 July 2007; revised 25 April 2009. Abstract. In EDM, Cu and graphite are commonly used as tool materials. The poor wear resistance is the drawback of these tools. In the current study, an attempt has been made to develop a ...

  16. System Diagnostic Builder - A rule generation tool for expert systems that do intelligent data evaluation. [applied to Shuttle Mission Simulator

    Science.gov (United States)

    Nieten, Joseph; Burke, Roger

    1993-01-01

    Consideration is given to the System Diagnostic Builder (SDB), an automated knowledge acquisition tool using state-of-the-art AI technologies. The SDB employs an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert. Thus, data are captured from the subject system, classified, and used to drive the rule generation process. These rule bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The knowledge bases captured from the Shuttle Mission Simulator can be used as black box simulations by the Intelligent Computer Aided Training devices. The SDB can also be used to construct knowledge bases for the process control industry, such as chemical production or oil and gas production.

  17. Artificial intelligence, neural network, and Internet tool integration in a pathology workstation to improve information access

    Science.gov (United States)

    Sargis, J. C.; Gray, W. A.

    1999-03-01

    The APWS allows user friendly access to several legacy systems which would normally each demand domain expertise for proper utilization. The generalized model, including objects, classes, strategies and patterns is presented. The core components of the APWS are the Microsoft Windows 95 Operating System, Oracle, Oracle Power Objects, Artificial Intelligence tools, a medical hyperlibrary and a web site. The paper includes a discussion of how could be automated by taking advantage of the expert system, object oriented programming and intelligent relational database tools within the APWS.

  18. Airline company management: 'Defining of necessary number of employees in airline by using artificial intelligence tools'

    Directory of Open Access Journals (Sweden)

    Petrović Dragan M.

    2015-01-01

    Full Text Available In this paper the model for preliminary estimation of number of employees in airline by using of artificial intelligence tools. It is assumed that the tools of artificial intelligence can be applied even for complex tasks such as defining the number of employees in the airline. The results obtained can be used for planning the number of employees, ie. planning the necessary financial investments in human resources, and may also be useful for a preliminary analysis of the airlines that choose to do restructuring or plan to increase/decrease the number of operations. Results were compared with those obtained by regression analysis.

  19. [Remote intelligent Brunnstrom assessment system for upper limb rehabilitation for post-stroke based on extreme learning machine].

    Science.gov (United States)

    Wang, Yue; Yu, Lei; Fu, Jianming; Fang, Qiang

    2014-04-01

    In order to realize an individualized and specialized rehabilitation assessment of remoteness and intelligence, we set up a remote intelligent assessment system of upper limb movement function of post-stroke patients during rehabilitation. By using the remote rehabilitation training sensors and client data sampling software, we collected and uploaded the gesture data from a patient's forearm and upper arm during rehabilitation training to database of the server. Then a remote intelligent assessment system, which had been developed based on the extreme learning machine (ELM) algorithm and Brunnstrom stage assessment standard, was used to evaluate the gesture data. To evaluate the reliability of the proposed method, a group of 23 stroke patients, whose upper limb movement functions were in different recovery stages, and 4 healthy people, whose upper limb movement functions were normal, were recruited to finish the same training task. The results showed that, compared to that of the experienced rehabilitation expert who used the Brunnstrom stage standard table, the accuracy of the proposed remote Brunnstrom intelligent assessment system can reach a higher level, as 92.1%. The practical effects of surgery have proved that the proposed system could realize the intelligent assessment of upper limb movement function of post-stroke patients remotely, and it could also make the rehabilitation of the post-stroke patients at home or in a community care center possible.

  20. An intelligent tool for the training of nuclear plant operators

    International Nuclear Information System (INIS)

    Cordier, B.

    1990-01-01

    A new type of pedagogical tool has been developped for the training of nuclear power plant operation. This tool combines simulation and expert system. The first process developped is about Steam Generator Tube Rupture (S.G.T.R.). All nuclear power plants will be equiped with this system in 1989 and 1990. After this first experiment, others processes will be developped for this tool

  1. Data mining practical machine learning tools and techniques

    CERN Document Server

    Witten, Ian H

    2005-01-01

    As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same

  2. A Web-Based Authoring Tool for Algebra-Related Intelligent Tutoring Systems

    Directory of Open Access Journals (Sweden)

    Maria Virvou

    2000-01-01

    Full Text Available This paper describes the development of a web-based authoring tool for Intelligent Tutoring Systems. The tool aims to be useful to teachers and students of domains that make use of algebraic equations. The initial input to the tool is a "description" of a specific domain given by a human teacher. In return the tool provides assistance at the construction of exercises by the human teacher and then monitors the students while they are solving the exercises and provides appropriate feedback. The tool incorporates intelligence in its diagnostic component, which performs error diagnosis to students’ errors. It also handles the teaching material in a flexible and individualised way.

  3. Possibilities of Application of High Pressure Jet Assisted Machining in Hard Turning with Carbide Tools

    Directory of Open Access Journals (Sweden)

    G. Globočki Lakić

    2017-06-01

    Full Text Available High Pressure Jet Assisted Machining (HPJAM in turning is a hybrid machining method in which a high pressure jet of cooling and lubrication fluid, under high pressure (50 MPa, leads to the zone between the cutting tool edge and workpiece. An experimental study was performed to investigate the capabilities of conventional and high pressure cooling (HPC in the turning of hard-to-machine materials: hard-chromed and surface hardened steel Ck45 (58 HRc and hardened bearing steel 100Cr6 (62 HRc. Machining experiments were performed using coated carbide tools and highly cutting speed. Experimental measurements were performed for different input process parameters. The cooling capabilities are compared by monitoring of tool wear, tool life, cooling efficiency, and surface roughness. Connection between the tool wear and surface roughness is established. Experimental research show that the hard turning with carbide cutting tools and HP supply CLF provides numerous advantages from the techno-economic aspect: greater productivity, reduce of temperature in the cutting zone, improved control chip formation, extended tool life, low intensity of tool wear, surface roughness in acceptable limits, significant reduce of production costs related to the CLF.

  4. Towards the Development of Web-based Business intelligence Tools

    DEFF Research Database (Denmark)

    Georgiev, Lachezar; Tanev, Stoyan

    2011-01-01

    This paper focuses on using web search techniques in examining the co-creation strategies of technology driven firms. It does not focus on the co-creation results but describes the implementation of a software tool using data mining techniques to analyze the content on firms’ websites. The tool...

  5. Effect of different machining processes on the tool surface integrity and fatigue life

    Energy Technology Data Exchange (ETDEWEB)

    Cao, Chuan Liang [College of Mechanical and Electrical Engineering, Nanchang University, Nanchang (China); Zhang, Xianglin [School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan (China)

    2016-08-15

    Ultra-precision grinding, wire-cut electro discharge machining and lapping are often used to machine the tools in fine blanking industry. And the surface integrity from these machining processes causes great concerns in the research field. To study the effect of processing surface integrity on the fine blanking tool life, the surface integrity of different tool materials under different processing conditions and its influence on fatigue life were thoroughly analyzed in the present study. The result shows that the surface integrity of different materials was quite different on the same processing condition. For the same tool material, the surface integrity on varying processing conditions was quite different too and deeply influenced the fatigue life.

  6. Intelligent tools for building a scientific information platform advanced architectures and solutions

    CERN Document Server

    Skonieczny, Lukasz; Rybinski, Henryk; Kryszkiewicz, Marzena; Niezgodka, Marek

    2013-01-01

    This book is a selection of results obtained within two years of research per- formed under SYNAT - a nation-wide scientific project aiming at creating an infrastructure for scientific content storage and sharing for academia, education and open knowledge society in Poland. The selection refers to the research in artificial intelligence, knowledge discovery and data mining, information retrieval and natural language processing, addressing the problems of implementing intelligent tools for building a scientific information platform.This book is a continuation and extension of the ideas presented in “Intelligent Tools for Building a Scientific Information Platform” published as volume 390 in the same series in 2012. It is based on the SYNAT 2012 Workshop held in Warsaw. The papers included in this volume present an overview and insight into information retrieval, repository systems, text processing, ontology-based systems, text mining, multimedia data processing and advanced software engineering.  

  7. Development of hole inspection program using touch trigger probe on CNC machine tools

    International Nuclear Information System (INIS)

    Lee, Chan Ho; Lee, Eung Suk

    2012-01-01

    According to many customers' requests, optical measurement module (OMM) applications using automatic measuring devices to measure the machined part rapidly on a machine tool have increased steeply. Touch trigger probes are being used for job setup and feature inspection as automatic measuring devices, and this makes quality checking and machining compensation possible. Therefore, in this study, the use of touch trigger probes for accurate measurement of the machined part has been studied and a macro program for a hole measuring cycle has been developed. This hole is the most common feature to be measured, but conventional methods are still not free from measuring error. In addition, the eccentricity change of the least square circle was simulated according to the roundness error in a hole measurement. To evaluate the reliability of this study, the developed hole measuring program was executed to measure the hole plate on the machine and verify the roundness error in the eccentricity simulation result

  8. Study of the stiffness for predicting the accuracy of machine tools

    International Nuclear Information System (INIS)

    Ortega, N.; Campa, F.J.; Fernandez Valdivielso, A.; Alonso, U.; Olvera, D.; Compean, F.I.

    2010-01-01

    Machining processes are frequently faced with the challenge of achieving more and more precision and surface qualities. These requirements are usually attained taking into account some process variables, including the cutting parameters and the use or not of refrigerant, leaving aside the mechanical aspects associated with the influence of machine tool itself. There are many sources of error linked with machine-workpiece interaction, but, in general, we can summarize them into two types of error: quasi-static and dynamic. This paper shows the influence of quasi-static error caused by low machine rigidity on the accuracy applied on two very different processes: turning and grinding. For the study of the static stiffness of these two machines, two different methods are proposed, both of them equally valid. The first one is based on separated parameters and the second one on finite elements. (Author).

  9. Bayesian networks modeling for thermal error of numerical control machine tools

    Institute of Scientific and Technical Information of China (English)

    Xin-hua YAO; Jian-zhong FU; Zi-chen CHEN

    2008-01-01

    The interaction between the heat source location,its intensity,thermal expansion coefficient,the machine system configuration and the running environment creates complex thermal behavior of a machine tool,and also makes thermal error prediction difficult.To address this issue,a novel prediction method for machine tool thermal error based on Bayesian networks (BNs) was presented.The method described causal relationships of factors inducing thermal deformation by graph theory and estimated the thermal error by Bayesian statistical techniques.Due to the effective combination of domain knowledge and sampled data,the BN method could adapt to the change of running state of machine,and obtain satisfactory prediction accuracy.Ex-periments on spindle thermal deformation were conducted to evaluate the modeling performance.Experimental results indicate that the BN method performs far better than the least squares(LS)analysis in terms of modeling estimation accuracy.

  10. Quantitative Evaluation of Heavy Duty Machine Tools Remanufacturing Based on Modified Catastrophe Progression Method

    Science.gov (United States)

    shunhe, Li; jianhua, Rao; lin, Gui; weimin, Zhang; degang, Liu

    2017-11-01

    The result of remanufacturing evaluation is the basis for judging whether the heavy duty machine tool can remanufacture in the EOL stage of the machine tool lifecycle management.The objectivity and accuracy of evaluation is the key to the evaluation method.In this paper, the catastrophe progression method is introduced into the quantitative evaluation of heavy duty machine tools’ remanufacturing,and the results are modified by the comprehensive adjustment method,which makes the evaluation results accord with the standard of human conventional thinking.Using the catastrophe progression method to establish the heavy duty machine tools’ quantitative evaluation model,to evaluate the retired TK6916 type CNC floor milling-boring machine’s remanufacturing.The evaluation process is simple,high quantification,the result is objective.

  11. Tool feed influence on the machinability of CO(2) laser optics.

    Science.gov (United States)

    Arnold, J B; Steger, P J; Saito, T T

    1975-08-01

    Influence of tool feed on reflectivity of diamond-machined surfaces was evaluated using materials (gold, silver, and copper) from which CO(2) laser optics are primarily produced. Fifteen specimens were machined by holding all machining parameters constant, except tool feed. Tool feed was allowed to vary by controlled amounts from one evaluation zone (or part) to another. Past experience has verified that the quality of a diamond-machined surface is not a function of the cutting velocity; therefore, this experiment was conducted on the basis that a variation in cutting velocity was not an influencing factor on the diamondturning process. Inspection results of the specimens indicated that tool feeds significantly higher than 5.1 micro/rev (200 microin./rev) produced detrimental effects on the machined surfaces. In some cases, at feeds as high as 13 microm/rev (500 microin./rev), visible scoring was evident. Those surfaces produced with tool feeds less than 5.1 microm/rev had little difference in reflectivity. Measurements indicat d that their reflectivity existed in a range from 96.7% to 99.3% at 10.6 microm.

  12. Monitoring wear and corrosion in industrial machines and systems: A radiation tool

    International Nuclear Information System (INIS)

    Konstantinov, I.O.; Zatolokin, B.V.

    1994-01-01

    Industrial equipment and machines, transport systems, nuclear and conventional power plants, pipelines, and other materials is substantially influenced by degradation processes such as wear and corrosion. For safety and economic reasons, appropriately monitoring the damage could prevent dangerous accidents. When the surfaces of machine parts under investigation are not easy to reach or are concealed by overlying structures, nuclear methods have become powerful tools for examination. They include X-ray radiography, neutron radiography, and a technique known as thin layer activation (TLA)

  13. Adaption of commercial off the shelf modules for reconfigurable machine tool design

    CSIR Research Space (South Africa)

    Mpofu, K

    2008-01-01

    Full Text Available . University of Ljubljana (Slovenia) Machine Design Approach. Butala and Sluga [4] view the architecture of the machine tool as a system structure which is reflected in its configuration and which impacts the systems performance. The interfaces... process movements. This approach was also implemented in a computer aided planning system, they clarify the need of having the features to be implemented embedded in the collective drives that constitute it. This resulted in an adaption...

  14. Entheogens and Existential Intelligence: The Use of Plant Teachers as Cognitive Tools

    Science.gov (United States)

    Tupper, Kenneth W.

    2002-01-01

    In light of recent specific liberalizations in drug laws in some countries, I have investigated the potential of entheogens (i.e., psychoactive plants used as spiritual sacraments) as tools to facilitate existential intelligence. "Plant teachers" from the Americas such as ayahuasca, psilocybin mushrooms, and peyote, and the Indo-Aryan…

  15. A modern artificial intelligence Playware art tool for psychological testing of group dynamics

    DEFF Research Database (Denmark)

    Pagliarini, Luigi; Lund, Henrik Hautop

    2015-01-01

    and the psychological findings. We describe the modern artificial intelligence implementation of this instrument. Between an art piece and a psychological test, at a first cognitive analysis, it seems to be a promising research tool. In the discussion we speculate about potential industrial applications, as well....

  16. Hybrid metallic nanocomposites for extra wear-resistant diamond machining tools

    DEFF Research Database (Denmark)

    Loginov, P.A.; Sidorenko, D.A.; Levashov, E.A.

    2018-01-01

    The applicability of metallic nanocomposites as binder for diamond machining tools is demonstrated. The various nanoreinforcements (carbon nanotubes, boron nitride hBN, nanoparticles of tungsten carbide/WC) and their combinations are embedded into metallic matrices and their mechanical properties...... are determined in experiments. The wear resistance of diamond tools with metallic binders modified by various nanoreinforcements was estimated. 3D hierarchical computational finite element model of the tool binder with hybrid nanoscale reinforcements is developed, and applied for the structure...

  17. Multi-Parameter Analysis of Surface Finish in Electro-Discharge Machining of Tool Steels

    Directory of Open Access Journals (Sweden)

    Cornelia Victoria Anghel

    2006-10-01

    Full Text Available The paper presents a multi- parameter analysis of surface finish imparted to tool-steel plates by electro-discharge machining (EDM is presented. The interrelationship between surface texture parameters and process parameters is emphasized. An increased number of parameters is studied including amplitude, spacing, hybrid and fractal parameters,, as well. The correlation of these parameters with the machining conditions is investigated. Observed characteristics become more pronounced, when intensifying machining conditions. Close correlation exists between certain surface finish parameters and EDM input variables and single and multiple statistical regression models are developed.

  18. Progressive Tool Wear in Cryogenic Machining: The Effect of Liquid Nitrogen and Carbon Dioxide

    Directory of Open Access Journals (Sweden)

    Yusuf Kaynak

    2018-05-01

    Full Text Available This experimental study focuses on various cooling strategies and lubrication-assisted cooling strategies to improve machining performance in the turning process of AISI 4140 steel. Liquid nitrogen (LN2 and carbon dioxide (CO2 were used as cryogenic coolants, and their performances were compared with respect to progression of tool wear. Minimum quantity lubrication (MQL was also used with carbon dioxide. Progression of wear, including flank and nose, are the main outputs examined during experimental study. This study illustrates that carbon dioxide-assisted cryogenic machining alone and with minimum quantity lubrication does not contribute to decreasing the progression of wear within selected cutting conditions. This study also showed that carbon dioxide-assisted cryogenic machining helps to increase chip breakability. Liquid nitrogen-assisted cryogenic machining results in a reduction of tool wear, including flank and nose wear, in the machining process of AISI 4140 steel material. It was also observed that in the machining process of this material at a cutting speed of 80 m/min, built-up edges occurred in both cryogenic cooling conditions. Additionally, chip flow damage occurs in particularly dry machining.

  19. FINITE ELEMENT ANALYSIS OF CONCRETE FILLER INFLUENCE ON DYNAMIC RIGIDITY OF HEAVY MACHINE TOOL PORTAL

    Directory of Open Access Journals (Sweden)

    Yu. V. Vasilevich

    2016-01-01

    Full Text Available Virtual testing of portal machine tool has been carried out with the help of finite elements method (FEM. Static, modal and harmonic analyses have been made for a heavy planer. The paper reveals influence of concrete filler on machine tool dynamic flexibility. A peculiar feature of the simulation is concrete filling of a high-level transverse beam. Such approach oes look a typical one for machine-tool industry. Concrete has been considered as generalized material in two variants. It has been established that concrete application provides approximately 3-fold increase in machine tool rigidity per each coordinate. In this regard it is necessary to arrange closure of rigidity contour by filling all the cavities inside of the portal. Modal FEA makes it possible to determine that concrete increases comparatively weakly (1.3–1.4-fold frequencies of resonance modes. Frequency of the lowest mode rises only from 30.25 to 42.86 Hz. The following most active whole-machine eigenmodes have been revealed in the paper: “Portal pecking”, “Parallelogram” and “Traverse pecking”. In order to restrain the last mode it is necessary to carry out concrete filling of the traverse, in particular. Frequency-response characteristics and curves of dynamic rigidity for a spindle have been plotted for 0–150 Hz interval while using harmonic FEM. It has been determined that concrete increases dynamic machine tool rigidity by 2.5–3.5-fold. The effect is obtained even in the case when weakly damping concrete (2 % is used. This is due to distribution of vibrational energy flow along concrete and along cast iron as well. Thus energy density and vibration amplitudes must decrease. The paper shows acceptability for internal reinforcement of high-level machine tool parts (for example, portal traverses and fillers are applied for this purpose. Traverse weighting is compensated by additional torsional, shear and bending rigidity. The machine tool obtains the

  20. The use of machine learning and nonlinear statistical tools for ADME prediction.

    Science.gov (United States)

    Sakiyama, Yojiro

    2009-02-01

    Absorption, distribution, metabolism and excretion (ADME)-related failure of drug candidates is a major issue for the pharmaceutical industry today. Prediction of ADME by in silico tools has now become an inevitable paradigm to reduce cost and enhance efficiency in pharmaceutical research. Recently, machine learning as well as nonlinear statistical tools has been widely applied to predict routine ADME end points. To achieve accurate and reliable predictions, it would be a prerequisite to understand the concepts, mechanisms and limitations of these tools. Here, we have devised a small synthetic nonlinear data set to help understand the mechanism of machine learning by 2D-visualisation. We applied six new machine learning methods to four different data sets. The methods include Naive Bayes classifier, classification and regression tree, random forest, Gaussian process, support vector machine and k nearest neighbour. The results demonstrated that ensemble learning and kernel machine displayed greater accuracy of prediction than classical methods irrespective of the data set size. The importance of interaction with the engineering field is also addressed. The results described here provide insights into the mechanism of machine learning, which will enable appropriate usage in the future.

  1. The Impact of Business Intelligence Tools on Performance: A User Satisfaction Paradox?

    OpenAIRE

    Bernhard Wieder; Maria-Luise Ossimitz; Peter Chamoni

    2012-01-01

    While Business Intelligence (BI) initiatives have been a top-priority of CIOs around the world for several years, accounting for billions of USD of IT investments per annum (IDC), academic research on the actual benefits derived from BI tools and the drivers of these benefits remain sparse. This paper reports the findings of an exploratory, cross-sectional field study investigating the factors that define and drive benefits associated with the deployment of dedicated BI tools. BI is broadly d...

  2. The Weighted Support Vector Machine Based on Hybrid Swarm Intelligence Optimization for Icing Prediction of Transmission Line

    Directory of Open Access Journals (Sweden)

    Xiaomin Xu

    2015-01-01

    Full Text Available Not only can the icing coat on transmission line cause the electrical fault of gap discharge and icing flashover but also it will lead to the mechanical failure of tower, conductor, insulators, and others. It will bring great harm to the people’s daily life and work. Thus, accurate prediction of ice thickness has important significance for power department to control the ice disaster effectively. Based on the analysis of standard support vector machine, this paper presents a weighted support vector machine regression model based on the similarity (WSVR. According to the different importance of samples, this paper introduces the weighted support vector machine and optimizes its parameters by hybrid swarm intelligence optimization algorithm with the particle swarm and ant colony (PSO-ACO, which improves the generalization ability of the model. In the case study, the actual data of ice thickness and climate in a certain area of Hunan province have been used to predict the icing thickness of the area, which verifies the validity and applicability of this proposed method. The predicted results show that the intelligent model proposed in this paper has higher precision and stronger generalization ability.

  3. Programming Models and Tools for Intelligent Embedded Systems

    DEFF Research Database (Denmark)

    Sørensen, Peter Verner Bojsen

    Design automation and analysis tools targeting embedded platforms, developed using a component-based design approach, must be able to reason about the capabilities of the platforms. In the general case where nothing is assumed about the components comprising a platform or the platform topology...... is used for checking the consistency of a design with respect to the availablity of services and resources. In the second application, a tool for automatically implementing the communication infrastructure of a process network application, the Service Relation Model is used for analyzing the capabilities...

  4. Toward transient finite element simulation of thermal deformation of machine tools in real-time

    Science.gov (United States)

    Naumann, Andreas; Ruprecht, Daniel; Wensch, Joerg

    2018-01-01

    Finite element models without simplifying assumptions can accurately describe the spatial and temporal distribution of heat in machine tools as well as the resulting deformation. In principle, this allows to correct for displacements of the Tool Centre Point and enables high precision manufacturing. However, the computational cost of FE models and restriction to generic algorithms in commercial tools like ANSYS prevents their operational use since simulations have to run faster than real-time. For the case where heat diffusion is slow compared to machine movement, we introduce a tailored implicit-explicit multi-rate time stepping method of higher order based on spectral deferred corrections. Using the open-source FEM library DUNE, we show that fully coupled simulations of the temperature field are possible in real-time for a machine consisting of a stock sliding up and down on rails attached to a stand.

  5. Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

    Directory of Open Access Journals (Sweden)

    Yuliang Su

    2015-04-01

    Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

  6. A Method to Optimize Geometric Errors of Machine Tool based on SNR Quality Loss Function and Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Cai Ligang

    2017-01-01

    Full Text Available Instead improving the accuracy of machine tool by increasing the precision of key components level blindly in the production process, the method of combination of SNR quality loss function and machine tool geometric error correlation analysis to optimize five-axis machine tool geometric errors will be adopted. Firstly, the homogeneous transformation matrix method will be used to build five-axis machine tool geometric error modeling. Secondly, the SNR quality loss function will be used for cost modeling. And then, machine tool accuracy optimal objective function will be established based on the correlation analysis. Finally, ISIGHT combined with MATLAB will be applied to optimize each error. The results show that this method is reasonable and appropriate to relax the range of tolerance values, so as to reduce the manufacturing cost of machine tools.

  7. Analysis of optoelectronic strategic planning in Taiwan by artificial intelligence portfolio tool

    Science.gov (United States)

    Chang, Rang-Seng

    1992-05-01

    Taiwan ROC has achieved significant advances in the optoelectronic industry with some Taiwan products ranked high in the world market and technology. Six segmentations of optoelectronic were planned. Each one was divided into several strategic items, design artificial intelligent portfolio tool (AIPT) to analyze the optoelectronic strategic planning in Taiwan. The portfolio is designed to provoke strategic thinking intelligently. This computer- generated strategy should be selected and modified by the individual. Some strategies for the development of the Taiwan optoelectronic industry also are discussed in this paper.

  8. Towards a New Approach of the Economic Intelligence Process: Basic Concepts, Analysis Methods and Informational Tools

    Directory of Open Access Journals (Sweden)

    Sorin Briciu

    2009-04-01

    Full Text Available One of the obvious trends in current business environment is the increased competition. In this context, organizations are becoming more and more aware of the importance of knowledge as a key factor in obtaining competitive advantage. A possible solution in knowledge management is Economic Intelligence (EI that involves the collection, evaluation, processing, analysis, and dissemination of economic data (about products, clients, competitors, etc. inside organizations. The availability of massive quantities of data correlated with advances in information and communication technology allowing for the filtering and processing of these data provide new tools for the production of economic intelligence.The research is focused on innovative aspects of economic intelligence process (models of analysis, activities, methods and informational tools and is providing practical guidelines for initiating this process. In this paper, we try: (a to contribute to a coherent view on economic intelligence process (approaches, stages, fields of application; b to describe the most important models of analysis related to this process; c to analyze the activities, methods and tools associated with each stage of an EI process.

  9. Systematic approach to the application of automation, robotics, and machine intelligence systems (aramis) to future space projects

    Energy Technology Data Exchange (ETDEWEB)

    Smith, D B.S.

    1983-01-01

    The potential applications of automation, robotics and machine intelligence systems (ARAMIS) to space projects are investigated, through a systematic method. In this method selected space projects are broken down into space project tasks, and 69 of these tasks are selected for study. Candidate ARAMIS options are defined for each task. The relative merits of these options are evaluated according to seven indices of performance. Logical sequences of ARAMIS development are also defined. Based on this data, promising applications of ARAMIS are identified for space project tasks. General conclusions and recommendations for further study are also presented. 6 references.

  10. CRISP. Requirements Specifications of Intelligent ICT Simulation Tools for Power Applications

    Energy Technology Data Exchange (ETDEWEB)

    Warmer, C.J.; Kester, J.C.P.; Kamphuis, I.G. [ECN Energy in the Built Environment and Networks, Petten (Netherlands); Carlsson, P [EnerSearch, Malmoe (Sweden); Fontela, M. [Laboratory of Electrical Engineering LEG, Grenoble (France); Gustavsson, R. [Blekinge Institute of Technology BTH, Karlskrona (Sweden)

    2003-10-15

    This report, deliverable D2.1 in the CRISP project, serves as a preparation report for the development of simulation tools and prototype software which will be developed in forthcoming stages of the CRISP project. Application areas for these simulations are: fault detection and diagnosis, supply and demand matching and intelligent load shedding. The context in which these applications function is the power network with a high degree of distributed generation, including renewables. In order to control a so called distributed grid we can benefit from a high level of distributed control and intelligence. This requires, on top of the power system network, an information and communication network.. We argue that such a network should be seen as an enabler of distributed control and intelligence. The applications, through which control and intelligence is implemented, then form a third network layer, the service oriented network. Building upon this three-layered network model we derive in this report the requirements for a simulation tool and experiments which study new techniques for fault detection and diagnostics and for simulation tools and experiments implementing intelligent load shedding and supply and demand matching scenarios. We also look at future implementation of these services within the three-layered network model and the requirements that follow for the core information and communication network and for the service oriented network. These requirements, supported by the studies performed in the CRISP Workpackage 1, serve as a basis for development of the simulation tools in the tasks 2.2 to 2.4.

  11. CRISP. Requirements Specifications of Intelligent ICT Simulation Tools for Power Applications

    International Nuclear Information System (INIS)

    Warmer, C.J.; Kester, J.C.P.; Kamphuis, I.G.; Carlsson, P; Fontela, M.; Gustavsson, R.

    2003-10-01

    This report, deliverable D2.1 in the CRISP project, serves as a preparation report for the development of simulation tools and prototype software which will be developed in forthcoming stages of the CRISP project. Application areas for these simulations are: fault detection and diagnosis, supply and demand matching and intelligent load shedding. The context in which these applications function is the power network with a high degree of distributed generation, including renewables. In order to control a so called distributed grid we can benefit from a high level of distributed control and intelligence. This requires, on top of the power system network, an information and communication network.. We argue that such a network should be seen as an enabler of distributed control and intelligence. The applications, through which control and intelligence is implemented, then form a third network layer, the service oriented network. Building upon this three-layered network model we derive in this report the requirements for a simulation tool and experiments which study new techniques for fault detection and diagnostics and for simulation tools and experiments implementing intelligent load shedding and supply and demand matching scenarios. We also look at future implementation of these services within the three-layered network model and the requirements that follow for the core information and communication network and for the service oriented network. These requirements, supported by the studies performed in the CRISP Workpackage 1, serve as a basis for development of the simulation tools in the tasks 2.2 to 2.4

  12. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

    Directory of Open Access Journals (Sweden)

    Huu-Tho Nguyen

    Full Text Available Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process and a fuzzy COmplex PRoportional ASsessment (COPRAS for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

  13. Artificial intelligence for the EChO mission planning tool

    Science.gov (United States)

    Garcia-Piquer, Alvaro; Ribas, Ignasi; Colomé, Josep

    2015-12-01

    The Exoplanet Characterisation Observatory (EChO) has as its main goal the measurement of atmospheres of transiting planets. This requires the observation of two types of events: primary and secondary eclipses. In order to yield measurements of sufficient Signal-to-Noise Ratio to fulfil the mission objectives, the events of each exoplanet have to be observed several times. In addition, several criteria have to be considered to carry out each observation, such as the exoplanet visibility, its event duration, and no overlapping with other tasks. It is expected that a suitable mission plan increases the efficiency of telescope operation, which will represent an important benefit in terms of scientific return and operational costs. Nevertheless, to obtain a long term mission plan becomes unaffordable for human planners due to the complexity of computing the huge number of possible combinations for finding an optimum solution. In this contribution we present a long term mission planning tool based on Genetic Algorithms, which are focused on solving optimization problems such as the planning of several tasks. Specifically, the proposed tool finds a solution that highly optimizes the defined objectives, which are based on the maximization of the time spent on scientific observations and the scientific return (e.g., the coverage of the mission survey). The results obtained on the large experimental set up support that the proposed scheduler technology is robust and can function in a variety of scenarios, offering a competitive performance which does not depend on the collection of exoplanets to be observed. Specifically, the results show that, with the proposed tool, EChO uses 94% of the available time of the mission, so the amount of downtime is small, and it completes 98% of the targets.

  14. Visual intelligence Microsoft tools and techniques for visualizing data

    CERN Document Server

    Stacey, Mark; Jorgensen, Adam

    2013-01-01

    Go beyond design concepts and learn to build state-of-the-art visualizations The visualization experts at Microsoft's Pragmatic Works have created a full-color, step-by-step guide to building specific types of visualizations. The book thoroughly covers the Microsoft toolset for data analysis and visualization, including Excel, and explores best practices for choosing a data visualization design, selecting tools from the Microsoft stack, and building a dynamic data visualization from start to finish. You'll examine different types of visualizations, their strengths and weaknesses, a

  15. Efficient thermal error prediction in a machine tool using finite element analysis

    International Nuclear Information System (INIS)

    Mian, Naeem S; Fletcher, Simon; Longstaff, Andrew P; Myers, Alan

    2011-01-01

    Thermally induced errors have a major significance on the positional accuracy of a machine tool. Heat generated during the machining process produces thermal gradients that flow through the machine structure causing linear and nonlinear thermal expansions and distortions of associated complex discrete structures, producing deformations that adversely affect structural stability. The heat passes through structural linkages and mechanical joints where interfacial parameters such as the roughness and form of the contacting surfaces affect the thermal resistance and thus the heat transfer coefficients. This paper presents a novel offline technique using finite element analysis (FEA) to simulate the effects of the major internal heat sources such as bearings, motors and belt drives of a small vertical milling machine (VMC) and the effects of ambient temperature pockets that build up during the machine operation. Simplified models of the machine have been created offline using FEA software and evaluated experimental results applied for offline thermal behaviour simulation of the full machine structure. The FEA simulated results are in close agreement with the experimental results ranging from 65% to 90% for a variety of testing regimes and revealed a maximum error range of 70 µm reduced to less than 10 µm

  16. Principles and tools for collaborative entity-based intelligence analysis.

    Science.gov (United States)

    Bier, Eric A; Card, Stuart K; Bodnar, John W

    2010-01-01

    Software tools that make it easier for analysts to collaborate as a natural part of their work will lead to better analysis that is informed by more perspectives. We are interested to know if software tools can be designed that support collaboration even as they allow analysts to find documents and organize information (including evidence, schemas, and hypotheses). We have modified the Entity Workspace system, described previously, to test such designs. We have evaluated the resulting design in both a laboratory study and a study where it is situated with an analysis team. In both cases, effects on collaboration appear to be positive. Key aspects of the design include an evidence notebook optimized for organizing entities (rather than text characters), information structures that can be collapsed and expanded, visualization of evidence that emphasizes events and documents (rather than emphasizing the entity graph), and a notification system that finds entities of mutual interest to multiple analysts. Long-term tests suggest that this approach can support both top-down and bottom-up styles of analysis.

  17. Miniaturized multiwavelength digital holography sensor for extensive in-machine tool measurement

    Science.gov (United States)

    Seyler, Tobias; Fratz, Markus; Beckmann, Tobias; Bertz, Alexander; Carl, Daniel

    2017-06-01

    In this paper we present a miniaturized digital holographic sensor (HoloCut) for operation inside a machine tool. With state-of-the-art 3D measurement systems, short-range structures such as tool marks cannot be resolved inside a machine tool chamber. Up to now, measurements had to be conducted outside the machine tool and thus processing data are generated offline. The sensor presented here uses digital multiwavelength holography to get 3D-shape-information of the machined sample. By using three wavelengths, we get a large artificial wavelength with a large unambiguous measurement range of 0.5mm and achieve micron repeatability even in the presence of laser speckles on rough surfaces. In addition, a digital refocusing algorithm based on phase noise is implemented to extend the measurement range beyond the limits of the artificial wavelength and geometrical depth-of-focus. With complex wave field propagation, the focus plane can be shifted after the camera images have been taken and a sharp image with extended depth of focus is constructed consequently. With 20mm x 20mm field of view the sensor enables measurement of both macro- and micro-structure (such as tool marks) with an axial resolution of 1 µm, lateral resolution of 7 µm and consequently allows processing data to be generated online which in turn qualifies it as a machine tool control. To make HoloCut compact enough for operation inside a machining center, the beams are arranged in two planes: The beams are split into reference beam and object beam in the bottom plane and combined onto the camera in the top plane later on. Using a mechanical standard interface according to DIN 69893 and having a very compact size of 235mm x 140mm x 215mm (WxHxD) and a weight of 7.5 kg, HoloCut can be easily integrated into different machine tools and extends no more in height than a typical processing tool.

  18. Investigation into the accuracy of a proposed laser diode based multilateration machine tool calibration system

    International Nuclear Information System (INIS)

    Fletcher, S; Longstaff, A P; Myers, A

    2005-01-01

    Geometric and thermal calibration of CNC machine tools is required in modern machine shops with volumetric accuracy assessment becoming the standard machine tool qualification in many industries. Laser interferometry is a popular method of measuring the errors but this, and other alternatives, tend to be expensive, time consuming or both. This paper investigates the feasibility of using a laser diode based system that capitalises on the low cost nature of the diode to provide multiple laser sources for fast error measurement using multilateration. Laser diode module technology enables improved wavelength stability and spectral linewidth which are important factors for laser interferometry. With more than three laser sources, the set-up process can be greatly simplified while providing flexibility in the location of the laser sources improving the accuracy of the system

  19. A Tool for Assessing the Text Legibility of Digital Human Machine Interfaces

    Energy Technology Data Exchange (ETDEWEB)

    Roger Lew; Ronald L. Boring; Thomas A. Ulrich

    2015-08-01

    A tool intended to aid qualified professionals in the assessment of the legibility of text presented on a digital display is described. The assessment of legibility is primarily for the purposes of designing and analyzing human machine interfaces in accordance with NUREG-0700 and MIL-STD 1472G. The tool addresses shortcomings of existing guidelines by providing more accurate metrics of text legibility with greater sensitivity to design alternatives.

  20. Influence of Workpiece Material on Tool Wear Performance and Tribofilm Formation in Machining Hardened Steel

    Directory of Open Access Journals (Sweden)

    Junfeng Yuan

    2016-04-01

    Full Text Available In addition to the bulk properties of a workpiece material, characteristics of the tribofilms formed as a result of workpiece material mass transfer to the friction surface play a significant role in friction control. This is especially true in cutting of hardened materials, where it is very difficult to use liquid based lubricants. To better understand wear performance and the formation of beneficial tribofilms, this study presents an assessment of uncoated mixed alumina ceramic tools (Al2O3+TiC in the turning of two grades of steel, AISI T1 and AISI D2. Both workpiece materials were hardened to 59 HRC then machined under identical cutting conditions. Comprehensive characterization of the resulting wear patterns and the tribofilms formed at the tool/workpiece interface were made using X-ray Photoelectron Spectroscopy and Scanning Electron Microscopy. Metallographic studies on the workpiece material were performed before the machining process and the surface integrity of the machined part was investigated after machining. Tool life was 23% higher when turning D2 than T1. This improvement in cutting tool life and wear behaviour was attributed to a difference in: (1 tribofilm generation on the friction surface and (2 the amount and distribution of carbide phases in the workpiece materials. The results show that wear performance depends both on properties of the workpiece material and characteristics of the tribofilms formed on the friction surface.

  1. Manufacturing process applications team (MATEAM). [technology transfer in the areas of machine tools and robots

    Science.gov (United States)

    1979-01-01

    The transfer of NASA technology to the industrial sector is reported. Presentations to the machine tool and robot industries and direct technology transfers of the Adams Manipulator arm, a-c motor control, and the bolt tension monitor are discussed. A listing of proposed RTOP programs with strong potential is included. A detailed description of the rotor technology available to industry is given.

  2. Research on Key Technologies of Unit-Based CNC Machine Tool Assembly Design

    Directory of Open Access Journals (Sweden)

    Zhongqi Sheng

    2014-01-01

    Full Text Available Assembly is the part that produces the maximum workload and consumed time during product design and manufacturing process. CNC machine tool is the key basic equipment in manufacturing industry and research on assembly design technologies of CNC machine tool has theoretical significance and practical value. This study established a simplified ASRG for CNC machine tool. The connection between parts, semantic information of transmission, and geometric constraint information were quantified to assembly connection strength to depict the assembling difficulty level. The transmissibility based on trust relationship was applied on the assembly connection strength. Assembly unit partition based on assembly connection strength was conducted, and interferential assembly units were identified and revised. The assembly sequence planning and optimization of parts in each assembly unit and between assembly units was conducted using genetic algorithm. With certain type of high speed CNC turning center, as an example, this paper explored into the assembly modeling, assembly unit partition, and assembly sequence planning and optimization and realized the optimized assembly sequence of headstock of CNC machine tool.

  3. a design to digitalize hydraulic cylinder control of a machine tool

    African Journals Online (AJOL)

    Dr Obe

    1995-09-01

    Sep 1, 1995 ... Department of Mechanical Engineering. FEDERAL UNIVERSITY OF TECHNOLOGY, OWERRI,. P.M.B. 1526, OWERRI. ABSTRACT. Conventionally hydraulic piston - cylinder servos are actuated using analogue controls for machine tool axis drives. In this paper a design of the axis control system of an NC ...

  4. 76 FR 5832 - International Business Machines (IBM), Software Group Business Unit, Optim Data Studio Tools QA...

    Science.gov (United States)

    2011-02-02

    ... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-74,554] International Business Machines (IBM), Software Group Business Unit, Optim Data Studio Tools QA, San Jose, CA; Notice of Affirmative Determination Regarding Application for Reconsideration By application dated November 29, 2010, a worker and a state workforce official...

  5. Technology and Jobs: Computer-Aided Design. Numerical-Control Machine-Tool Operators. Office Automation.

    Science.gov (United States)

    Stanton, Michael; And Others

    1985-01-01

    Three reports on the effects of high technology on the nature of work include (1) Stanton on applications and implications of computer-aided design for engineers, drafters, and architects; (2) Nardone on the outlook and training of numerical-control machine tool operators; and (3) Austin and Drake on the future of clerical occupations in automated…

  6. The intelligent clinical laboratory as a tool to increase cancer care management productivity.

    Science.gov (United States)

    Mohammadzadeh, Niloofar; Safdari, Reza

    2014-01-01

    Studies of the causes of cancer, early detection, prevention or treatment need accurate, comprehensive, and timely cancer data. The clinical laboratory provides important cancer information needed for physicians which influence clinical decisions regarding treatment, diagnosis and patient monitoring. Poor communication between health care providers and clinical laboratory personnel can lead to medical errors and wrong decisions in providing cancer care. Because of the key impact of laboratory information on cancer diagnosis and treatment the quality of the tests, lab reports, and appropriate lab management are very important. A laboratory information management system (LIMS) can have an important role in diagnosis, fast and effective access to cancer data, decrease redundancy and costs, and facilitate the integration and collection of data from different types of instruments and systems. In spite of significant advantages LIMS is limited by factors such as problems in adaption to new instruments that may change existing work processes. Applications of intelligent software simultaneously with existing information systems, in addition to remove these restrictions, have important benefits including adding additional non-laboratory-generated information to the reports, facilitating decision making, and improving quality and productivity of cancer care services. Laboratory systems must have flexibility to change and have the capability to develop and benefit from intelligent devices. Intelligent laboratory information management systems need to benefit from informatics tools and latest technologies like open sources. The aim of this commentary is to survey application, opportunities and necessity of intelligent clinical laboratory as a tool to increase cancer care management productivity.

  7. Supervised-machine Learning for Intelligent Collision Avoidance Decision-making and Sensor Tasking

    Data.gov (United States)

    National Aeronautics and Space Administration — Building an autonomous architecture that uses directed self-learning neuro-fuzzy networks with the aim of developing an intelligent autonomous collision avoidance...

  8. FEM-DEM coupling simulations of the tool wear characteristics in prestressed machining superalloy

    Directory of Open Access Journals (Sweden)

    Ruitao Peng

    2016-01-01

    Full Text Available Due to the complicated contact loading at the tool-chip interface, ceramic tool wear in prestressed machining superalloy is rare difficult to evaluate only by experimental approaches. This study aims to develop a methodology to predict the tool wear evolution by using combined FEM and DEM numerical simulations. Firstly, a finite element model for prestressed cutting is established, subsequently a discrete element model to describe the tool-chip behaviour is established based on the obtained boundary conditions by FEM simulations, finally, simulated results are experimentally validated. The predicted tool wear results show nice agreement with experiments, the simulation indicates that, within a certain range, higher cutting speed effectively results in slighter wear of Sialon ceramic tools, and deeper depth of cut leads to more serious tool wear.

  9. Investigation of tool engagement and cutting performance in machining a pocket

    Science.gov (United States)

    Adesta, E. Y. T.; Hamidon, R.; Riza, M.; Alrashidi, R. F. F. A.; Alazemi, A. F. F. S.

    2018-01-01

    This study investigates the variation of tool engagement for different profile of cutting. In addition, behavior of cutting force and cutting temperature for different tool engagements for machining a pocket also been explored. Initially, simple tool engagement models were developed for peripheral and slot cutting for different types of corner. Based on these models, the tool engagements for contour and zig zag tool path strategies for a rectangular shape pocket with dimension 80 mm x 60 mm were analyzed. Experiments were conducted to investigate the effect of tool engagements on cutting force and cutting temperature for the machining of a pocket of AISI H13 material. The cutting parameters used were 150m/min cutting speed, 0.05mm/tooth feed, and 0.1mm depth of cut. Based on the results obtained, the changes of cutting force and cutting temperature performance there exist a relationship between cutting force, cutting temperature and tool engagement. A higher cutting force and cutting temperature is obtained when the cutting tool goes through up milling and when the cutting tool makes a full engagement with the workpiece.

  10. Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?

    Science.gov (United States)

    Bini, Stefano A

    2018-02-27

    This article was presented at the 2017 annual meeting of the American Association of Hip and Knee Surgeons to introduce the members gathered as the audience to the concepts behind artificial intelligence (AI) and the applications that AI can have in the world of health care today. We discuss the origin of AI, progress to machine learning, and then discuss how the limits of machine learning lead data scientists to develop artificial neural networks and deep learning algorithms through biomimicry. We will place all these technologies in the context of practical clinical examples and show how AI can act as a tool to support and amplify human cognitive functions for physicians delivering care to increasingly complex patients. The aim of this article is to provide the reader with a basic understanding of the fundamentals of AI. Its purpose is to demystify this technology for practicing surgeons so they can better understand how and where to apply it. Copyright © 2018 Elsevier Inc. All rights reserved.

  11. An artificial intelligence tool for complex age-depth models

    Science.gov (United States)

    Bradley, E.; Anderson, K. A.; de Vesine, L. R.; Lai, V.; Thomas, M.; Nelson, T. H.; Weiss, I.; White, J. W. C.

    2017-12-01

    CSciBox is an integrated software system for age modeling of paleoenvironmental records. It incorporates an array of data-processing and visualization facilities, ranging from 14C calibrations to sophisticated interpolation tools. Using CSciBox's GUI, a scientist can build custom analysis pipelines by composing these built-in components or adding new ones. Alternatively, she can employ CSciBox's automated reasoning engine, Hobbes, which uses AI techniques to perform an in-depth, autonomous exploration of the space of possible age-depth models and presents the results—both the models and the reasoning that was used in constructing and evaluating them—to the user for her inspection. Hobbes accomplishes this using a rulebase that captures the knowledge of expert geoscientists, which was collected over the course of more than 100 hours of interviews. It works by using these rules to generate arguments for and against different age-depth model choices for a given core. Given a marine-sediment record containing uncalibrated 14C dates, for instance, Hobbes tries CALIB-style calibrations using a choice of IntCal curves, with reservoir age correction values chosen from the 14CHRONO database using the lat/long information provided with the core, and finally composes the resulting age points into a full age model using different interpolation methods. It evaluates each model—e.g., looking for outliers or reversals—and uses that information to guide the next steps of its exploration, and presents the results to the user in human-readable form. The most powerful of CSciBox's built-in interpolation methods is BACON, a Bayesian sedimentation-rate algorithm—a powerful but complex tool that can be difficult to use. Hobbes adjusts BACON's many parameters autonomously to match the age model to the expectations of expert geoscientists, as captured in its rulebase. It then checks the model against the data and iteratively re-calculates until it is a good fit to the data.

  12. Effect of changing polarity of graphite tool/ Hadfield steel workpiece couple on machining performances in die sinking EDM

    Directory of Open Access Journals (Sweden)

    Özerkan Haci Bekir

    2017-01-01

    Full Text Available In this study, machining performance ouput parameters such as machined surface roughness (SR, material removal rate (MRR, tool wear rate (TWR, were experimentally examined and analyzed with the diversifying and changing machining parameters in (EDM. The processing parameters (input par. of this research are stated as tool material, peak current (I, pulse duration (ton and pulse interval (toff. The experimental machinings were put into practice by using Hadfield steel workpiece (prismatic and cylindrical graphite electrodes with kerosene dielectric at different machining current, polarity and pulse time settings. The experiments have shown that the type of tool material, polarity (direct polarity forms higher MRR, SR and TWR, current (high current lowers TWR and enhances MRR, TWR and pulse on time (ton=48□s is critical threshold value for MRR and TWR were influential on machining performance in electrical discharge machining.

  13. Open source intelligence: A tool to combat illicit trafficking

    Energy Technology Data Exchange (ETDEWEB)

    Sjoeberg, J [Swedish Armed Forces HQ, Stockholm (Sweden)

    2001-10-01

    The purpose of my presentation is to provide some thoughts on Open Sources and how Open Sources can be used as tools for detecting illicit trafficking and proliferation. To fulfill this purpose I would like to deal with the following points during my presentation: What is Open Source? How can it be defined? - Different sources - Methods. Open Source information can be defined as publicly available information as well as other unclassified information that has limited public distribution or access to it. It comes in print, electronic or oral form. It can be found distributed either to the mass public by print or electronic media or to a much more limited customer base like companies, experts or specialists of some kind including the so called gray literature. Open Source information is not a single source but a multi-source. Thus, you can say that Open Sources does not say anything about the information itself, it only refers to if the information is classified or not.

  14. Open source intelligence: A tool to combat illicit trafficking

    International Nuclear Information System (INIS)

    Sjoeberg, J.

    2001-01-01

    The purpose of my presentation is to provide some thoughts on Open Sources and how Open Sources can be used as tools for detecting illicit trafficking and proliferation. To fulfill this purpose I would like to deal with the following points during my presentation: What is Open Source? How can it be defined? - Different sources - Methods. Open Source information can be defined as publicly available information as well as other unclassified information that has limited public distribution or access to it. It comes in print, electronic or oral form. It can be found distributed either to the mass public by print or electronic media or to a much more limited customer base like companies, experts or specialists of some kind including the so called gray literature. Open Source information is not a single source but a multi-source. Thus, you can say that Open Sources does not say anything about the information itself, it only refers to if the information is classified or not

  15. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  16. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  17. Intelligent Electric Power Systems with Active-Adaptive Electric Networks: Challenges for Simulation Tools

    Directory of Open Access Journals (Sweden)

    Ufa Ruslan A.

    2015-01-01

    Full Text Available The motivation of the presented research is based on the needs for development of new methods and tools for adequate simulation of intelligent electric power systems with active-adaptive electric networks (IES including Flexible Alternating Current Transmission System (FACTS devices. The key requirements for the simulation were formed. The presented analysis of simulation results of IES confirms the need to use a hybrid modelling approach.

  18. Precise gouging-free tool orientations for 5-axis CNC machining

    KAUST Repository

    Kim, Yong-Joon

    2014-08-19

    We present a precise approach to the generation of optimized collision-free and gouging-free tool paths for 5-axis CNC machining of freeform NURBS surfaces using flat-end and rounded-end (bull nose) tools having cylindrical shank. To achieve high approximation quality, we employ analysis of hyper-osculating circles (HOCs) (Wang et al., 1993a,b), that have third order contact with the target surface, and lead to a locally collision-free configuration between the tool and the target surface. At locations where an HOC is not possible, we aim at a double tangential contact among the tool and the target surface, and use it as a bridge between the feasible HOC tool paths. We formulate all such possible two-contact configurations as systems of algebraic constraints and solve them. For all feasible HOCs and two-contact configurations, we perform a global optimization to find the tool path that maximizes the approximation quality of the machining, while being gouge-free and possibly satisfying constraints on the tool tilt and the tool acceleration. We demonstrate the effectiveness of our approach via several experimental results.

  19. Precise gouging-free tool orientations for 5-axis CNC machining

    KAUST Repository

    Kim, Yong-Joon; Elber, Gershon; Barton, Michael; Pottmann, Helmut

    2014-01-01

    We present a precise approach to the generation of optimized collision-free and gouging-free tool paths for 5-axis CNC machining of freeform NURBS surfaces using flat-end and rounded-end (bull nose) tools having cylindrical shank. To achieve high approximation quality, we employ analysis of hyper-osculating circles (HOCs) (Wang et al., 1993a,b), that have third order contact with the target surface, and lead to a locally collision-free configuration between the tool and the target surface. At locations where an HOC is not possible, we aim at a double tangential contact among the tool and the target surface, and use it as a bridge between the feasible HOC tool paths. We formulate all such possible two-contact configurations as systems of algebraic constraints and solve them. For all feasible HOCs and two-contact configurations, we perform a global optimization to find the tool path that maximizes the approximation quality of the machining, while being gouge-free and possibly satisfying constraints on the tool tilt and the tool acceleration. We demonstrate the effectiveness of our approach via several experimental results.

  20. A cloud platform for remote diagnosis of breast cancer in mammography by fusion of machine and human intelligence

    Science.gov (United States)

    Jiang, Guodong; Fan, Ming; Li, Lihua

    2016-03-01

    Mammography is the gold standard for breast cancer screening, reducing mortality by about 30%. The application of a computer-aided detection (CAD) system to assist a single radiologist is important to further improve mammographic sensitivity for breast cancer detection. In this study, a design and realization of the prototype for remote diagnosis system in mammography based on cloud platform were proposed. To build this system, technologies were utilized including medical image information construction, cloud infrastructure and human-machine diagnosis model. Specifically, on one hand, web platform for remote diagnosis was established by J2EE web technology. Moreover, background design was realized through Hadoop open-source framework. On the other hand, storage system was built up with Hadoop distributed file system (HDFS) technology which enables users to easily develop and run on massive data application, and give full play to the advantages of cloud computing which is characterized by high efficiency, scalability and low cost. In addition, the CAD system was realized through MapReduce frame. The diagnosis module in this system implemented the algorithms of fusion of machine and human intelligence. Specifically, we combined results of diagnoses from doctors' experience and traditional CAD by using the man-machine intelligent fusion model based on Alpha-Integration and multi-agent algorithm. Finally, the applications on different levels of this system in the platform were also discussed. This diagnosis system will have great importance for the balanced health resource, lower medical expense and improvement of accuracy of diagnosis in basic medical institutes.

  1. Appendix to rationally designing of machine tools for example of universal lathe

    Directory of Open Access Journals (Sweden)

    Pejović Branko B.

    2015-01-01

    Full Text Available In this paper, for the universal machine tool for turning and function of the thrust of the cutting speed for blasting area efficiency and stability of the tool and sectional filings. These dependencies were used to determine the main characteristics of the optimal and maximum operating power equipment. Based on this, an analysis of the increase in operating power equipment typical cases in order to adapt to the new needs of exploitation properties and improve productivity. Using the previous analysis, it was determined the best solution in terms of the rational design of machines, by ensuring the simultaneous use of the main features on the basis of increase in speed with the use of tools and higher stability. In order to better display problems, an analysis of the appropriate diagrams P-V and V-D. On a typical example of the manufacturing practice at the end of the work, we demonstrate improvement of exploitation characteristics of a universal machine through appropriate calculations in terms of new needs adjustment feature, where it is expected that the reconstruction of the smallest machines.

  2. Statistical investigations into the erosion of material from the tool in micro-electrical discharge machining

    DEFF Research Database (Denmark)

    Puthumana, Govindan

    2018-01-01

    This paper presents a statistical study of the erosion of material from the tool electrode in a micro-electrical discharge machining process. The work involves analysis of variance and analysis of means approaches on the results of the tool electrode wear rate obtained based on design...... current (Id) and discharge frequency (fd) control the erosion of material from the tool electrode. The material erosion from the tool electrode (Me) increases linearly with the discharge frequency. As the current index increases from 20 to 35, the Me decreases linearly by 29%, and then increases by of 36......%. The current index of 35 gives the minimum material erosion from the tool. It is observed that none of the two-factor interactions are significant in controlling the erosion of the material from the tool....

  3. Development of effective tool for iterative design of human machine interfaces in nuclear power plant

    International Nuclear Information System (INIS)

    Nakagawa, Takashi; Matsuo, Satoko; Yoshikawa, Hidekazu; Wu, Wei; Kameda, Akiyuki; Fumizawa, Motoo

    2000-01-01

    The authors have developed SEAMAID, which is a Simulation-based Evaluation and Analysis support system for MAn-machine Interface Design (SEAMAID) in the domain of nuclear power plants. The SEAMAID simulated the interaction between an operator and human machine interfaces (HMI), and supports to evaluate the HMI by using the simulation results. In this paper, a case study of evaluation for conventional center control room design was conducted. The authors were confirmed that SEAMAID is a useful tool for improvements of HMI design (J.P.N.)

  4. Study on effect of tool electrodes on surface finish during electrical discharge machining of Nitinol

    Science.gov (United States)

    Sahu, Anshuman Kumar; Chatterjee, Suman; Nayak, Praveen Kumar; Sankar Mahapatra, Siba

    2018-03-01

    Electrical discharge machining (EDM) is a non-traditional machining process which is widely used in machining of difficult-to-machine materials. EDM process can produce complex and intrinsic shaped component made of difficult-to-machine materials, largely applied in aerospace, biomedical, die and mold making industries. To meet the required applications, the EDMed components need to possess high accuracy and excellent surface finish. In this work, EDM process is performed using Nitinol as work piece material and AlSiMg prepared by selective laser sintering (SLS) as tool electrode along with conventional copper and graphite electrodes. The SLS is a rapid prototyping (RP) method to produce complex metallic parts by additive manufacturing (AM) process. Experiments have been carried out varying different process parameters like open circuit voltage (V), discharge current (Ip), duty cycle (τ), pulse-on-time (Ton) and tool material. The surface roughness parameter like average roughness (Ra), maximum height of the profile (Rt) and average height of the profile (Rz) are measured using surface roughness measuring instrument (Talysurf). To reduce the number of experiments, design of experiment (DOE) approach like Taguchi’s L27 orthogonal array has been chosen. The surface properties of the EDM specimen are optimized by desirability function approach and the best parametric setting is reported for the EDM process. Type of tool happens to be the most significant parameter followed by interaction of tool type and duty cycle, duty cycle, discharge current and voltage. Better surface finish of EDMed specimen can be obtained with low value of voltage (V), discharge current (Ip), duty cycle (τ) and pulse on time (Ton) along with the use of AlSiMg RP electrode.

  5. Obtaining Global Picture From Single Point Observations by Combining Data Assimilation and Machine Learning Tools

    Science.gov (United States)

    Shprits, Y.; Zhelavskaya, I. S.; Kellerman, A. C.; Spasojevic, M.; Kondrashov, D. A.; Ghil, M.; Aseev, N.; Castillo Tibocha, A. M.; Cervantes Villa, J. S.; Kletzing, C.; Kurth, W. S.

    2017-12-01

    Increasing volume of satellite measurements requires deployment of new tools that can utilize such vast amount of data. Satellite measurements are usually limited to a single location in space, which complicates the data analysis geared towards reproducing the global state of the space environment. In this study we show how measurements can be combined by means of data assimilation and how machine learning can help analyze large amounts of data and can help develop global models that are trained on single point measurement. Data Assimilation: Manual analysis of the satellite measurements is a challenging task, while automated analysis is complicated by the fact that measurements are given at various locations in space, have different instrumental errors, and often vary by orders of magnitude. We show results of the long term reanalysis of radiation belt measurements along with fully operational real-time predictions using data assimilative VERB code. Machine Learning: We present application of the machine learning tools for the analysis of NASA Van Allen Probes upper-hybrid frequency measurements. Using the obtained data set we train a new global predictive neural network. The results for the Van Allen Probes based neural network are compared with historical IMAGE satellite observations. We also show examples of predictions of geomagnetic indices using neural networks. Combination of machine learning and data assimilation: We discuss how data assimilation tools and machine learning tools can be combine so that physics-based insight into the dynamics of the particular system can be combined with empirical knowledge of it's non-linear behavior.

  6. A robust hybrid model integrating enhanced inputs based extreme learning machine with PLSR (PLSR-EIELM) and its application to intelligent measurement.

    Science.gov (United States)

    He, Yan-Lin; Geng, Zhi-Qiang; Xu, Yuan; Zhu, Qun-Xiong

    2015-09-01

    In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons and the over-fitting phenomenon. First, a traditional extreme learning machine (ELM) is selected. Second, a method of randomly assigning is applied to the weights between the input layer and the hidden layer, and then the nonlinear transformation for independent variables can be obtained from the output of the hidden layer neurons. Especially, the original input variables are regarded as enhanced inputs; then the enhanced inputs and the nonlinear transformed variables are tied together as the whole independent variables. In this way, the PLSR can be carried out to identify the PLS components not only from the nonlinear transformed variables but also from the original input variables, which can remove the correlation among the whole independent variables and the expected outputs. Finally, the optimal relationship model of the whole independent variables with the expected outputs can be achieved by using PLSR. Thus, the PLSR-EIELM model is developed. Then the PLSR-EIELM model served as an intelligent measurement tool for the key variables of the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. The experimental results show that the predictive accuracy of PLSR-EIELM is stable, which indicate that PLSR-EIELM has good robust character. Moreover, compared with ELM, PLSR, hierarchical ELM (HELM), and PLSR-ELM, PLSR-EIELM can achieve much smaller predicted relative errors in these two applications. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

    Science.gov (United States)

    Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

    2016-06-01

    With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

  8. Proceedings of the Workshop on software tools for distributed intelligent control systems

    Energy Technology Data Exchange (ETDEWEB)

    Herget, C.J. (ed.)

    1990-09-01

    The Workshop on Software Tools for Distributed Intelligent Control Systems was organized by Lawrence Livermore National Laboratory for the United States Army Headquarters Training and Doctrine Command and the Defense Advanced Research Projects Agency. The goals of the workshop were to the identify the current state of the art in tools which support control systems engineering design and implementation, identify research issues associated with writing software tools which would provide a design environment to assist engineers in multidisciplinary control design and implementation, formulate a potential investment strategy to resolve the research issues and develop public domain code which can form the core of more powerful engineering design tools, and recommend test cases to focus the software development process and test associated performance metrics. Recognizing that the development of software tools for distributed intelligent control systems will require a multidisciplinary effort, experts in systems engineering, control systems engineering, and compute science were invited to participate in the workshop. In particular, experts who could address the following topics were selected: operating systems, engineering data representation and manipulation, emerging standards for manufacturing data, mathematical foundations, coupling of symbolic and numerical computation, user interface, system identification, system representation at different levels of abstraction, system specification, system design, verification and validation, automatic code generation, and integration of modular, reusable code.

  9. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  10. Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine

    Directory of Open Access Journals (Sweden)

    F. Khammar

    2016-01-01

    Full Text Available The induction machine is experiencing a growing success for two decades by gradually replacing the DC machines and synchronous in many industrial applications. This paper is devoted to the study of advanced methods applied to the command of the asynchronous machine in order to obtain a system of control of high performance. While the criteria for response time, overtaking, and static error can be assured by the techniques of conventional control, the criterion of robustness remains a challenge for researchers. This criterion can be satisfied only by applying advanced techniques of command. After mathematical modeling of the asynchronous machine, it defines the control strategies based on the orientation of the rotor flux. The results of the different simulation tests highlight the properties of robustness of algorithms proposed and suggested to compare the different control strategies.

  11. Delay dynamical systems and applications to nonlinear machine-tool chatter

    International Nuclear Information System (INIS)

    Fofana, M.S.

    2003-01-01

    The stability behaviour of machine chatter that exhibits Hopf and degenerate bifurcations has been examined without the assumption of small delays between successive cuts. Delay dynamical system theory leading to the reduction of the infinite-dimensional character of the governing delay differential equations (DDEs) to a finite-dimensional set of ordinary differential equations have been employed. The essential mathematical arguments for these systems in the context of retarded DDEs are summarized. Then the application of these arguments in the stability study of machine-tool chatter with multiple time delays is presented. Explicit analytical expressions ensuring stable and unstable machining when perturbations are periodic, stochastic and nonlinear have been derived using the integral averaging method and Lyapunov exponents

  12. MECHANISMS OF CUTTING BLADE WEAR AND THEIR INFLUENCE ON CUTTING ABILITY OF THE TOOL DURING MACHINING OF SPECIAL ALLOYS

    Directory of Open Access Journals (Sweden)

    Tomáš Zlámal

    2016-09-01

    Full Text Available With increased requirements for quality and shelf life of machined parts there is also a higher share of the use of material with specific properties that are identified by the term “superalloys”. These materials differ from common steels by mechanical and physical properties that cause their worse machinability. During machining of “superalloys” worse machinability has negative influence primarily on the amount of cutting edge wear, which shortens durability of the cutting tool. The goal of experimental activity shown in this contribution is to determine individual mechanisms of the cutting edge wear and their effects on the cutting ability during high speed machining of nickel superalloy. A specific exchangeable cutting insert made from cubic boric nitride was used for machining of the 625 material according to ASM 5666F. The criteria to evaluate cutting ability and durability of the cutting tool became selected parameters of surface integrity and quality of the machined surface.

  13. Design and Analysis of a Collision Detector for Hybrid Robotic Machine Tools

    Directory of Open Access Journals (Sweden)

    Dan ZHANG

    2015-10-01

    Full Text Available Capacitive sensing depends on the physical parameter changing either the spacing between the two plates or the dielectric constant. Based on this idea, a capacitive based collision detection sensor is proposed and designed in this paper for the purpose of detecting any collision between the end effector and peripheral equipment (e.g., fixture for the three degrees of freedom hybrid robotic machine tools when it is in operation. One side of the finger-like capacitor is attached to the moving platform of the hybrid robotic manipulator and the other side of the finger-like capacitor is attached to the tool. When the tool accidently hits the peripheral equipment, the vibration will make the distance of the capacitor change and therefore trigger the machine to stop. The new design is illustrated and modelled. The capacitance, sensitivity and frequency response of the detector are analyzed in detail, and finally, the fabrication process is presented. The proposed collision detector can also be applied to other machine tools.

  14. Machinability of Stainless Tool Steel using Nitrogen Oil-Mist coalant

    Directory of Open Access Journals (Sweden)

    Amad E. Elshwain

    2017-01-01

    Full Text Available For all dry machining process, temperature generated in the cutting zone is the major challenge. It causes tool failure and results in unsatisfactory surface finish. Application of flood coolant method during machining processes can significantly reduce the temperature and consequently extend the cutting tool life. However, it has serious concerns regarding environmental pollution, operator health and manufacturing cost. These issues are usually attempts to be overcame by using minimum quantity lubrication (MQL technique. This method merges the advantages of both dry cutting and flood cooling by spraying a small amount of lubricant to the cutting zone using vegetable oil. In this paper, another technique is proposed in order to further enhance the machineability of the stainless tool steel (STAVAX ESR 48 HRC. This involves using of nitrogen gas (N2 and air as cooling medium in combination with oil mist lubricant (MQL. The results show that the combination between nitrogen and oil-mist lubricant much more prolonged the tool life and improved the surface finish than the air-oil mist lubricant medium.

  15. CATO: a CAD tool for intelligent design of optical networks and interconnects

    Science.gov (United States)

    Chlamtac, Imrich; Ciesielski, Maciej; Fumagalli, Andrea F.; Ruszczyk, Chester; Wedzinga, Gosse

    1997-10-01

    Increasing communication speed requirements have created a great interest in very high speed optical and all-optical networks and interconnects. The design of these optical systems is a highly complex task, requiring the simultaneous optimization of various parts of the system, ranging from optical components' characteristics to access protocol techniques. Currently there are no computer aided design (CAD) tools on the market to support the interrelated design of all parts of optical communication systems, thus the designer has to rely on costly and time consuming testbed evaluations. The objective of the CATO (CAD tool for optical networks and interconnects) project is to develop a prototype of an intelligent CAD tool for the specification, design, simulation and optimization of optical communication networks. CATO allows the user to build an abstract, possible incomplete, model of the system, and determine its expected performance. Based on design constraints provided by the user, CATO will automatically complete an optimum design, using mathematical programming techniques, intelligent search methods and artificial intelligence (AI). Initial design and testing of a CATO prototype (CATO-1) has been completed recently. The objective was to prove the feasibility of combining AI techniques, simulation techniques, an optical device library and a graphical user interface into a flexible CAD tool for obtaining optimal communication network designs in terms of system cost and performance. CATO-1 is an experimental tool for designing packet-switching wavelength division multiplexing all-optical communication systems using a LAN/MAN ring topology as the underlying network. The two specific AI algorithms incorporated are simulated annealing and a genetic algorithm. CATO-1 finds the optimal number of transceivers for each network node, using an objective function that includes the cost of the devices and the overall system performance.

  16. Intelligent coverage path planning for agricultural robots and autonomous machines on three-dimensional terrain

    DEFF Research Database (Denmark)

    Hameed, Ibahim

    2014-01-01

    Field operations should be done in a manner that minimizes time and travels over the field surface. Automated and intelligent path planning can help to find the best coverage path so that costs of various field operations can be minimized. The algorithms for generating an optimized field coverage...

  17. Machining tools in AISI M2 high-speed steel obtained by spray forming process

    International Nuclear Information System (INIS)

    Jesus, Edilson Rosa Barbosa de.

    2004-01-01

    The aim of the present work was the obtention of AISI M2 high-speed steel by spray forming technique and the material evaluation when used as machining tool. The obtained material was hot rolled at 50% and 72% reduction ratios, and from which it was manufactured inserts for machining tests. The performance of inserts made of the spray formed material was compared to inserts obtained from conventional and powder metallurgy (MP) processed materials. The spray formed material was chemical, physical, mechanical and microstructural characterised. For further characterisation, the materials were submitted to machining tests for performance evaluation under real work condition. The results of material characterisation highlight the potential of the spray forming technique, in the obtention of materials with good characteristics and properties. Under the current processing, hot rolling and heat treatments condition, the analysis of the results of the machining tests revealed a very similar behaviour among the tested materials. Proceeding a criterious analysis of the machining results tests, it was verified that the performance presented by the powder metallurgy material (MP) was slight superior, followed by conventional obtained material (MConv), which presented a insignificant advantage over the spray formed and hot rolled (72% reduction ratio) material. The worst result was encountered for the spray forming and hot rolled (50% reduction ratio) material that presented the highest wear values. (author)

  18. Modeling and simulation of the fluid flow in wire electrochemical machining with rotating tool (wire ECM)

    Science.gov (United States)

    Klocke, F.; Herrig, T.; Zeis, M.; Klink, A.

    2017-10-01

    Combining the working principle of electrochemical machining (ECM) with a universal rotating tool, like a wire, could manage lots of challenges of the classical ECM sinking process. Such a wire-ECM process could be able to machine flexible and efficient 2.5-dimensional geometries like fir tree slots in turbine discs. Nowadays, established manufacturing technologies for slotting turbine discs are broaching and wire electrical discharge machining (wire EDM). Nevertheless, high requirements on surface integrity of turbine parts need cost intensive process development and - in case of wire-EDM - trim cuts to reduce the heat affected rim zone. Due to the process specific advantages, ECM is an attractive alternative manufacturing technology and is getting more and more relevant for sinking applications within the last few years. But ECM is also opposed with high costs for process development and complex electrolyte flow devices. In the past, few studies dealt with the development of a wire ECM process to meet these challenges. However, previous concepts of wire ECM were only suitable for micro machining applications. Due to insufficient flushing concepts the application of the process for machining macro geometries failed. Therefore, this paper presents the modeling and simulation of a new flushing approach for process assessment. The suitability of a rotating structured wire electrode in combination with an axial flushing for electrodes with high aspect ratios is investigated and discussed.

  19. Repurposing mainstream CNC machine tools for laser-based additive manufacturing

    Science.gov (United States)

    Jones, Jason B.

    2016-04-01

    The advent of laser technology has been a key enabler for industrial 3D printing, known as Additive Manufacturing (AM). Despite its commercial success and unique technical capabilities, laser-based AM systems are not yet able to produce parts with the same accuracy and surface finish as CNC machining. To enable the geometry and material freedoms afforded by AM, yet achieve the precision and productivity of CNC machining, hybrid combinations of these two processes have started to gain traction. To achieve the benefits of combined processing, laser technology has been integrated into mainstream CNC machines - effectively repurposing them as hybrid manufacturing platforms. This paper reviews how this engineering challenge has prompted beam delivery innovations to allow automated changeover between laser processing and machining, using standard CNC tool changers. Handling laser-processing heads using the tool changer also enables automated change over between different types of laser processing heads, further expanding the breadth of laser processing flexibility in a hybrid CNC. This paper highlights the development, challenges and future impact of hybrid CNCs on laser processing.

  20. Performance of Ti-multilayer coated tool during machining of MDN431 alloyed steel

    Science.gov (United States)

    Badiger, Pradeep V.; Desai, Vijay; Ramesh, M. R.

    2018-04-01

    Turbine forgings and other components are required to be high resistance to corrosion and oxidation because which they are highly alloyed with Ni and Cr. Midhani manufactures one of such material MDN431. It's a hard-to-machine steel with high hardness and strength. PVD coated insert provide an answer to problem with its state of art technique on the WC tool. Machinability studies is carried out on MDN431 steel using uncoated and Ti-multilayer coated WC tool insert using Taguchi optimisation technique. During the present investigation, speed (398-625rpm), feed (0.093-0.175mm/rev), and depth of cut (0.2-0.4mm) varied according to Taguchi L9 orthogonal array, subsequently cutting forces and surface roughness (Ra) were measured. Optimizations of the obtained results are done using Taguchi technique for cutting forces and surface roughness. Using Taguchi technique linear fit model regression analysis carried out for the combination of each input variable. Experimented results are compared and found the developed model is adequate which supported by proof trials. Speed, feed and depth of cut are linearly dependent on the cutting force and surface roughness for uncoated insert whereas Speed and depth of cut feed is inversely dependent in coated insert for both cutting force and surface roughness. Machined surface for coated and uncoated inserts during machining of MDN431 is studied using optical profilometer.

  1. Methods of In-Process On-Machine Auto-Inspection of Dimensional Error and Auto-Compensation of Tool Wear for Precision Turning

    Directory of Open Access Journals (Sweden)

    Shih-Ming Wang

    2016-04-01

    Full Text Available The purpose of this study is mainly to develop an information and communication technology (ICT-based intelligent dimension inspection and tool wear compensation method for precision tuning. With the use of vibration signal processing/characteristics analysis technology combined with ICT, statistical analysis, and diagnosis algorithms, the method can be used to proceed with an on-line dimension inspection and on-machine tool wear auto-compensation for the turning process. Meanwhile, the method can also monitor critical tool life to identify the appropriate time for cutter replacement to reduce machining costs and improve the production efficiency of the turning process. Compared to the traditional ways, the method offers the advantages of requiring less manpower, and having better production efficiency, high tool life, fewer scrap parts, and low costs for inspection instruments. Algorithms and diagnosis threshold values for the detection, cutter wear compensation, and cutter life monitoring were developed. In addition, a bilateral communication module utilizing FANUC Open CNC (computer numerical control Application Programming Interface (API Spec was developed for the on-line extraction of instant NC (numerical control codes for monitoring and transmit commands to CNC controllers for cutter wear compensation. With use of local area networks (LAN to deliver the detection and correction information, the proposed method was able to remotely control the on-machine monitoring process and upload the machining and inspection data to a remote central platform for further production optimization. The verification experiments were conducted on a turning production line. The results showed that the system provided 93% correction for size inspection and 100% correction for cutter wear compensation.

  2. Dust Emission Induced By Friction Modifications At Tool Chip Interface In Dry Machining In MMCp

    International Nuclear Information System (INIS)

    Kremer, Arnaud; El Mansori, Mohamed

    2011-01-01

    This paper investigates the relationship between dust emission and tribological conditions at the tool-chip interface when machining Metal Matrix composite reinforced with particles (MMCp) in dry mode. Machining generates aerosols that can easily be inhaled by workers. Aerosols may be composed of oil mist, tool material or alloying elements of workpiece material. Bar turning tests were conducted on a 2009 aluminum alloy reinforced with different level of Silicon Carbide particles (15, 25 and 35% of SiCp). Variety of PCD tools and nanostructured diamond coatings were used to analyze their performances on air pollution. A spectrometer was used to detect airborne aerosol particles in the size range between 0.3μm to 20 μm and to sort them in 15 size channels in real time. It was used to compare the effects of test parameters on dust emission. Observations of tool face and chip morphology reveal the importance of friction phenomena. It was demonstrated that level of friction modifies chip curvature and dust emission. The increase of level of reinforcement increase the chip segmentation and decrease the contact length and friction area. A ''running in'' phenomenon with important dust emission appeared with PCD tool due to the tool rake face flatness. In addition dust generation is more sensitive to edge integrity than power consumption.

  3. Dust Emission Induced By Friction Modifications At Tool Chip Interface In Dry Machining In MMCp

    Science.gov (United States)

    Kremer, Arnaud; El Mansori, Mohamed

    2011-01-01

    This paper investigates the relationship between dust emission and tribological conditions at the tool-chip interface when machining Metal Matrix composite reinforced with particles (MMCp) in dry mode. Machining generates aerosols that can easily be inhaled by workers. Aerosols may be composed of oil mist, tool material or alloying elements of workpiece material. Bar turning tests were conducted on a 2009 aluminum alloy reinforced with different level of Silicon Carbide particles (15, 25 and 35% of SiCp). Variety of PCD tools and nanostructured diamond coatings were used to analyze their performances on air pollution. A spectrometer was used to detect airborne aerosol particles in the size range between 0.3μm to 20 μm and to sort them in 15 size channels in real time. It was used to compare the effects of test parameters on dust emission. Observations of tool face and chip morphology reveal the importance of friction phenomena. It was demonstrated that level of friction modifies chip curvature and dust emission. The increase of level of reinforcement increase the chip segmentation and decrease the contact length and friction area. A "running in" phenomenon with important dust emission appeared with PCD tool due to the tool rake face flatness. In addition dust generation is more sensitive to edge integrity than power consumption.

  4. Mounting arrangement for the drive system of an air-bearing spindle on a machine tool

    Science.gov (United States)

    Lunsford, J.S.; Crisp, D.W.; Petrowski, P.L.

    1987-12-07

    The present invention is directed to a mounting arrangement for the drive system of an air-bearing spindle utilized on a machine tool such as a lathe. The mounting arrangement of the present invention comprises a housing which is secured to the casing of the air bearing in such a manner that the housing position can be selectively adjusted to provide alignment of the air-bearing drive shaft supported by the housing and the air-bearing spindle. Once this alignment is achieved the air between spindle and the drive arrangement is maintained in permanent alignment so as to overcome misalignment problems encountered in the operation of the machine tool between the air-bearing spindle and the shaft utilized for driving the air-bearing spindle.

  5. Clinical Data Warehouse: An Effective Tool to Create Intelligence in Disease Management.

    Science.gov (United States)

    Karami, Mahtab; Rahimi, Azin; Shahmirzadi, Ali Hosseini

    Clinical business intelligence tools such as clinical data warehouse enable health care organizations to objectively assess the disease management programs that affect the quality of patients' life and well-being in public. The purpose of these programs is to reduce disease occurrence, improve patient care, and decrease health care costs. Therefore, applying clinical data warehouse can be effective in generating useful information about aspects of patient care to facilitate budgeting, planning, research, process improvement, external reporting, benchmarking, and trend analysis, as well as to enable the decisions needed to prevent the progression or appearance of the illness aligning with maintaining the health of the population. The aim of this review article is to describe the benefits of clinical data warehouse applications in creating intelligence for disease management programs.

  6. Space applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 4: Application of ARAMIS capabilities to space project functional elements

    Science.gov (United States)

    Miller, R. H.; Minsky, M. L.; Smith, D. B. S.

    1982-01-01

    Applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities and their related ground support functions are studied, so that informed decisions can be made on which aspects of ARAMIS to develop. The specific tasks which will be required by future space project tasks are identified and the relative merits of these options are evaluated. The ARAMIS options defined and researched span the range from fully human to fully machine, including a number of intermediate options (e.g., humans assisted by computers, and various levels of teleoperation). By including this spectrum, the study searches for the optimum mix of humans and machines for space project tasks.

  7. Analytical sensitivity analysis of geometric errors in a three axis machine tool

    International Nuclear Information System (INIS)

    Park, Sung Ryung; Yang, Seung Han

    2012-01-01

    In this paper, an analytical method is used to perform a sensitivity analysis of geometric errors in a three axis machine tool. First, an error synthesis model is constructed for evaluating the position volumetric error due to the geometric errors, and then an output variable is defined, such as the magnitude of the position volumetric error. Next, the global sensitivity analysis is executed using an analytical method. Finally, the sensitivity indices are calculated using the quantitative values of the geometric errors

  8. STUDY OF THE VIBRATION LEVEL IN CASE OF MANUFACTURING ON A CNC MACHINE-TOOL

    Directory of Open Access Journals (Sweden)

    Ioan Călin ROȘCA

    2015-12-01

    Full Text Available The paper presents the results of an experimental research performed on a CNC machine tool type ISEL-GFV considering the vibration level developed during the manufacturing of different pieces of particleboard at six processing regimes. There were recorded signals on both time and frequency domains on the three main directions. Based on recorded data there are presented the main conclusions referring to the level of vibrations and the frequencies associated to the highest levels.

  9. Parameter identification and optimization of slide guide joint of CNC machine tools

    Science.gov (United States)

    Zhou, S.; Sun, B. B.

    2017-11-01

    The joint surface has an important influence on the performance of CNC machine tools. In order to identify the dynamic parameters of slide guide joint, the parametric finite element model of the joint is established and optimum design method is used based on the finite element simulation and modal test. Then the mode that has the most influence on the dynamics of slip joint is found through harmonic response analysis. Take the frequency of this mode as objective, the sensitivity analysis of the stiffness of each joint surface is carried out using Latin Hypercube Sampling and Monte Carlo Simulation. The result shows that the vertical stiffness of slip joint surface constituted by the bed and the slide plate has the most obvious influence on the structure. Therefore, this stiffness is taken as the optimization variable and the optimal value is obtained through studying the relationship between structural dynamic performance and stiffness. Take the stiffness values before and after optimization into the FEM of machine tool, and it is found that the dynamic performance of the machine tool is improved.

  10. High productivity machining of holes in Inconel 718 with SiAlON tools

    Science.gov (United States)

    Agirreurreta, Aitor Arruti; Pelegay, Jose Angel; Arrazola, Pedro Jose; Ørskov, Klaus Bonde

    2016-10-01

    Inconel 718 is often employed in aerospace engines and power generation turbines. Numerous researches have proven the enhanced productivity when turning with ceramic tools compared to carbide ones, however there is considerably less information with regard to milling. Moreover, no knowledge has been published about machining holes with this type of tools. Additional research on different machining techniques, like for instance circular ramping, is critical to expand the productivity improvements that ceramics can offer. In this a 3D model of the machining and a number of experiments with SiAlON round inserts have been carried out in order to evaluate the effect of the cutting speed and pitch on the tool wear and chip generation. The results of this analysis show that three different types of chips are generated and also that there are three potential wear zones. Top slice wear is identified as the most critical wear type followed by the notch wear as a secondary wear mechanism. Flank wear and adhesion are also found in most of the tests.

  11. Influence of Cooling Lubricants on the Surface Roughness and Energy Efficiency of the Cutting Machine Tools

    Directory of Open Access Journals (Sweden)

    Jersák J.

    2017-08-01

    Full Text Available The Technical University of Liberec and Brandenburg University of Technology Cottbus-Senftenberg investigated the influence of cooling lubricants on the surface roughness and energy efficiency of cutting machine tools. After summarizing the achieved experimental results, the authors conclude that cooling lubricants extensively influence the cutting temperature, cutting forces and energy consumption. Also, it is recognizable that cooling lubricants affect the cutting tools lifetime and the workpiece surface quality as well. Furthermore, costs of these cooling lubricants and the related environmental burden need to be considered. A current trend is to reduce the amount of lubricants that are used, e.g., when the Minimum Quantity Lubrication (MQL technique is applied. The lubricant or process liquid is thereby transported by the compressed air in the form of an aerosol to the contact area between the tool and workpiece. The cutting process was monitored during testing by the three following techniques: lubricant-free cutting, cutting with the use of a lubricant with the MQL technique, and only utilizing finish-turning and finish-face milling. The research allowed the authors to monitor the cutting power and mark the achieved surface quality in relation to the electrical power consumption of the cutting machine. In conclusions, the coherence between energy efficiency of the cutting machine and the workpiece surface quality regarding the used cooling lubricant is described.

  12. Influence of export control policy on the competitiveness of machine tool producing organizations

    Science.gov (United States)

    Ahrstrom, Jeffrey D.

    The possible influence of export control policies on producers of export controlled machine tools is examined in this quantitative study. International market competitiveness theories hold that market controlling policies such as export control regulations may influence an organization's ability to compete (Burris, 2010). Differences in domestic application of export control policy on machine tool exports may impose throttling effects on the competitiveness of participating firms (Freedenberg, 2010). Commodity shipments from Japan, Germany, and the United States to the Russian market will be examined using descriptive statistics; gravity modeling of these specific markets provides a foundation for comparison to actual shipment data; and industry participant responses to a user developed survey will provide additional data for analysis using a Kruskal-Wallis one-way analysis of variance. There is scarce academic research data on the topic of export control effects within the machine tool industry. Research results may be of interest to industry leadership in market participation decisions, advocacy arguments, and strategic planning. Industry advocates and export policy decision makers could find data of interest in supporting positions for or against modifications of export control policies.

  13. A computational proof of concept of a machine-intelligent artificial pancreas using Lyapunov stability and differential game theory.

    Science.gov (United States)

    Greenwood, Nigel J C; Gunton, Jenny E

    2014-07-01

    This study demonstrated the novel application of a "machine-intelligent" mathematical structure, combining differential game theory and Lyapunov-based control theory, to the artificial pancreas to handle dynamic uncertainties. Realistic type 1 diabetes (T1D) models from the literature were combined into a composite system. Using a mixture of "black box" simulations and actual data from diabetic medical histories, realistic sets of diabetic time series were constructed for blood glucose (BG), interstitial fluid glucose, infused insulin, meal estimates, and sometimes plasma insulin assays. The problem of underdetermined parameters was side stepped by applying a variant of a genetic algorithm to partial information, whereby multiple candidate-personalized models were constructed and then rigorously tested using further data. These formed a "dynamic envelope" of trajectories in state space, where each trajectory was generated by a hypothesis on the hidden T1D system dynamics. This dynamic envelope was then culled to a reduced form to cover observed dynamic behavior. A machine-intelligent autonomous algorithm then implemented game theory to construct real-time insulin infusion strategies, based on the flow of these trajectories through state space and their interactions with hypoglycemic or near-hyperglycemic states. This technique was tested on 2 simulated participants over a total of fifty-five 24-hour days, with no hypoglycemic or hyperglycemic events, despite significant uncertainties from using actual diabetic meal histories with 10-minute warnings. In the main case studies, BG was steered within the desired target set for 99.8% of a 16-hour daily assessment period. Tests confirmed algorithm robustness for ±25% carbohydrate error. For over 99% of the overall 55-day simulation period, either formal controller stability was achieved to the desired target or else the trajectory was within the desired target. These results suggest that this is a stable, high

  14. The Influence of Tool Geometry towards Cutting Performance in Machining Aluminium 7075

    Directory of Open Access Journals (Sweden)

    Muhammad Syafik Jumali

    2017-01-01

    Full Text Available Aerospace industries often use Computer Numerical Control (CNC machining in manufacturing aerospace parts. Aluminium 7075 is the most common material used as aircraft components. This research aims to produce end mill with optimum geometry in terms of the helix angle, primary radial relief angle and secondary relief angle. End mills with different geometry parameters are tested on Aluminium 7075 and data on surface roughness and tool wear were collected. The results were then analysed to determine which parameters brought the optimum result with regards to surface roughness and tool wear.

  15. Mathematical support for automated geometry analysis of lathe machining of oblique peakless round-nose tools

    Science.gov (United States)

    Filippov, A. V.; Tarasov, S. Yu; Podgornyh, O. A.; Shamarin, N. N.; Filippova, E. O.

    2017-01-01

    Automatization of engineering processes requires developing relevant mathematical support and a computer software. Analysis of metal cutting kinematics and tool geometry is a necessary key task at the preproduction stage. This paper is focused on developing a procedure for determining the geometry of oblique peakless round-nose tool lathe machining with the use of vector/matrix transformations. Such an approach allows integration into modern mathematical software packages in distinction to the traditional analytic description. Such an advantage is very promising for developing automated control of the preproduction process. A kinematic criterion for the applicable tool geometry has been developed from the results of this study. The effect of tool blade inclination and curvature on the geometry-dependent process parameters was evaluated.

  16. A Benchmarking Analysis of Open-Source Business Intelligence Tools in Healthcare Environments

    Directory of Open Access Journals (Sweden)

    Andreia Brandão

    2016-10-01

    Full Text Available In recent years, a wide range of Business Intelligence (BI technologies have been applied to different areas in order to support the decision-making process. BI enables the extraction of knowledge from the data stored. The healthcare industry is no exception, and so BI applications have been under investigation across multiple units of different institutions. Thus, in this article, we intend to analyze some open-source/free BI tools on the market and their applicability in the clinical sphere, taking into consideration the general characteristics of the clinical environment. For this purpose, six BI tools were selected, analyzed, and tested in a practical environment. Then, a comparison metric and a ranking were defined for the tested applications in order to choose the one that best applies to the extraction of useful knowledge and clinical data in a healthcare environment. Finally, a pervasive BI platform was developed using a real case in order to prove the tool viability.

  17. El Diseño Modular en el contexto del desarrollo de Máquinas Herramienta Reconfigurables. // Modular Design in the development of reconfigurable Machine Tools´ context.

    Directory of Open Access Journals (Sweden)

    R. Pérez Rodríguez

    2005-05-01

    Full Text Available Las tendencias actuales en los procesos de manufactura reflejan los cambios en las demandas de los clientes. En nuestrosdías, el mercado requiere inexorablemente de productos cada vez más personalizados, por lo que se tiende de unaproducción masiva hacia un tipo específico de producción, en menos tiempo y con menos costos de producción. Enrespuesta a esta necesidad, la nueva generación de máquinas herramienta debe de ser reconfigurable e inteligente. Lascaracterísticas principales de las Máquinas Reconfigurables e Inteligentes son la modularidad, convertibilidad, flexibilidady efectividad en los costos. Este artículo presenta un enfoque para el diseño modular de máquinas herramienta, basado en elportafolio de productos del constructor de máquinas. La metodología parte de un conjunto de requerimientos funcionalesdefinidos por el constructor de máquinas y ofrece una descripción de los posibles módulos que pueden ser desarrolladospara una determinada máquina herramienta reconfigurable.Palabras claves: Diseño modular, máquinas herramienta, reconfigurable, inteligente.___________________________________________________________________________Abstract.The manufacturing tendencies reflect the changes on the customer demands. Nowadays, the market is constantly requiringmore customized products, moving from mass production to “one-of-a-kind production” in less time with lower productioncosts. In response to this need, the next generation of machine tools should be reconfigurable and intelligent.Reconfigurability allows for the reduction of machine design lead time, machine set-up and ramp-up time. The principalcharacteristics of the Reconfigurable and Intelligent Machines are modularity, convertibility, flexibility and costeffectiveness.This paper presents an approach for the design of machine tools modules, based on the product portfolio ofthe machine tool builder. The methodology takes as input a set of functional requirements

  18. Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions.

    Science.gov (United States)

    Kassahun, Yohannes; Yu, Bingbin; Tibebu, Abraham Temesgen; Stoyanov, Danail; Giannarou, Stamatia; Metzen, Jan Hendrik; Vander Poorten, Emmanuel

    2016-04-01

    Advances in technology and computing play an increasingly important role in the evolution of modern surgical techniques and paradigms. This article reviews the current role of machine learning (ML) techniques in the context of surgery with a focus on surgical robotics (SR). Also, we provide a perspective on the future possibilities for enhancing the effectiveness of procedures by integrating ML in the operating room. The review is focused on ML techniques directly applied to surgery, surgical robotics, surgical training and assessment. The widespread use of ML methods in diagnosis and medical image computing is beyond the scope of the review. Searches were performed on PubMed and IEEE Explore using combinations of keywords: ML, surgery, robotics, surgical and medical robotics, skill learning, skill analysis and learning to perceive. Studies making use of ML methods in the context of surgery are increasingly being reported. In particular, there is an increasing interest in using ML for developing tools to understand and model surgical skill and competence or to extract surgical workflow. Many researchers begin to integrate this understanding into the control of recent surgical robots and devices. ML is an expanding field. It is popular as it allows efficient processing of vast amounts of data for interpreting and real-time decision making. Already widely used in imaging and diagnosis, it is believed that ML will also play an important role in surgery and interventional treatments. In particular, ML could become a game changer into the conception of cognitive surgical robots. Such robots endowed with cognitive skills would assist the surgical team also on a cognitive level, such as possibly lowering the mental load of the team. For example, ML could help extracting surgical skill, learned through demonstration by human experts, and could transfer this to robotic skills. Such intelligent surgical assistance would significantly surpass the state of the art in surgical

  19. Designing an Intelligent Mobile Learning Tool for Grammar Learning (i-MoL

    Directory of Open Access Journals (Sweden)

    Munir Shuib

    2015-01-01

    Full Text Available English is the most important second language in most non-English speaking countries, including Malaysia. A good English proficiency comes from good grasp of grammar. To conquer the problems of low English proficiency among Malaysians, it is important to identify the key motivators that could facilitate the process of grammar learning. In this digital age, technology can play a very important role and mobile technology could be one of it. Thus, this study aims at designing a mobile learning tool, namely the Intelligent Mobile Learning Tool for Grammar Learning (i-MoL to act as the “on-the-go” grammar learning support via mobile phones. i-MoL helps reinforce grammar learning through mobile phone with game-like applications, inquiry-based activities and flashcard-like information. The intelligent part of i-MoL lies in its ability to map the mobile-based grammar learning content to individual’s preferred learning styles based on Felder-Silverman Learning Style Model (FSLSM. The instructional system design through the ADDIE model was used in this study as a systematic approach in designing a novel and comprehensive mobile learning tool for grammar learning. In terms of implications, this study provides insights on how mobile technologies can be utilized to meet the mobility demand among language learners today.

  20. A Business intelligence tool for studying value co-creation and innovation

    DEFF Research Database (Denmark)

    Tanev, Stoyan; Ruskov, Petko; Georgiev, Lachezar

    2011-01-01

    Value co-creation is an emerging marketing and innovation paradigm describing a broader opening of the firm to its customers by providing them with the opportunity to become active participants in the design and development of personalized products, services and experiences. However......, there is not yet a fully satisfactory theoretical vision about its distinctive characteristics as compared to more traditional value creation approaches. One of the challenges in studying value co-creation is the lack of business intelligence (BI) tools that can be used in the conceptualization of value co...... is the relationship between the degree of firms’ involvement in value co-creation activities and their innovativeness....

  1. Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor Systems

    Directory of Open Access Journals (Sweden)

    Andreas König

    2009-11-01

    Full Text Available The emergence of novel sensing elements, computing nodes, wireless communication and integration technology provides unprecedented possibilities for the design and application of intelligent systems. Each new application system must be designed from scratch, employing sophisticated methods ranging from conventional signal processing to computational intelligence. Currently, a significant part of this overall algorithmic chain of the computational system model still has to be assembled manually by experienced designers in a time and labor consuming process. In this research work, this challenge is picked up and a methodology and algorithms for automated design of intelligent integrated and resource-aware multi-sensor systems employing multi-objective evolutionary computation are introduced. The proposed methodology tackles the challenge of rapid-prototyping of such systems under realization constraints and, additionally, includes features of system instance specific self-correction for sustained operation of a large volume and in a dynamically changing environment. The extension of these concepts to the reconfigurable hardware platform renders so called self-x sensor systems, which stands, e.g., for self-monitoring, -calibrating, -trimming, and -repairing/-healing systems. Selected experimental results prove the applicability and effectiveness of our proposed methodology and emerging tool. By our approach, competitive results were achieved with regard to classification accuracy, flexibility, and design speed under additional design constraints.

  2. Online multiple intelligence teaching tools (On-MITT) for enhancing interpersonal teaching activities

    Science.gov (United States)

    Mohamad, Siti Nurul Mahfuzah; Salam, Sazilah; Bakar, Norasiken; Sui, Linda Khoo Mei

    2014-07-01

    The theories of Multiple Intelligence (MI) used in this paper apply to students with interpersonal intelligence who is encouraged to work together in cooperative groups where interpersonal interaction is practiced. In this context, students used their knowledge and skills to help the group or partner to complete the tasks given. Students can interact with each other as they learn and the process of learning requires their verbal and non-verbal communication skills, co-operation and empathy in the group. Meanwhile educators can incorporate cooperative learning in groups in the classroom. On-MITT provides various tools to facilitate lecturers in preparing e-content that applies interpersonal intelligence. With minimal knowledge of Information and Technology (IT) skills, educators can produce creative and interesting teaching activities and teaching materials. The objective of this paper is to develop On-MITT prototype for interpersonal teaching activities. This paper addressed initial prototype of this study. An evaluation of On-MITT has been completed by 20 lecturers of Malaysian Polytechnics. Motivation Survey Questionnaire is used as the instrument to measure four motivation variables: ease of use, enjoyment, usefulness and self-confidence. Based on the findings, the On-MITT can facilitate educators to prepare teaching materials that are compatible for interpersonal learner.

  3. The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation.

    Science.gov (United States)

    Michie, Susan; Thomas, James; Johnston, Marie; Aonghusa, Pol Mac; Shawe-Taylor, John; Kelly, Michael P; Deleris, Léa A; Finnerty, Ailbhe N; Marques, Marta M; Norris, Emma; O'Mara-Eves, Alison; West, Robert

    2017-10-18

    Behaviour change is key to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. We need to make better use of the vast amount of accumulating evidence from behaviour change intervention (BCI) evaluations and promote the uptake of that evidence into a wide range of contexts. The scale and complexity of the task of synthesising and interpreting this evidence, and increasing evidence timeliness and accessibility, will require increased computer support. The Human Behaviour-Change Project (HBCP) will use Artificial Intelligence and Machine Learning to (i) develop and evaluate a 'Knowledge System' that automatically extracts, synthesises and interprets findings from BCI evaluation reports to generate new insights about behaviour change and improve prediction of intervention effectiveness and (ii) allow users, such as practitioners, policy makers and researchers, to easily and efficiently query the system to get answers to variants of the question 'What works, compared with what, how well, with what exposure, with what behaviours (for how long), for whom, in what settings and why?'. The HBCP will: a) develop an ontology of BCI evaluations and their reports linking effect sizes for given target behaviours with intervention content and delivery and mechanisms of action, as moderated by exposure, populations and settings; b) develop and train an automated feature extraction system to annotate BCI evaluation reports using this ontology; c) develop and train machine learning and reasoning algorithms to use the annotated BCI evaluation reports to predict effect sizes for particular combinations of behaviours, interventions, populations and settings; d) build user and machine interfaces for interrogating and updating the knowledge base; and e) evaluate all the above in terms of performance and utility. The HBCP aims to revolutionise our ability to synthesise, interpret and deliver

  4. Study of Cutting Edge Temperature and Cutting Force of End Mill Tool in High Speed Machining

    Directory of Open Access Journals (Sweden)

    Kiprawi Mohammad Ashaari

    2017-01-01

    Full Text Available A wear of cutting tools during machining process is unavoidable due to the presence of frictional forces during removing process of unwanted material of workpiece. It is unavoidable but can be controlled at slower rate if the cutting speed is fixed at certain point in order to achieve optimum cutting conditions. The wear of cutting tools is closely related with the thermal deformations that occurred between the frictional contact point of cutting edge of cutting tool and workpiece. This research paper is focused on determinations of relationship among cutting temperature, cutting speed, cutting forces and radial depth of cutting parameters. The cutting temperature is determined by using the Indium Arsenide (InAs and Indium Antimonide (InSb photocells to measure infrared radiation that are emitted from cutting tools and cutting forces is determined by using dynamometer. The high speed machining process is done by end milling the outer surface of carbon steel. The signal from the photocell is digitally visualized in the digital oscilloscope. Based on the results, the cutting temperature increased as the radial depth and cutting speed increased. The cutting forces increased when radial depth increased but decreased when cutting speed is increased. The setup for calibration and discussion of the experiment will be explained in this paper.

  5. A tool for urban soundscape evaluation applying Support Vector Machines for developing a soundscape classification model.

    Science.gov (United States)

    Torija, Antonio J; Ruiz, Diego P; Ramos-Ridao, Angel F

    2014-06-01

    To ensure appropriate soundscape management in urban environments, the urban-planning authorities need a range of tools that enable such a task to be performed. An essential step during the management of urban areas from a sound standpoint should be the evaluation of the soundscape in such an area. In this sense, it has been widely acknowledged that a subjective and acoustical categorization of a soundscape is the first step to evaluate it, providing a basis for designing or adapting it to match people's expectations as well. In this sense, this work proposes a model for automatic classification of urban soundscapes. This model is intended for the automatic classification of urban soundscapes based on underlying acoustical and perceptual criteria. Thus, this classification model is proposed to be used as a tool for a comprehensive urban soundscape evaluation. Because of the great complexity associated with the problem, two machine learning techniques, Support Vector Machines (SVM) and Support Vector Machines trained with Sequential Minimal Optimization (SMO), are implemented in developing model classification. The results indicate that the SMO model outperforms the SVM model in the specific task of soundscape classification. With the implementation of the SMO algorithm, the classification model achieves an outstanding performance (91.3% of instances correctly classified). © 2013 Elsevier B.V. All rights reserved.

  6. Surface texturing of Si3N4–SiC ceramic tool components by pulsed laser machining

    CSIR Research Space (South Africa)

    Tshabalala, LC

    2016-03-01

    Full Text Available texturing of Si(sub3)N(sub4)–SiC composites in the fabrication of machining tool inserts for various tribological applications. The samples were machined at varied laser energy (0.1–0.6 mJ) and lateral pulse overlap (50–88%) in order to generate a sequence...

  7. Software tool for resolution of inverse problems using artificial intelligence techniques: an application in neutron spectrometry

    International Nuclear Information System (INIS)

    Castaneda M, V. H.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Leon P, A. A.; Hernandez P, C. F.; Espinoza G, J. G.; Ortiz R, J. M.; Vega C, H. R.; Mendez, R.; Gallego, E.; Sousa L, M. A.

    2016-10-01

    The Taguchi methodology has proved to be highly efficient to solve inverse problems, in which the values of some parameters of the model must be obtained from the observed data. There are intrinsic mathematical characteristics that make a problem known as inverse. Inverse problems appear in many branches of science, engineering and mathematics. To solve this type of problem, researches have used different techniques. Recently, the use of techniques based on Artificial Intelligence technology is being explored by researches. This paper presents the use of a software tool based on artificial neural networks of generalized regression in the solution of inverse problems with application in high energy physics, specifically in the solution of the problem of neutron spectrometry. To solve this problem we use a software tool developed in the Mat Lab programming environment, which employs a friendly user interface, intuitive and easy to use for the user. This computational tool solves the inverse problem involved in the reconstruction of the neutron spectrum based on measurements made with a Bonner spheres spectrometric system. Introducing this information, the neural network is able to reconstruct the neutron spectrum with high performance and generalization capability. The tool allows that the end user does not require great training or technical knowledge in development and/or use of software, so it facilitates the use of the program for the resolution of inverse problems that are in several areas of knowledge. The techniques of Artificial Intelligence present singular veracity to solve inverse problems, given the characteristics of artificial neural networks and their network topology, therefore, the tool developed has been very useful, since the results generated by the Artificial Neural Network require few time in comparison to other techniques and are correct results comparing them with the actual data of the experiment. (Author)

  8. Research on criticality analysis method of CNC machine tools components under fault rate correlation

    Science.gov (United States)

    Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

    2018-02-01

    In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

  9. Investigation of machining damage and tool wear resulting from drilling powder metal aluminum alloy

    Energy Technology Data Exchange (ETDEWEB)

    Fell, H.A. [Lockheed Martin Energy Systems, Inc., Oak Ridge, TN (United States)

    1997-05-01

    This report documents the cutting of aluminum powder metallurgy (PM) parts for the North Carolina Manufacturing Extension Partnership. The parts, an aluminum powder metal formulation, were supplied by Sinter Metals Inc., of Conover, North Carolina. The intended use of the alloy is for automotive components. Machining tests were conducted at Y-12 in the machine shop of the Skills Demonstration Center in Building 9737. Testing was done on June 2 and June 3, 1997. The powder metal alloy tested is very abrasive and tends to wear craters and produce erosion effects on the chip washed face of the drills used. It also resulted in huge amounts of flank wear and degraded performance on the part of most drills. Anti-wear coatings on drills seemed to have an effect. Drills with the coating showed less wear for the same amount of cutting. The usefulness of coolants and lubricants in reducing tool wear and chipping/breakout was not investigated.

  10. Robust iterative learning contouring controller with disturbance observer for machine tool feed drives.

    Science.gov (United States)

    Simba, Kenneth Renny; Bui, Ba Dinh; Msukwa, Mathew Renny; Uchiyama, Naoki

    2018-04-01

    In feed drive systems, particularly machine tools, a contour error is more significant than the individual axial tracking errors from the view point of enhancing precision in manufacturing and production systems. The contour error must be within the permissible tolerance of given products. In machining complex or sharp-corner products, large contour errors occur mainly owing to discontinuous trajectories and the existence of nonlinear uncertainties. Therefore, it is indispensable to design robust controllers that can enhance the tracking ability of feed drive systems. In this study, an iterative learning contouring controller consisting of a classical Proportional-Derivative (PD) controller and disturbance observer is proposed. The proposed controller was evaluated experimentally by using a typical sharp-corner trajectory, and its performance was compared with that of conventional controllers. The results revealed that the maximum contour error can be reduced by about 37% on average. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

    Science.gov (United States)

    Wei, Yawei; Venayagamoorthy, Ganesh Kumar

    2017-09-01

    To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Status of Preliminary Design on the Assembly Tools for ITER Tokamak Machine

    International Nuclear Information System (INIS)

    Nam, Kyoung O; Park, Hyun Ki; Kim, Dong Jin; Moon, Jae Hwan; Kim, Byung Seok; Lee, Jae Hyuk; Shaw, Robert

    2012-01-01

    The ITER Tokamak device is principally composed of nine 40 .deg. sectors. Each 40 .deg. sector is made up of one 40 .deg. vacuum vessel (VV), two 20 .deg. toroidal filed coils (TFC) and associated vacuum vessel thermal shield (VVTS) segments which consist of one inboard and two outboard vacuum vessel thermal shields. Based on the design description document and final report prepared by the ITER organization (IO) and conceptual design, Korea has carried out the preliminary design of these assembly tools. The assembly strategy and relevant tools for the 40 .deg. sector sub-assembly and sector assembly at in-pit should be developed to satisfy the basic assembly requirements of the ITER Tokamak machine. Assembly strategy, preliminary design of the sector sub-assembly and assembly tools are described in this paper

  13. Tool Wear Analysis due to Machining In Super Austenitic Stainless Steel

    Directory of Open Access Journals (Sweden)

    Polishetty Ashwin

    2017-01-01

    Full Text Available This paper presents tool wear study when a machinability test was applied using milling on Super Austenitic Stainless Steel AL6XN alloy. Eight milling trials were performed under two cutting speeds, 100 m/min and 150 m/min, combined with two feed rates at 0.1mm/tooth and 0.15 mm/tooth and two depth of cuts at 2 mm and 3 mm. An Alicona 3D optical surface profilometer was used to scan cutting inserts flank and rake face areas for wear. Readings such as maximum and minimum deviations were extracted and used to analyse the outcomes. Results showed various types of wear were generated on the tool rake and flank faces. The common formed wear was the crater wear. The formation of the build-up edge was observed on the rake face of the cutting tool.

  14. Profiles of Major Suppliers to the Automotive Industry : Vol. 7. Machine Tool Suppliers to the Automotive Industry.

    Science.gov (United States)

    1982-08-01

    This study summarizes extensive information collected over a two-year period (October 1978 to October 1980) on suppliers of parts and components, materials, and machine tools to the automotive industry in the United States. The objective of the study...

  15. HClass: Automatic classification tool for health pathologies using artificial intelligence techniques.

    Science.gov (United States)

    Garcia-Chimeno, Yolanda; Garcia-Zapirain, Begonya

    2015-01-01

    The classification of subjects' pathologies enables a rigorousness to be applied to the treatment of certain pathologies, as doctors on occasions play with so many variables that they can end up confusing some illnesses with others. Thanks to Machine Learning techniques applied to a health-record database, it is possible to make using our algorithm. hClass contains a non-linear classification of either a supervised, non-supervised or semi-supervised type. The machine is configured using other techniques such as validation of the set to be classified (cross-validation), reduction in features (PCA) and committees for assessing the various classifiers. The tool is easy to use, and the sample matrix and features that one wishes to classify, the number of iterations and the subjects who are going to be used to train the machine all need to be introduced as inputs. As a result, the success rate is shown either via a classifier or via a committee if one has been formed. A 90% success rate is obtained in the ADABoost classifier and 89.7% in the case of a committee (comprising three classifiers) when PCA is applied. This tool can be expanded to allow the user to totally characterise the classifiers by adjusting them to each classification use.

  16. Competitive intelligence tools used by small and medium-sized enterprises

    Directory of Open Access Journals (Sweden)

    Tshilidzi Eric Nenzhelele

    2015-08-01

    Full Text Available Small and Medium-sized Enterprises (SMEs contribute highly to the gross domestic product, reduction in unemployment, wealth creation and improvement in the quality of life. Due to technology and globalisation, SMEs now compete with enterprises beyond the borders of their country. To survive in this global competitive business environment, SMEs seek for tools that offer competitive advantage. Competitive Intelligence (CI provides competitive advantage to enterprises that practice it. While CI practice has been widely research for larger enterprises, there is lack of research on CI practice pertaining to SMEs. This research establishes tools used by SMEs in CI practice. The research was quantitative in nature and a self-administered questionnaire was used to collected data from owners/managers of SMEs

  17. The Virtual UNICOS Process Expert: integration of Artificial Intelligence tools in Control Systems

    CERN Multimedia

    Vilches Calvo, I; Barillere, R

    2009-01-01

    UNICOS is a CERN framework to produce control applications. It provides operators with ways to interact with all process items from the most simple (e.g. I/O channels) to the most abstract objects (e.g. a part of the plant). This possibility of fine grain operation is particularly useful to recover from abnormal situations if operators have the required knowledge. The Virtual UNICOS Process Expert project aims at providing operators with means to handle difficult operation cases for which the intervention of process experts is usually requested. The main idea of project is to use the openness of the UNICOS-based applications to integrate tools (e.g. Artificial Intelligence tools) which will act as Process Experts to analyze complex situations, to propose and to execute smooth recovery procedures.

  18. corrosion and wear resistant ternary Cr-C-N coatings deposited by the ARC PVD process for machining tools and machining parts

    International Nuclear Information System (INIS)

    Knotek, O.; Lugscheider, E.; Zimmermann, H.; Bobzin, K.

    1997-01-01

    With the deposition of PVD hard coatings on the tools applied in machining operations it is possible to achieve significant improvements in the performance and quality of the machining processes. Depending on the machined material and the operating principle, e.g. turning, milling or drilling, not only different machining parameters but also different coating materials are necessary. In interrupted cut machining of tempered steel, for example, the life time of Ti-C-N coated inserts is several times greater than the Ti-C-N coated ones. This is a result of the favourable thermophysical and tribological properties of Ti-N-C. The potential for tool protection by CrN coatings is a result of the high ductility and low internal stress of this coating materials. CrN films can be deposited with greater film thickness, still maintaining very good adhesion. This paper presents the development of new arc PVD coatings in the system Cr-C-N. Owing to the carbon content in the coating an increased hardness and a better wear behavior in comparison to CrN was expected. The effects of various carbon carrier gases on the coating properties were examined. The coating properties were investigated by mechanical tests. X-ray diffraction, SEM analysis and corrosion tests. Some of the coatings were tested in machining tests. The results of these tests are presented in this paper. (author)

  19. Development of a method of continuous improvement of services using the Business Intelligence tools

    Directory of Open Access Journals (Sweden)

    Svetlana V. Kulikova

    2018-01-01

    Full Text Available The purpose of the study was to develop a method of continuous improvement of services using the Business Intelligence tools.Materials and methods: the materials are used on the concept of the Deming Cycle, methods and Business Intelligence technologies, Agile methodology and SCRUM.Results: the article considers the problem of continuous improvement of services and offers solutions using methods and technologies of Business Intelligence. In this case, the purpose of this technology is to solve and make the final decision regarding what needs to be improved in the current organization of services. In other words, Business Intelligence helps the product manager to see what is hidden from the “human eye” on the basis of received and processed data. Development of a method based on the concept of the Deming Cycle and Agile methodologies, and SCRUM.The article describes the main stages of development of method based on activity of the enterprise. It is necessary to fully build the Business Intelligence system in the enterprise to identify bottlenecks and justify the need for their elimination and, in general, for continuous improvement of the services. This process is represented in the notation of DFD. The article presents a scheme for the selection of suitable agile methodologies.The proposed concept of the solution of the stated objectives, including methods of identification of problems through Business Intelligence technology, development of the system for troubleshooting and analysis of results of the introduced changes. The technical description of the project is given.Conclusion: following the work of the authors there was formed the concept of the method for the continuous improvement of the services, using the Business Intelligence technology with the specifics of the enterprises, offering SaaS solutions. It was also found that when using this method, the recommended development methodology is SCRUM. The result of this scientific

  20. Intelligent mechatronics; Intelligent mechatronics

    Energy Technology Data Exchange (ETDEWEB)

    Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

    1995-10-01

    Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

  1. A planning quality evaluation tool for prostate adaptive IMRT based on machine learning

    International Nuclear Information System (INIS)

    Zhu Xiaofeng; Ge Yaorong; Li Taoran; Thongphiew, Danthai; Yin Fangfang; Wu, Q Jackie

    2011-01-01

    Purpose: To ensure plan quality for adaptive IMRT of the prostate, we developed a quantitative evaluation tool using a machine learning approach. This tool generates dose volume histograms (DVHs) of organs-at-risk (OARs) based on prior plans as a reference, to be compared with the adaptive plan derived from fluence map deformation. Methods: Under the same configuration using seven-field 15 MV photon beams, DVHs of OARs (bladder and rectum) were estimated based on anatomical information of the patient and a model learned from a database of high quality prior plans. In this study, the anatomical information was characterized by the organ volumes and distance-to-target histogram (DTH). The database consists of 198 high quality prostate plans and was validated with 14 cases outside the training pool. Principal component analysis (PCA) was applied to DVHs and DTHs to quantify their salient features. Then, support vector regression (SVR) was implemented to establish the correlation between the features of the DVH and the anatomical information. Results: DVH/DTH curves could be characterized sufficiently just using only two or three truncated principal components, thus, patient anatomical information was quantified with reduced numbers of variables. The evaluation of the model using the test data set demonstrated its accuracy ∼80% in prediction and effectiveness in improving ART planning quality. Conclusions: An adaptive IMRT plan quality evaluation tool based on machine learning has been developed, which estimates OAR sparing and provides reference in evaluating ART.

  2. Hardware and software and machine-tool simulation with parallel structures mechanisms

    Directory of Open Access Journals (Sweden)

    Keba P.V.

    2016-12-01

    Full Text Available The usage spectrum of mechanisms with parallel structure is spreading all the time. The mechanisms of machine-tools and manipulators become more complicated and it is necessary to improve the program-controlled modules. Closed circuit mechanisms are mostly spread in robotic complexes, where manipulator performs complicated spatial movements by the given trajectory. The usage spectrum is very wide and the most popular are sorting, welding, assembling and others. However, the problem of designing the operating programs is still present even today. It is just because the developed post-processors are created for the equipment that we have for now. But new machine tool constructions appear every day and there is a necessity to control them. The problems associated with using of hardware and software of mechanisms with parallel structure in computer-aided simulation are considered. The program for inverse problem kinematics solving is designed. New method of designing the control programs is found. The kinematic analysis methods options and calculated data obtained by computer mathematics systems are shown with «Tools Glide» software taken as an example.

  3. Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

    Science.gov (United States)

    Pierce, S. A.

    2017-12-01

    Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case

  4. Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

    Directory of Open Access Journals (Sweden)

    Okokpujie Imhade Princess

    2017-12-01

    Full Text Available In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N, feed rate (f, axial depth of cut (a and radial depth of cut (r. The experiment was designed using central composite design (CCD in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM. The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

  5. Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

    Science.gov (United States)

    Okokpujie, Imhade Princess; Ikumapayi, Omolayo M.; Okonkwo, Ugochukwu C.; Salawu, Enesi Y.; Afolalu, Sunday A.; Dirisu, Joseph O.; Nwoke, Obinna N.; Ajayi, Oluseyi O.

    2017-12-01

    In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N), feed rate (f), axial depth of cut (a) and radial depth of cut (r). The experiment was designed using central composite design (CCD) in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM). The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

  6. Heuristic algorithms for solving of the tool routing problem for CNC cutting machines

    Science.gov (United States)

    Chentsov, P. A.; Petunin, A. A.; Sesekin, A. N.; Shipacheva, E. N.; Sholohov, A. E.

    2015-11-01

    The article is devoted to the problem of minimizing the path of the cutting tool to shape cutting machines began. This problem can be interpreted as a generalized traveling salesman problem. Earlier version of the dynamic programming method to solve this problem was developed. Unfortunately, this method allows to process an amount not exceeding thirty circuits. In this regard, the task of constructing quasi-optimal route becomes relevant. In this paper we propose options for quasi-optimal greedy algorithms. Comparison of the results of exact and approximate algorithms is given.

  7. Intelligent Machine Vision Based Modeling and Positioning System in Sand Casting Process

    Directory of Open Access Journals (Sweden)

    Shahid Ikramullah Butt

    2017-01-01

    Full Text Available Advanced vision solutions enable manufacturers in the technology sector to reconcile both competitive and regulatory concerns and address the need for immaculate fault detection and quality assurance. The modern manufacturing has completely shifted from the manual inspections to the machine assisted vision inspection methodology. Furthermore, the research outcomes in industrial automation have revolutionized the whole product development strategy. The purpose of this research paper is to introduce a new scheme of automation in the sand casting process by means of machine vision based technology for mold positioning. Automation has been achieved by developing a novel system in which casting molds of different sizes, having different pouring cup location and radius, position themselves in front of the induction furnace such that the center of pouring cup comes directly beneath the pouring point of furnace. The coordinates of the center of pouring cup are found by using computer vision algorithms. The output is then transferred to a microcontroller which controls the alignment mechanism on which the mold is placed at the optimum location.

  8. Modeling of the flow stress for AISI H13 Tool Steel during Hard Machining Processes

    Science.gov (United States)

    Umbrello, Domenico; Rizzuti, Stefania; Outeiro, José C.; Shivpuri, Rajiv

    2007-04-01

    In general, the flow stress models used in computer simulation of machining processes are a function of effective strain, effective strain rate and temperature developed during the cutting process. However, these models do not adequately describe the material behavior in hard machining, where a range of material hardness between 45 and 60 HRC are used. Thus, depending on the specific material hardness different material models must be used in modeling the cutting process. This paper describes the development of a hardness-based flow stress and fracture models for the AISI H13 tool steel, which can be applied for range of material hardness mentioned above. These models were implemented in a non-isothermal viscoplastic numerical model to simulate the machining process for AISI H13 with various hardness values and applying different cutting regime parameters. Predicted results are validated by comparing them with experimental results found in the literature. They are found to predict reasonably well the cutting forces as well as the change in chip morphology from continuous to segmented chip as the material hardness change.

  9. Modeling of the flow stress for AISI H13 Tool Steel during Hard Machining Processes

    International Nuclear Information System (INIS)

    Umbrello, Domenico; Rizzuti, Stefania; Outeiro, Jose C.; Shivpuri, Rajiv

    2007-01-01

    In general, the flow stress models used in computer simulation of machining processes are a function of effective strain, effective strain rate and temperature developed during the cutting process. However, these models do not adequately describe the material behavior in hard machining, where a range of material hardness between 45 and 60 HRC are used. Thus, depending on the specific material hardness different material models must be used in modeling the cutting process. This paper describes the development of a hardness-based flow stress and fracture models for the AISI H13 tool steel, which can be applied for range of material hardness mentioned above. These models were implemented in a non-isothermal viscoplastic numerical model to simulate the machining process for AISI H13 with various hardness values and applying different cutting regime parameters. Predicted results are validated by comparing them with experimental results found in the literature. They are found to predict reasonably well the cutting forces as well as the change in chip morphology from continuous to segmented chip as the material hardness change

  10. CONDITIONS FOR STABLE CHIP BREAKING AND PROVISION OF MACHINED SURFACE QUALITY WHILE TURNING WITH ASYMMETRIC TOOL VIBRATIONS

    Directory of Open Access Journals (Sweden)

    V. K. Sheleh

    2015-01-01

    Full Text Available The paper considers a process of turning structural steel with asymmetric tool vibrations directed along feeding. Asymmetric vibrations characterized by asymmetry coefficient of vibration cycle, their frequency and amplitude are additionally transferred to the tool in the turning process with the purpose to crush chips. Conditions of stable chip breaking and obtaining optimum dimensions of chip elements have been determined in the paper. In order to reduce a negative impact of the vibration amplitude on a cutting process and quality of the machined surfaces machining must be carried out with its minimum value. In this case certain ratio of the tool vibration frequency to the work-piece rotation speed has been ensured in the paper. A formula has been obtained for calculation of this ratio with due account of the expected length of chip elements and coefficient of vibration cycle asymmetry.Influence of the asymmetric coefficient of the tool vibration cycle on roughness of the machined surfaces and cutting tool wear has been determined in the paper. According to the results pertaining to machining of work-pieces made of 45 and ШХ15 steel the paper presents mathematical relationships of machined surface roughness with cutting modes and asymmetry coefficient of tool vibration cycle. Tool feeding being one of the cutting modes exerts the most significant impact on the roughness value and increase of the tool feeding entails increase in roughness. Reduction in coefficient of vibration cycle asymmetry contributes to surface roughness reduction. However, the cutting tool wear occurs more intensive. Coefficient of the vibration cycle asymmetry must be increased in order to reduce wear rate. Therefore, the choice of the coefficient of the vibration cycle asymmetry is based on the parameters of surface roughness which must be obtained after machining and intensity of tool wear rate.The paper considers a process of turning structural steel with asymmetric

  11. [Emotional Intelligence Index: a tool for the routine assessment of mental health promotion programs in schools].

    Science.gov (United States)

    Veltro, Franco; Ialenti, Valentina; Morales García, Manuel Alejandro; Gigantesco, Antonella

    2016-01-01

    After critical examination of several aspects relating to the evaluation of some dimensions of emotional intelligence through self-assessment tools, is described the procedure of construction and validation of an Index for its measurement, conceived only for the routine assessment of health promotion programs mental in schools that include among their objectives the improvement of emotional intelligence specifically "outcome-oriented". On the basis of the two most common international tools, are listed 27 items plus 6 of control, illustrated two Focus Group (FG) of students (face validity). The scale obtained by FG was administered to 300 students, and the results were submitted to factorial analysis (construct validity). It was also evaluated the internal consistency with Cronbach's Alpha and studied concurrent validity with the emotional quotient inventory, a scale of perceived self-efficacy and a stress test rating. From the analysis of FG all the original items were modified, deleted 4, and reduced the encoding system from 6 to 4 levels of Likert scale. Of the 23 items included in the analysis have emerged five factors (intra-psychic dimension, interpersonal, impulsivity, adaptive coping, sense of self-efficacy) for a total of 15 items. Very satisfactory were the results of the validation process of internal consistency (0.72) and the concurrent validity. The results are positive. It is obtained in fact the shortest routine assessment tool currently available in Italy which constitutes a real Index, for which compilation are required on average 3 minutes. Is emphasized the characteristic of an Index, and not of questionnaire or interview for clinical use, highlighting the only specific use for mental health promotion programs in schools.

  12. Machine learning methods as a tool to analyse incomplete or irregularly sampled radon time series data.

    Science.gov (United States)

    Janik, M; Bossew, P; Kurihara, O

    2018-07-15

    Machine learning is a class of statistical techniques which has proven to be a powerful tool for modelling the behaviour of complex systems, in which response quantities depend on assumed controls or predictors in a complicated way. In this paper, as our first purpose, we propose the application of machine learning to reconstruct incomplete or irregularly sampled data of time series indoor radon ( 222 Rn). The physical assumption underlying the modelling is that Rn concentration in the air is controlled by environmental variables such as air temperature and pressure. The algorithms "learn" from complete sections of multivariate series, derive a dependence model and apply it to sections where the controls are available, but not the response (Rn), and in this way complete the Rn series. Three machine learning techniques are applied in this study, namely random forest, its extension called the gradient boosting machine and deep learning. For a comparison, we apply the classical multiple regression in a generalized linear model version. Performance of the models is evaluated through different metrics. The performance of the gradient boosting machine is found to be superior to that of the other techniques. By applying learning machines, we show, as our second purpose, that missing data or periods of Rn series data can be reconstructed and resampled on a regular grid reasonably, if data of appropriate physical controls are available. The techniques also identify to which degree the assumed controls contribute to imputing missing Rn values. Our third purpose, though no less important from the viewpoint of physics, is identifying to which degree physical, in this case environmental variables, are relevant as Rn predictors, or in other words, which predictors explain most of the temporal variability of Rn. We show that variables which contribute most to the Rn series reconstruction, are temperature, relative humidity and day of the year. The first two are physical

  13. The research of device for measuring film thickness of intelligent coating machine

    Directory of Open Access Journals (Sweden)

    Wang Wanjun

    2015-01-01

    Full Text Available Ion beam sputtering machine uses computer to real time monitor the change of film thickness in the preparation process of soft X ray multilayer element fabrication. It solves the problems of uneven film thickness and too thick film thickness and so on, which exist in the original preparation process. The high-precision quartz crystal converts film thickness measurement into frequency measurement. The equal precision frequency meter based on FPGA measures the frequency. It can reduce the signal delay and interference signal of discrete components, accordingly improving the accuracy of measurement. Then it sents the count value to the host computer through the single chip microcomputer serial port. It calculates and displays the value by the GUI of LabVIEW. The experimental results show that, the relative measurement error can be decreased to 1/10, i.e., the measurement accuracy can be improved by more than ten times.

  14. Adjustment and Prediction of Machine Factors Based on Neural Artificial Intelligence

    International Nuclear Information System (INIS)

    Hussein, A.Z.; Amin, E.S.; Ibrahim, M.S.

    2009-01-01

    Since the discovery of x-ray, it is use in examination has become an integral part of medical diagnostic radiology. The use of X-ray is harmful to human beings but recent technological advances and regulatory constraints have made the medical Xray much safer than they were at the beginning of the 20th century. However, the potential benefits of the engineered safety features can not be fully realized unless the operators are aware of these safety features. The aim of this work is to adjust and predict x-ray machine factors (current and voltage) using neural artificial network in order to obtain effective dose within the range of dose limitation system and assure radiological safety.

  15. Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics

    Directory of Open Access Journals (Sweden)

    Héctor Herrero

    2017-05-01

    Full Text Available This paper presents a state machine-based architecture, which enhances the flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes, increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating the presented approach versus traditional robot programming techniques.

  16. Research on Error Modelling and Identification of 3 Axis NC Machine Tools Based on Cross Grid Encoder Measurement

    International Nuclear Information System (INIS)

    Du, Z C; Lv, C F; Hong, M S

    2006-01-01

    A new error modelling and identification method based on the cross grid encoder is proposed in this paper. Generally, there are 21 error components in the geometric error of the 3 axis NC machine tools. However according our theoretical analysis, the squareness error among different guide ways affects not only the translation error component, but also the rotational ones. Therefore, a revised synthetic error model is developed. And the mapping relationship between the error component and radial motion error of round workpiece manufactured on the NC machine tools are deduced. This mapping relationship shows that the radial error of circular motion is the comprehensive function result of all the error components of link, worktable, sliding table and main spindle block. Aiming to overcome the solution singularity shortcoming of traditional error component identification method, a new multi-step identification method of error component by using the Cross Grid Encoder measurement technology is proposed based on the kinematic error model of NC machine tool. Firstly, the 12 translational error components of the NC machine tool are measured and identified by using the least square method (LSM) when the NC machine tools go linear motion in the three orthogonal planes: XOY plane, XOZ plane and YOZ plane. Secondly, the circular error tracks are measured when the NC machine tools go circular motion in the same above orthogonal planes by using the cross grid encoder Heidenhain KGM 182. Therefore 9 rotational errors can be identified by using LSM. Finally the experimental validation of the above modelling theory and identification method is carried out in the 3 axis CNC vertical machining centre Cincinnati 750 Arrow. The entire 21 error components have been successfully measured out by the above method. Research shows the multi-step modelling and identification method is very suitable for 'on machine measurement'

  17. Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success.

    Science.gov (United States)

    Thrall, James H; Li, Xiang; Li, Quanzheng; Cruz, Cinthia; Do, Synho; Dreyer, Keith; Brink, James

    2018-03-01

    Worldwide interest in artificial intelligence (AI) applications, including imaging, is high and growing rapidly, fueled by availability of large datasets ("big data"), substantial advances in computing power, and new deep-learning algorithms. Apart from developing new AI methods per se, there are many opportunities and challenges for the imaging community, including the development of a common nomenclature, better ways to share image data, and standards for validating AI program use across different imaging platforms and patient populations. AI surveillance programs may help radiologists prioritize work lists by identifying suspicious or positive cases for early review. AI programs can be used to extract "radiomic" information from images not discernible by visual inspection, potentially increasing the diagnostic and prognostic value derived from image datasets. Predictions have been made that suggest AI will put radiologists out of business. This issue has been overstated, and it is much more likely that radiologists will beneficially incorporate AI methods into their practices. Current limitations in availability of technical expertise and even computing power will be resolved over time and can also be addressed by remote access solutions. Success for AI in imaging will be measured by value created: increased diagnostic certainty, faster turnaround, better outcomes for patients, and better quality of work life for radiologists. AI offers a new and promising set of methods for analyzing image data. Radiologists will explore these new pathways and are likely to play a leading role in medical applications of AI. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  18. Strategic Performance Measurement Using Balanced Scorecard: A Case of Machine Tool Industry

    Directory of Open Access Journals (Sweden)

    Kshatriya Anil

    2017-02-01

    Full Text Available This paper focuses on implementation, monitoring, and application of balanced scorecard (BSC techniques in an organization involved in providing machine tool solutions to the industrial sector. The growth of the company considered in real time constituted improvements of both top and bottom lines. In the industry under consideration, it was observed that in our company, the top line was steadily growing but not the bottom line. This is when we started getting down to brass tacks and strategically focusing on growth in overall profits of the company. This included growing revenues by improving of EBITDA (earnings before interests, taxes, depreciation, and amortization and by increasing efficiency (i.e., cutting costs. These improvements were implemented by chalking out a comprehensive BSC designed to suit the machine tool industry. The four perspectives of the management, namely, internal business process, organizational learning, financial perspective, and customer perspective, have been considered lucidly and enunciate the parameters that affect the BSC very aptly. The BSC designed considered 9 objectives and 27 relative measures of these factors to quantify the various quantitative and qualitative dimensions that affect the company’s performance. A Balanced Lean Index (BL Score was used to measure the results for company X.

  19. Experimental Investigation of Surface Layer Properties of High Thermal Conductivity Tool Steel after Electrical Discharge Machining

    Directory of Open Access Journals (Sweden)

    Rafał Świercz

    2017-12-01

    Full Text Available New materials require the use of advanced technology in manufacturing complex shape parts. One of the modern materials widely used in the tool industry for injection molds or hot stamping dies is high conductivity tool steel (HTCS 150. Due to its hardness (55 HRC and thermal conductivity at 66 W/mK, this material is difficult to machine by conventional treatment and is being increasingly manufactured by nonconventional technology such as electrical discharge machining (EDM. In the EDM process, material is removed from the workpiece by a series of electrical discharges that cause changes to the surface layers properties. The final state of the surface layer directly influences the durability of the produced elements. This paper presents the influence of EDM process parameters: discharge current Ic and the pulse time ton on surface layer properties. The experimental investigation was carried out with an experimental methodology design. Surface layers properties including roughness 3D parameters, the thickness of the white layer, heat affected zone, tempered layer and occurring micro cracks were investigated and described. The influence of the response surface methodology (RSM of discharge current Ic and the pulse time ton on the thickness of the white layer and roughness parameters Sa, Sds and Ssc were described and established.

  20. Multidisciplinary Investigations Regarding the Wear of Machine Tools Operating Into the Soil

    Science.gov (United States)

    Cardei, P.; Vladutoiu, L. C.; Gheorghe, G.; Fechete, T. L. V.; Chisiu, G.

    2018-01-01

    The paper presents the results obtained by the authors in investigating the problem of wear of work organs of machines working in continuous interaction with the soil. The phenomenon of the interaction of the tools of agricultural machinery for ploughing, and the soil, is a complex of phenomena, one of the most difficult to model. Among the phenomena involved in this interaction, friction and wear (of many types) are the most important. We did not take into account the chemical wear, and by the wear caused by weather conditions. Research has focused on formulating a theory that has more than a descriptive character, for it be used for application purposes. For this we used classical theoretical models, mathematical models based on the theory of continuous bodies, theory of flow of fluids around the profiles, as well as other theories, approached or not, in an attempt to solve as satisfactorily the issue of the wear, for the tools of the agricultural machines for the tillage. We also sought to highlight the fact that wear is a phenomenon on a micro and macro-scale scale, and its generating causes must ultimately be related to observable effects, on the macro-structural scale.

  1. Random and Systematic Errors Share in Total Error of Probes for CNC Machine Tools

    Directory of Open Access Journals (Sweden)

    Adam Wozniak

    2018-03-01

    Full Text Available Probes for CNC machine tools, as every measurement device, have accuracy limited by random errors and by systematic errors. Random errors of these probes are described by a parameter called unidirectional repeatability. Manufacturers of probes for CNC machine tools usually specify only this parameter, while parameters describing systematic errors of the probes, such as pre-travel variation or triggering radius variation, are used rarely. Systematic errors of the probes, linked to the differences in pre-travel values for different measurement directions, can be corrected or compensated, but it is not a widely used procedure. In this paper, the share of systematic errors and random errors in total error of exemplary probes are determined. In the case of simple, kinematic probes, systematic errors are much greater than random errors, so compensation would significantly reduce the probing error. Moreover, it shows that in the case of kinematic probes commonly specified unidirectional repeatability is significantly better than 2D performance. However, in the case of more precise strain-gauge probe systematic errors are of the same order as random errors, which means that errors correction or compensation, in this case, would not yield any significant benefits.

  2. Quality of clinical brain tumor MR spectra judged by humans and machine learning tools.

    Science.gov (United States)

    Kyathanahally, Sreenath P; Mocioiu, Victor; Pedrosa de Barros, Nuno; Slotboom, Johannes; Wright, Alan J; Julià-Sapé, Margarida; Arús, Carles; Kreis, Roland

    2018-05-01

    To investigate and compare human judgment and machine learning tools for quality assessment of clinical MR spectra of brain tumors. A very large set of 2574 single voxel spectra with short and long echo time from the eTUMOUR and INTERPRET databases were used for this analysis. Original human quality ratings from these studies as well as new human guidelines were used to train different machine learning algorithms for automatic quality control (AQC) based on various feature extraction methods and classification tools. The performance was compared with variance in human judgment. AQC built using the RUSBoost classifier that combats imbalanced training data performed best. When furnished with a large range of spectral and derived features where the most crucial ones had been selected by the TreeBagger algorithm it showed better specificity (98%) in judging spectra from an independent test-set than previously published methods. Optimal performance was reached with a virtual three-class ranking system. Our results suggest that feature space should be relatively large for the case of MR tumor spectra and that three-class labels may be beneficial for AQC. The best AQC algorithm showed a performance in rejecting spectra that was comparable to that of a panel of human expert spectroscopists. Magn Reson Med 79:2500-2510, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  3. Five-axis Control Processing Using NC Machine Tools : A Tool Posture Decision Using the Tangent Slope at a Cut Point on a Work

    OpenAIRE

    小島, 龍広; 西田, 知照; 扇谷, 保彦

    2003-01-01

    This report deals with the way to decide tool posture and the way to analytically calculate tool path for the work shape requiring 5-axis control machining. In the tool path calculation, basic equations are derived using the principle that the tangent slope at a cut point on a work and the one at a cutting point on a tool edge are identical. A tool posture decision procedure using the tangent slope at each cut point on a work is proposed for any shape of tool edge. The valid- ity of the way t...

  4. A chord error conforming tool path B-spline fitting method for NC machining based on energy minimization and LSPIA

    OpenAIRE

    He, Shanshan; Ou, Daojiang; Yan, Changya; Lee, Chen-Han

    2015-01-01

    Piecewise linear (G01-based) tool paths generated by CAM systems lack G1 and G2 continuity. The discontinuity causes vibration and unnecessary hesitation during machining. To ensure efficient high-speed machining, a method to improve the continuity of the tool paths is required, such as B-spline fitting that approximates G01 paths with B-spline curves. Conventional B-spline fitting approaches cannot be directly used for tool path B-spline fitting, because they have shortages such as numerical...

  5. Evaluation of Surface Roughness and Power Consumption in Machining FCD 450 Cast Iron using Coated and Uncoated Irregular Milling Tools

    International Nuclear Information System (INIS)

    Yusoff, Ahmad Razlan; Arsyad, Fitriyanti

    2016-01-01

    In this project, the effects of different cutting parameters on surface roughness and power consumption when machining FCD450 cast iron were studied using coated and uncoated irregular milling tool geometry of variable helix and pitch. Their responses on roughness and power consumption were evaluated based on the spindle speed, feed rate, and depth of cut, machining length and machining time. Results showed that except spindle speed and machining length, other parameters such as feed rate, axial and radial depth of cut and also machining time proportionate with surface roughness. The power consumption proportionately increase for all cutting parameters except feedrate. It is showed that the average decrement 27.92 percent for surface roughness and average decrement 9.32 percent for power consumption by using coated compared to uncoated tool. Optimum cutting parameters for both minimum surface roughness and power consumption can be determined. The coated tools performed better than uncoated milling tools for responses of surface roughness and power consumption to increase machining productivity and profit. (paper)

  6. INFORMATION ARCHITECTURE ANALYSIS USING BUSINESS INTELLIGENCE TOOLS BASED ON THE INFORMATION NEEDS OF EXECUTIVES

    Directory of Open Access Journals (Sweden)

    Fabricio Sobrosa Affeldt

    2013-08-01

    Full Text Available Devising an information architecture system that enables an organization to centralize information regarding its operational, managerial and strategic performance is one of the challenges currently facing information technology. The present study aimed to analyze an information architecture system developed using Business Intelligence (BI technology. The analysis was performed based on a questionnaire enquiring as to whether the information needs of executives were met during the process. A theoretical framework was applied consisting of information architecture and BI technology, using a case study methodology. Results indicated that the transaction processing systems studied did not meet the information needs of company executives. Information architecture using data warehousing, online analytical processing (OLAP tools and data mining may provide a more agile means of meeting these needs. However, some items must be included and others modified, in addition to improving the culture of information use by company executives.

  7. Artificial intelligence-based computer modeling tools for controlling slag foaming in electric arc furnaces

    Science.gov (United States)

    Wilson, Eric Lee

    Due to increased competition in a world economy, steel companies are currently interested in developing techniques that will allow for the improvement of the steelmaking process, either by increasing output efficiency or by improving the quality of their product, or both. Slag foaming is one practice that has been shown to contribute to both these goals. However, slag foaming is highly dynamic and difficult to model or control. This dissertation describes an effort to use artificial intelligence-based tools (genetic algorithms, fuzzy logic, and neural networks) to both model and control the slag foaming process. Specifically, a neural network is trained and tested on slag foaming data provided by a steel plant. This neural network model is then controlled by a fuzzy logic controller, which in turn is optimized by a genetic algorithm. This tuned controller is then installed at a steel plant and given control be a more efficient slag foaming controller than what was previously used by the steel plant.

  8. Managing Sustainability with the Support of Business Intelligence Methods and Tools

    Science.gov (United States)

    Petrini, Maira; Pozzebon, Marlei

    In this paper we explore the role of business intelligence (BI) in helping to support the management of sustainability in contemporary firms. The concepts of sustainability and corporate social responsibility (CSR) are among the most important themes to have emerged in the last decade at the global level. We suggest that BI methods and tools have an important but not yet well studied role to play in helping organizations implement and monitor sustainable and socially responsible business practices. Using grounded theory, the main contribution of our study is to propose a conceptual model that seeks to support the process of definition and monitoring of socio-environmental indicators and the relationship between their management and business strategy.

  9. Building an asynchronous web-based tool for machine learning classification.

    Science.gov (United States)

    Weber, Griffin; Vinterbo, Staal; Ohno-Machado, Lucila

    2002-01-01

    Various unsupervised and supervised learning methods including support vector machines, classification trees, linear discriminant analysis and nearest neighbor classifiers have been used to classify high-throughput gene expression data. Simpler and more widely accepted statistical tools have not yet been used for this purpose, hence proper comparisons between classification methods have not been conducted. We developed free software that implements logistic regression with stepwise variable selection as a quick and simple method for initial exploration of important genetic markers in disease classification. To implement the algorithm and allow our collaborators in remote locations to evaluate and compare its results against those of other methods, we developed a user-friendly asynchronous web-based application with a minimal amount of programming using free, downloadable software tools. With this program, we show that classification using logistic regression can perform as well as other more sophisticated algorithms, and it has the advantages of being easy to interpret and reproduce. By making the tool freely and easily available, we hope to promote the comparison of classification methods. In addition, we believe our web application can be used as a model for other bioinformatics laboratories that need to develop web-based analysis tools in a short amount of time and on a limited budget.

  10. Intelligent Fault Diagnosis of Delta 3D Printers Using Attitude Sensors Based on Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Kun He

    2018-04-01

    Full Text Available Health condition is a vital factor affecting printing quality for a 3D printer. In this work, an attitude monitoring approach is proposed to diagnose the fault of the delta 3D printer using support vector machines (SVM. An attitude sensor was mounted on the moving platform of the printer to monitor its 3-axial attitude angle, angular velocity, vibratory acceleration and magnetic field intensity. The attitude data of the working printer were collected under different conditions involving 12 fault types and a normal condition. The collected data were analyzed for diagnosing the health condition. To this end, the combination of binary classification, one-against-one with least-square SVM, was adopted for fault diagnosis modelling by using all channels of attitude monitoring data in the experiment. For comparison, each one channel of the attitude monitoring data was employed for model training and testing. On the other hand, a back propagation neural network (BPNN was also applied to diagnose fault using the same data. The best fault diagnosis accuracy (94.44% was obtained when all channels of the attitude monitoring data were used with SVM modelling. The results indicate that the attitude monitoring with SVM is an effective method for the fault diagnosis of delta 3D printers.

  11. Fullrmc, a rigid body Reverse Monte Carlo modeling package enabled with machine learning and artificial intelligence.

    Science.gov (United States)

    Aoun, Bachir

    2016-05-05

    A new Reverse Monte Carlo (RMC) package "fullrmc" for atomic or rigid body and molecular, amorphous, or crystalline materials is presented. fullrmc main purpose is to provide a fully modular, fast and flexible software, thoroughly documented, complex molecules enabled, written in a modern programming language (python, cython, C and C++ when performance is needed) and complying to modern programming practices. fullrmc approach in solving an atomic or molecular structure is different from existing RMC algorithms and software. In a nutshell, traditional RMC methods and software randomly adjust atom positions until the whole system has the greatest consistency with a set of experimental data. In contrast, fullrmc applies smart moves endorsed with reinforcement machine learning to groups of atoms. While fullrmc allows running traditional RMC modeling, the uniqueness of this approach resides in its ability to customize grouping atoms in any convenient way with no additional programming efforts and to apply smart and more physically meaningful moves to the defined groups of atoms. In addition, fullrmc provides a unique way with almost no additional computational cost to recur a group's selection, allowing the system to go out of local minimas by refining a group's position or exploring through and beyond not allowed positions and energy barriers the unrestricted three dimensional space around a group. © 2016 Wiley Periodicals, Inc.

  12. Towards Intelligent Interpretation of Low Strain Pile Integrity Testing Results Using Machine Learning Techniques.

    Science.gov (United States)

    Cui, De-Mi; Yan, Weizhong; Wang, Xiao-Quan; Lu, Lie-Min

    2017-10-25

    Low strain pile integrity testing (LSPIT), due to its simplicity and low cost, is one of the most popular NDE methods used in pile foundation construction. While performing LSPIT in the field is generally quite simple and quick, determining the integrity of the test piles by analyzing and interpreting the test signals (reflectograms) is still a manual process performed by experienced experts only. For foundation construction sites where the number of piles to be tested is large, it may take days before the expert can complete interpreting all of the piles and delivering the integrity assessment report. Techniques that can automate test signal interpretation, thus shortening the LSPIT's turnaround time, are of great business value and are in great need. Motivated by this need, in this paper, we develop a computer-aided reflectogram interpretation (CARI) methodology that can interpret a large number of LSPIT signals quickly and consistently. The methodology, built on advanced signal processing and machine learning technologies, can be used to assist the experts in performing both qualitative and quantitative interpretation of LSPIT signals. Specifically, the methodology can ease experts' interpretation burden by screening all test piles quickly and identifying a small number of suspected piles for experts to perform manual, in-depth interpretation. We demonstrate the methodology's effectiveness using the LSPIT signals collected from a number of real-world pile construction sites. The proposed methodology can potentially enhance LSPIT and make it even more efficient and effective in quality control of deep foundation construction.

  13. Intelligent Fault Diagnosis of Delta 3D Printers Using Attitude Sensors Based on Support Vector Machines

    Science.gov (United States)

    He, Kun; Yang, Zhijun; Bai, Yun; Long, Jianyu; Li, Chuan

    2018-01-01

    Health condition is a vital factor affecting printing quality for a 3D printer. In this work, an attitude monitoring approach is proposed to diagnose the fault of the delta 3D printer using support vector machines (SVM). An attitude sensor was mounted on the moving platform of the printer to monitor its 3-axial attitude angle, angular velocity, vibratory acceleration and magnetic field intensity. The attitude data of the working printer were collected under different conditions involving 12 fault types and a normal condition. The collected data were analyzed for diagnosing the health condition. To this end, the combination of binary classification, one-against-one with least-square SVM, was adopted for fault diagnosis modelling by using all channels of attitude monitoring data in the experiment. For comparison, each one channel of the attitude monitoring data was employed for model training and testing. On the other hand, a back propagation neural network (BPNN) was also applied to diagnose fault using the same data. The best fault diagnosis accuracy (94.44%) was obtained when all channels of the attitude monitoring data were used with SVM modelling. The results indicate that the attitude monitoring with SVM is an effective method for the fault diagnosis of delta 3D printers. PMID:29690641

  14. Intelligent Fault Diagnosis of Delta 3D Printers Using Attitude Sensors Based on Support Vector Machines.

    Science.gov (United States)

    He, Kun; Yang, Zhijun; Bai, Yun; Long, Jianyu; Li, Chuan

    2018-04-23

    Health condition is a vital factor affecting printing quality for a 3D printer. In this work, an attitude monitoring approach is proposed to diagnose the fault of the delta 3D printer using support vector machines (SVM). An attitude sensor was mounted on the moving platform of the printer to monitor its 3-axial attitude angle, angular velocity, vibratory acceleration and magnetic field intensity. The attitude data of the working printer were collected under different conditions involving 12 fault types and a normal condition. The collected data were analyzed for diagnosing the health condition. To this end, the combination of binary classification, one-against-one with least-square SVM, was adopted for fault diagnosis modelling by using all channels of attitude monitoring data in the experiment. For comparison, each one channel of the attitude monitoring data was employed for model training and testing. On the other hand, a back propagation neural network (BPNN) was also applied to diagnose fault using the same data. The best fault diagnosis accuracy (94.44%) was obtained when all channels of the attitude monitoring data were used with SVM modelling. The results indicate that the attitude monitoring with SVM is an effective method for the fault diagnosis of delta 3D printers.

  15. A Quasiphysics Intelligent Model for a Long Range Fast Tool Servo

    Science.gov (United States)

    Liu, Qiang; Zhou, Xiaoqin; Lin, Jieqiong; Xu, Pengzi; Zhu, Zhiwei

    2013-01-01

    Accurately modeling the dynamic behaviors of fast tool servo (FTS) is one of the key issues in the ultraprecision positioning of the cutting tool. Herein, a quasiphysics intelligent model (QPIM) integrating a linear physics model (LPM) and a radial basis function (RBF) based neural model (NM) is developed to accurately describe the dynamic behaviors of a voice coil motor (VCM) actuated long range fast tool servo (LFTS). To identify the parameters of the LPM, a novel Opposition-based Self-adaptive Replacement Differential Evolution (OSaRDE) algorithm is proposed which has been proved to have a faster convergence mechanism without compromising with the quality of solution and outperform than similar evolution algorithms taken for consideration. The modeling errors of the LPM and the QPIM are investigated by experiments. The modeling error of the LPM presents an obvious trend component which is about ±1.15% of the full span range verifying the efficiency of the proposed OSaRDE algorithm for system identification. As for the QPIM, the trend component in the residual error of LPM can be well suppressed, and the error of the QPIM maintains noise level. All the results verify the efficiency and superiority of the proposed modeling and identification approaches. PMID:24163627

  16. A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery

    Directory of Open Access Journals (Sweden)

    A. Castillo Atoche

    2013-01-01

    Full Text Available A novel parallel tool for large-scale image enhancement/reconstruction and postprocessing of radar/SAR sensor systems is addressed. The proposed parallel tool performs the following intelligent processing steps: image formation, for the application of different system-level effects of image degradation with a particular remote sensing (RS system and simulation of random noising effects, enhancement/reconstruction by employing nonparametric robust high-resolution techniques, and image postprocessing using the fuzzy anisotropic diffusion technique which incorporates a better edge-preserving noise removal effect and faster diffusion process. This innovative tool allows the processing of high-resolution images provided with different radar/SAR sensor systems as required by RS endusers for environmental monitoring, risk prevention, and resource management. To verify the performance implementation of the proposed parallel framework, the processing steps are developed and specifically tested on graphic processing units (GPU, achieving considerable speedups compared to the serial version of the same techniques implemented in C language.

  17. Intelligent Information Retrieval: Diagnosing Information Need. Part I. The Theoretical Framework for Developing an Intelligent IR Tool.

    Science.gov (United States)

    Cole, Charles

    1998-01-01

    Suggests that the principles underlying the procedure used by doctors to diagnose a patient's disease are useful in the design of intelligent information-retrieval systems because the task of the doctor is conceptually similar to the computer or human intermediary's task in information retrieval: to draw out the user's query/information need.…

  18. Machinability of an experimental Ti-Ag alloy in terms of tool life in a dental CAD/CAM system.

    Science.gov (United States)

    Inagaki, Ryoichi; Kikuchi, Masafumi; Takahashi, Masatoshi; Takada, Yukyo; Sasaki, Keiichi

    2015-01-01

    Titanium is difficult to machine because of its intrinsic properties. In a previous study, the machinability of titanium was improved by alloying with silver. This study aimed to evaluate the durability of tungsten carbide burs after the fabrication of frameworks using a Ti-20%Ag alloy and titanium with a computer-aided design and computer-aided manufacturing system. There was a significant difference in attrition area ratio between the two metals. Compared with titanium, the ratio of the area of attrition of machining burs was significantly lower for the experimental Ti-20%Ag alloy. The difference in the area of attrition for titanium and Ti-20%Ag became remarkable with increasing number of machining operations. The results show that the same burs can be used for a longer time with Ti-20%Ag than with pure titanium. Therefore, in terms of tool life, the machinability of the Ti-20%Ag alloy is superior to that of titanium.

  19. Analyzing the effect of cutting parameters on surface roughness and tool wear when machining nickel based hastelloy - 276

    International Nuclear Information System (INIS)

    Khidhir, Basim A; Mohamed, Bashir

    2011-01-01

    Machining parameters has an important factor on tool wear and surface finish, for that the manufacturers need to obtain optimal operating parameters with a minimum set of experiments as well as minimizing the simulations in order to reduce machining set up costs. The cutting speed is one of the most important cutting parameter to evaluate, it clearly most influences on one hand, tool life, tool stability, and cutting process quality, and on the other hand controls production flow. Due to more demanding manufacturing systems, the requirements for reliable technological information have increased. For a reliable analysis in cutting, the cutting zone (tip insert-workpiece-chip system) as the mechanics of cutting in this area are very complicated, the chip is formed in the shear plane (entrance the shear zone) and is shape in the sliding plane. The temperature contributed in the primary shear, chamfer and sticking, sliding zones are expressed as a function of unknown shear angle on the rake face and temperature modified flow stress in each zone. The experiments were carried out on a CNC lathe and surface finish and tool tip wear are measured in process. Machining experiments are conducted. Reasonable agreement is observed under turning with high depth of cut. Results of this research help to guide the design of new cutting tool materials and the studies on evaluation of machining parameters to further advance the productivity of nickel based alloy Hastelloy - 276 machining.

  20. The use of open and machine vision technologies for development of gesture recognition intelligent systems

    Science.gov (United States)

    Cherkasov, Kirill V.; Gavrilova, Irina V.; Chernova, Elena V.; Dokolin, Andrey S.

    2018-05-01

    The article is devoted to reflection of separate aspects of intellectual system gesture recognition development. The peculiarity of the system is its intellectual block which completely based on open technologies: OpenCV library and Microsoft Cognitive Toolkit (CNTK) platform. The article presents the rationale for the choice of such set of tools, as well as the functional scheme of the system and the hierarchy of its modules. Experiments have shown that the system correctly recognizes about 85% of images received from sensors. The authors assume that the improvement of the algorithmic block of the system will increase the accuracy of gesture recognition up to 95%.

  1. Intelligent Information Retrieval: Diagnosing Information Need. Part II. Uncertainty Expansion in a Prototype of a Diagnostic IR Tool.

    Science.gov (United States)

    Cole, Charles; Cantero, Pablo; Sauve, Diane

    1998-01-01

    Outlines a prototype of an intelligent information-retrieval tool to facilitate information access for an undergraduate seeking information for a term paper. Topics include diagnosing the information need, Kuhlthau's information-search-process model, Shannon's mathematical theory of communication, and principles of uncertainty expansion and…

  2. Evaluation of machine learning tools for inspection of steam generator tube structures using pulsed eddy current

    Science.gov (United States)

    Buck, J. A.; Underhill, P. R.; Morelli, J.; Krause, T. W.

    2017-02-01

    Degradation of nuclear steam generator (SG) tubes and support structures can result in a loss of reactor efficiency. Regular in-service inspection, by conventional eddy current testing (ECT), permits detection of cracks, measurement of wall loss, and identification of other SG tube degradation modes. However, ECT is challenged by overlapping degradation modes such as might occur for SG tube fretting accompanied by tube off-set within a corroding ferromagnetic support structure. Pulsed eddy current (PEC) is an emerging technology examined here for inspection of Alloy-800 SG tubes and associated carbon steel drilled support structures. Support structure hole size was varied to simulate uniform corrosion, while SG tube was off-set relative to hole axis. PEC measurements were performed using a single driver with an 8 pick-up coil configuration in the presence of flat-bottom rectangular frets as an overlapping degradation mode. A modified principal component analysis (MPCA) was performed on the time-voltage data in order to reduce data dimensionality. The MPCA scores were then used to train a support vector machine (SVM) that simultaneously targeted four independent parameters associated with; support structure hole size, tube off-centering in two dimensions and fret depth. The support vector machine was trained, tested, and validated on experimental data. Results were compared with a previously developed artificial neural network (ANN) trained on the same data. Estimates of tube position showed comparable results between the two machine learning tools. However, the ANN produced better estimates of hole inner diameter and fret depth. The better results from ANN analysis was attributed to challenges associated with the SVM when non-constant variance is present in the data.

  3. Finite Element Analysis as a response to frequently asked questions of machine tool mechanical design-engineers

    Directory of Open Access Journals (Sweden)

    Kehl Gerhard

    2017-01-01

    Full Text Available The finite element analysis (FEA nowadays is indispensable in the product development of machining centres and production machinery for metal cutting processes. It enables extensive static, dynamic and thermal simulation of digital prototypes of machine tools before production start-up. But until now less reflection has been made about what are the most pressing questions to be answered in this application field, with the intention to align the modelling and simulation methods with substantial requirements. Based on 3D CAD geometry data for a modern machining centre (Deckel-Maho-Gildemeister DMG 635 V eco merely the basic steps of a static analysis are reconstructed by FEA. Particularly the two most frequently asked questions by the design departments of machine tool manufacturers are discussed and highlighted. For this authentic simulation results are used, at which their selection is a consequence of long lasting experience in the industrial application of FEA in the design process chain. Noticing that such machine tools are mechatronic systems applying a considerable number of actuators, sensors and controllers in addition to mechanical structures, the answers to those core questions are required for design enhancement, to save costs and to improve the productivity and the quality of machined workpieces.

  4. Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools.

    Directory of Open Access Journals (Sweden)

    Lei Jia

    Full Text Available Thermostability issue of protein point mutations is a common occurrence in protein engineering. An application which predicts the thermostability of mutants can be helpful for guiding decision making process in protein design via mutagenesis. An in silico point mutation scanning method is frequently used to find "hot spots" in proteins for focused mutagenesis. ProTherm (http://gibk26.bio.kyutech.ac.jp/jouhou/Protherm/protherm.html is a public database that consists of thousands of protein mutants' experimentally measured thermostability. Two data sets based on two differently measured thermostability properties of protein single point mutations, namely the unfolding free energy change (ddG and melting temperature change (dTm were obtained from this database. Folding free energy change calculation from Rosetta, structural information of the point mutations as well as amino acid physical properties were obtained for building thermostability prediction models with informatics modeling tools. Five supervised machine learning methods (support vector machine, random forests, artificial neural network, naïve Bayes classifier, K nearest neighbor and partial least squares regression are used for building the prediction models. Binary and ternary classifications as well as regression models were built and evaluated. Data set redundancy and balancing, the reverse mutations technique, feature selection, and comparison to other published methods were discussed. Rosetta calculated folding free energy change ranked as the most influential features in all prediction models. Other descriptors also made significant contributions to increasing the accuracy of the prediction models.

  5. Analysis of residual stress in subsurface layers after precision hard machining of forging tools

    Directory of Open Access Journals (Sweden)

    Czan Andrej

    2018-01-01

    Full Text Available This paper is focused on analysis of residual stress of functional surfaces and subsurface layers created by precision technologies of hard machining for progressive constructional materials of forging tools. Methods of experiments are oriented on monitoring of residual stress in surface which is created by hard turning (roughing and finishing operations. Subsequently these surfaces were etched in thin layers by electro-chemical polishing. The residual stress was monitored in each etched layer. The measuring was executed by portable X-ray diffractometer for detection of residual stress and structural phases. The results significantly indicate rise and distribution of residual stress in surface and subsurface layers and their impact on functional properties of surface integrity.

  6. DIAGNOSTICS OF WORKPIECE SURFACE CONDITION BASED ON CUTTING TOOL VIBRATIONS DURING MACHINING

    Directory of Open Access Journals (Sweden)

    Jerzy Józwik

    2015-05-01

    Full Text Available The paper presents functional relationships between surface geometry parameters, feed and vibrations level in the radial direction of the workpiece. Time characteristics of the acceleration of cutting tool vibration registered during C45 steel and stainless steel machining for separate axes (X, Y, Z were presented as a function of feedrate f. During the tests surface geometric accuracy assessment was performed and 3D surface roughness parameters were determined. The Sz parameter was selected for the analysis, which was then collated with RMS vibration acceleration and feedrate f. The Sz parameter indirectly provides information on peak to valley height and is characterised by high generalising potential i.e. it is highly correlated to other surface and volume parameters of surface roughness. Test results presented in this paper may constitute a valuable source of information considering the influence of vibrations on geometric accuracy of elements for engineers designing technological processes.

  7. Servo scanning 3D micro EDM for array micro cavities using on-machine fabricated tool electrodes

    Science.gov (United States)

    Tong, Hao; Li, Yong; Zhang, Long

    2018-02-01

    Array micro cavities are useful in many fields including in micro molds, optical devices, biochips and so on. Array servo scanning micro electro discharge machining (EDM), using array micro electrodes with simple cross-sectional shape, has the advantage of machining complex 3D micro cavities in batches. In this paper, the machining errors caused by offline-fabricated array micro electrodes are analyzed in particular, and then a machining process of array servo scanning micro EDM is proposed by using on-machine fabricated array micro electrodes. The array micro electrodes are fabricated on-machine by combined procedures including wire electro discharge grinding, array reverse copying and electrode end trimming. Nine-array tool electrodes with Φ80 µm diameter and 600 µm length are obtained. Furthermore, the proposed process is verified by several machining experiments for achieving nine-array hexagonal micro cavities with top side length of 300 µm, bottom side length of 150 µm, and depth of 112 µm or 120 µm. In the experiments, a chip hump accumulates on the electrode tips like the built-up edge in mechanical machining under the conditions of brass workpieces, copper electrodes and the dielectric of deionized water. The accumulated hump can be avoided by replacing the water dielectric by an oil dielectric.

  8. Evaluation on machined surface of hardened stainless steel generated by hard turning using coated carbide tools with wiper geometry

    International Nuclear Information System (INIS)

    Noordin, M.Y.; Kurniawan, D.; Sharif, S.

    2007-01-01

    Hard turning has been explored to be the finish machining operation for parts made of hardened steel. Its feasibility is determined partially by the quality of the resulting machined surface. This study evaluates the surface integrity of martensitic stainless steel (48 HRC) resulting from hard turning using coated carbide tool with wiper geometry at various cutting speed and feed and compares to that obtained using coated carbide tool with conventional geometry. The wiper coated carbide tool is able to produce machined surface which is of finer finish (Ra is finer than 0.4 μm at most cutting parameters) and yet is similarly inducing only minor microstructural alteration compared to its conventional counterpart. From the view of the chip morphology where continuous type of chip is desired rather than sawtooth chip type, the wiper tool generates continuous chip at almost similar range of cutting parameters compared to the case when using conventional tool. Additionally, the use of wiper tool also induces the preferred compressive residual stress at the machined surface. (author)

  9. A long-term risk management tool for electricity markets using swarm intelligence

    International Nuclear Information System (INIS)

    Azevedo, F.; Vale, Z.A.; Khodr, H.M.; Oliveira, P.B. Moura

    2010-01-01

    This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn. (author)

  10. SNMP-SI: A Network Management Tool Based on Slow Intelligence System Approach

    Science.gov (United States)

    Colace, Francesco; de Santo, Massimo; Ferrandino, Salvatore

    The last decade has witnessed an intense spread of computer networks that has been further accelerated with the introduction of wireless networks. Simultaneously with, this growth has increased significantly the problems of network management. Especially in small companies, where there is no provision of personnel assigned to these tasks, the management of such networks is often complex and malfunctions can have significant impacts on their businesses. A possible solution is the adoption of Simple Network Management Protocol. Simple Network Management Protocol (SNMP) is a standard protocol used to exchange network management information. It is part of the Transmission Control Protocol/Internet Protocol (TCP/IP) protocol suite. SNMP provides a tool for network administrators to manage network performance, find and solve network problems, and plan for network growth. SNMP has a big disadvantage: its simple design means that the information it deals with is neither detailed nor well organized enough to deal with the expanding modern networking requirements. Over the past years much efforts has been given to improve the lack of Simple Network Management Protocol and new frameworks has been developed: A promising approach involves the use of Ontology. This is the starting point of this paper where a novel approach to the network management based on the use of the Slow Intelligence System methodologies and Ontology based techniques is proposed. Slow Intelligence Systems is a general-purpose systems characterized by being able to improve performance over time through a process involving enumeration, propagation, adaptation, elimination and concentration. Therefore, the proposed approach aims to develop a system able to acquire, according to an SNMP standard, information from the various hosts that are in the managed networks and apply solutions in order to solve problems. To check the feasibility of this model first experimental results in a real scenario are showed.

  11. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  12. Finite Element Modelling of the effect of tool rake angle on tool temperature and cutting force during high speed machining of AISI 4340 steel

    International Nuclear Information System (INIS)

    Sulaiman, S; Roshan, A; Ariffin, M K A

    2013-01-01

    In this paper, a Finite Element Method (FEM) based on the ABAQUS explicit software which involves Johnson-Cook material model was used to simulate cutting force and tool temperature during high speed machining (HSM) of AISI 4340 steel. In this simulation work, a tool rake angle ranging from 0° to 20° and a range of cutting speeds between 300 to 550 m/min was investigated. The purpose of this simulation analysis was to find optimum tool rake angle where cutting force is smallest as well as tool temperature is lowest during high speed machining. It was found that cutting forces to have a decreasing trend as rake angle increased to positive direction. The optimum rake angle observed between 10° and 18° due to decrease of cutting force as 20% for all simulated cutting speeds. In addition, increasing cutting tool rake angle over its optimum value had negative influence on tool's performance and led to an increase in cutting temperature. The results give a better understanding and recognition of the cutting tool design for high speed machining processes

  13. 1st International Conference on Intelligent Computing, Communication and Devices

    CERN Document Server

    Patnaik, Srikanta; Ichalkaranje, Nikhil

    2015-01-01

    In the history of mankind, three revolutions which impact the human life are the tool-making revolution, agricultural revolution and industrial revolution. They have transformed not only the economy and civilization but the overall development of the society. Probably, intelligence revolution is the next revolution, which the society will perceive in the next 10 years. ICCD-2014 covers all dimensions of intelligent sciences, i.e. Intelligent Computing, Intelligent Communication and Intelligent Devices. This volume covers contributions from Intelligent Communication which are from the areas such as Communications and Wireless Ad Hoc & Sensor Networks, Speech & Natural Language Processing, including Signal, Image and Video Processing and Mobile broadband and Optical networks, which are the key to the ground-breaking inventions to intelligent communication technologies. Secondly, Intelligent Device is any type of equipment, instrument, or machine that has its own computing capability. Contributions from ...

  14. iPat: intelligent prediction and association tool for genomic research.

    Science.gov (United States)

    Chen, Chunpeng James; Zhang, Zhiwu

    2018-06-01

    The ultimate goal of genomic research is to effectively predict phenotypes from genotypes so that medical management can improve human health and molecular breeding can increase agricultural production. Genomic prediction or selection (GS) plays a complementary role to genome-wide association studies (GWAS), which is the primary method to identify genes underlying phenotypes. Unfortunately, most computing tools cannot perform data analyses for both GWAS and GS. Furthermore, the majority of these tools are executed through a command-line interface (CLI), which requires programming skills. Non-programmers struggle to use them efficiently because of the steep learning curves and zero tolerance for data formats and mistakes when inputting keywords and parameters. To address these problems, this study developed a software package, named the Intelligent Prediction and Association Tool (iPat), with a user-friendly graphical user interface. With iPat, GWAS or GS can be performed using a pointing device to simply drag and/or click on graphical elements to specify input data files, choose input parameters and select analytical models. Models available to users include those implemented in third party CLI packages such as GAPIT, PLINK, FarmCPU, BLINK, rrBLUP and BGLR. Users can choose any data format and conduct analyses with any of these packages. File conversions are automatically conducted for specified input data and selected packages. A GWAS-assisted genomic prediction method was implemented to perform genomic prediction using any GWAS method such as FarmCPU. iPat was written in Java for adaptation to multiple operating systems including Windows, Mac and Linux. The iPat executable file, user manual, tutorials and example datasets are freely available at http://zzlab.net/iPat. zhiwu.zhang@wsu.edu.

  15. Optimizing the way kinematical feed chains with great distance between slides are chosen for CNC machine tools

    Science.gov (United States)

    Lucian, P.; Gheorghe, S.

    2017-08-01

    This paper presents a new method, based on FRISCO formula, for optimizing the choice of the best control system for kinematical feed chains with great distance between slides used in computer numerical controlled machine tools. Such machines are usually, but not limited to, used for machining large and complex parts (mostly in the aviation industry) or complex casting molds. For such machine tools the kinematic feed chains are arranged in a dual-parallel drive structure that allows the mobile element to be moved by the two kinematical branches and their related control systems. Such an arrangement allows for high speed and high rigidity (a critical requirement for precision machining) during the machining process. A significant issue for such an arrangement it’s the ability of the two parallel control systems to follow the same trajectory accurately in order to address this issue it is necessary to achieve synchronous motion control for the two kinematical branches ensuring that the correct perpendicular position it’s kept by the mobile element during its motion on the two slides.

  16. Analysis of the application of poly-nanocrystalline diamond tools for ultra precision machining of steel with ultrasonic assistance

    Science.gov (United States)

    Doetz, M.; Dambon, O.; Klocke, F.; Bulla, B.; Schottka, K.; Robertson, D. J.

    2017-10-01

    Ultra-precision diamond turning enables the manufacturing of parts with mirror-like surfaces and highest form accuracies out of non-ferrous, a few crystalline and plastic materials. Furthermore, an ultrasonic assistance has the ability to push these boundaries and enables the machining of materials like steel, which is not possible in a conventional way due to the excessive tool wear caused by the affinity of carbon to iron. Usually monocrystalline diamonds tools are applied due to their unsurpassed cutting edge properties. New cutting tool material developments have shown that it is possible to produce tools made of nano-polycrystalline diamonds with cutting edges equivalent to monocrystalline diamonds. In nano-polycrystalline diamonds ultra-fine grains of a few tens of nanometers are firmly and directly bonded together creating an unisotropic structure. The properties of this material are described to be isotropic, harder and tougher than those of the monocrystalline diamonds, which are unisotropic. This publication will present machining results from the newest investigations of the process potential of this new polycrystalline cutting material. In order to provide a baseline with which to characterize the cutting material cutting experiments on different conventional machinable materials like Cooper or Aluminum are performed. The results provide information on the roughness and the topography of the surface focusing on the comparison to the results while machining with monocrystalline diamond. Furthermore, the cutting material is tested in machining steel with ultrasonic assistance with a focus on tool life time and surface roughness. An outlook on the machinability of other materials will be given.

  17. Study on lean thinking among MSMEs in the Machine tool sector in India

    Science.gov (United States)

    Priyaadarshini, R. G.; Sathish Kumar, V. R.; Aishwarya Rajlakshmi, S.

    2018-02-01

    In the era of stiff competition and customer expectations, manufacturing organizations across the world are struggling hard to minimize their costs and maximise their performance. Micro, Small and Medium enterprises (MSMEs), who are dependent on large corporate for business and support have a tall task of keeping pace quality in processes and output. They are in the constant vigil to adopt new systems and practices so that they can minimise their cost and maximize the productivity. This study has been conducted in the machine tool sector of Coimbatore, India; which houses more than 9000 companies and offers employment to over one lakh employees. They have a tremendous pressure to use scientific processes to increase their product quality and productivity. While Lean manufacturing has been the thrust to improve the competitiveness among MSMEs in India, this study has attempted to understand their attitude towards lean management and understand the extent to which companies practice lean tools and practices. It has been found that most of the organizations in the study possess a culture of lean thinking and possess the support of top management and employees also towards the initiative. It is also seen that the organizations that incorporated lean in their daily operations have been able to scale up their productivity.

  18. Machine learning-based assessment tool for imbalance and vestibular dysfunction with virtual reality rehabilitation system.

    Science.gov (United States)

    Yeh, Shih-Ching; Huang, Ming-Chun; Wang, Pa-Chun; Fang, Te-Yung; Su, Mu-Chun; Tsai, Po-Yi; Rizzo, Albert

    2014-10-01

    Dizziness is a major consequence of imbalance and vestibular dysfunction. Compared to surgery and drug treatments, balance training is non-invasive and more desired. However, training exercises are usually tedious and the assessment tool is insufficient to diagnose patient's severity rapidly. An interactive virtual reality (VR) game-based rehabilitation program that adopted Cawthorne-Cooksey exercises, and a sensor-based measuring system were introduced. To verify the therapeutic effect, a clinical experiment with 48 patients and 36 normal subjects was conducted. Quantified balance indices were measured and analyzed by statistical tools and a Support Vector Machine (SVM) classifier. In terms of balance indices, patients who completed the training process are progressed and the difference between normal subjects and patients is obvious. Further analysis by SVM classifier show that the accuracy of recognizing the differences between patients and normal subject is feasible, and these results can be used to evaluate patients' severity and make rapid assessment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  19. Effect of cutting parameters on sustainable machining performance of coated carbide tool in dry turning process of stainless steel 316

    Science.gov (United States)

    Bagaber, Salem A.; Yusoff, Ahmed Razlan

    2017-04-01

    The manufacturing industry aims to produce many products of high quality with relatively less cost and time. Different cutting parameters affect the machining performance of surface roughness, cutting force, and material removal rate. Nevertheless, a few studies reported on the effects of sustainable factors such as power consumed, cycle time during machining, and tool life on the dry turning of AISI 316. The present study aims to evaluate the machining performance of coated carbide in the machining of hard steel AISI 316 under the dry turning process. The influence of cutting parameters of cutting speed, feed rate, and depth of cut with their five (5) levels is established by a central composite design. Highly significant parameters were determined by analysis of variance (ANOVA), and the main effects of power consumed and time during machining, surface roughness, and tool wear were observed. Results showed that the cutting speed was proportional to power consumption and tool wear. Meanwhile, insignificant to surface roughness, feed rate most significantly affected surface roughness and power consumption followed by depth of cut.

  20. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Verhaegh, W.F.J.; Aarts, E.H.L.; Korst, J.H.M.

    2004-01-01

    In this chapter, we discuss the new paradigm for user-centered computing known as ambient intelligence and its relation with methods and techniques from the field of computational intelligence, including problem solving, machine learning, and expert systems.

  1. Artificial Intelligence Tools for Scaling Up of High Shear Wet Granulation Process.

    Science.gov (United States)

    Landin, Mariana

    2017-01-01

    The results presented in this article demonstrate the potential of artificial intelligence tools for predicting the endpoint of the granulation process in high-speed mixer granulators of different scales from 25L to 600L. The combination of neurofuzzy logic and gene expression programing technologies allowed the modeling of the impeller power as a function of operation conditions and wet granule properties, establishing the critical variables that affect the response and obtaining a unique experimental polynomial equation (transparent model) of high predictability (R 2 > 86.78%) for all size equipment. Gene expression programing allowed the modeling of the granulation process for granulators of similar and dissimilar geometries and can be improved by implementing additional characteristics of the process, as composition variables or operation parameters (e.g., batch size, chopper speed). The principles and the methodology proposed here can be applied to understand and control manufacturing process, using any other granulation equipment, including continuous granulation processes. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  2. Integrating and analyzing medical and environmental data using ETL and Business Intelligence tools

    Science.gov (United States)

    Villar, Alejandro; Zarrabeitia, María T.; Fdez-Arroyabe, Pablo; Santurtún, Ana

    2018-06-01

    Processing data that originates from different sources (such as environmental and medical data) can prove to be a difficult task, due to the heterogeneity of variables, storage systems, and file formats that can be used. Moreover, once the amount of data reaches a certain threshold, conventional mining methods (based on spreadsheets or statistical software) become cumbersome or even impossible to apply. Data Extract, Transform, and Load (ETL) solutions provide a framework to normalize and integrate heterogeneous data into a local data store. Additionally, the application of Online Analytical Processing (OLAP), a set of Business Intelligence (BI) methodologies and practices for multidimensional data analysis, can be an invaluable tool for its examination and mining. In this article, we describe a solution based on an ETL + OLAP tandem used for the on-the-fly analysis of tens of millions of individual medical, meteorological, and air quality observations from 16 provinces in Spain provided by 20 different national and regional entities in a diverse array for file types and formats, with the intention of evaluating the effect of several environmental variables on human health in future studies. Our work shows how a sizable amount of data, spread across a wide range of file formats and structures, and originating from a number of different sources belonging to various business domains, can be integrated in a single system that researchers can use for global data analysis and mining.

  3. Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

    International Nuclear Information System (INIS)

    Ahmadi, Rouhollah; Khamehchi, Ehsan

    2013-01-01

    Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks and fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data

  4. A prototype system for perinatal knowledge engineering using an artificial intelligence tool.

    Science.gov (United States)

    Sokol, R J; Chik, L

    1988-01-01

    Though several perinatal expert systems are extant, the use of artificial intelligence has, as yet, had minimal impact in medical computing. In this evaluation of the potential of AI techniques in the development of a computer based "Perinatal Consultant," a "top down" approach to the development of a perinatal knowledge base was taken, using as a source for such a knowledge base a 30-page manuscript of a chapter concerning high risk pregnancy. The UNIX utility "style" was used to parse sentences and obtain key words and phrases, both as part of a natural language interface and to identify key perinatal concepts. Compared with the "gold standard" of sentences containing key facts as chosen by the experts, a semiautomated method using a nonmedical speller to identify key words and phrases in context functioned with a sensitivity of 79%, i.e., approximately 8 in 10 key sentences were detected as the basis for PROLOG, rules and facts for the knowledge base. These encouraging results suggest that functional perinatal expert systems may well be expedited by using programming utilities in conjunction with AI tools and published literature.

  5. Integrating and analyzing medical and environmental data using ETL and Business Intelligence tools.

    Science.gov (United States)

    Villar, Alejandro; Zarrabeitia, María T; Fdez-Arroyabe, Pablo; Santurtún, Ana

    2018-03-07

    Processing data that originates from different sources (such as environmental and medical data) can prove to be a difficult task, due to the heterogeneity of variables, storage systems, and file formats that can be used. Moreover, once the amount of data reaches a certain threshold, conventional mining methods (based on spreadsheets or statistical software) become cumbersome or even impossible to apply. Data Extract, Transform, and Load (ETL) solutions provide a framework to normalize and integrate heterogeneous data into a local data store. Additionally, the application of Online Analytical Processing (OLAP), a set of Business Intelligence (BI) methodologies and practices for multidimensional data analysis, can be an invaluable tool for its examination and mining. In this article, we describe a solution based on an ETL + OLAP tandem used for the on-the-fly analysis of tens of millions of individual medical, meteorological, and air quality observations from 16 provinces in Spain provided by 20 different national and regional entities in a diverse array for file types and formats, with the intention of evaluating the effect of several environmental variables on human health in future studies. Our work shows how a sizable amount of data, spread across a wide range of file formats and structures, and originating from a number of different sources belonging to various business domains, can be integrated in a single system that researchers can use for global data analysis and mining.

  6. Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

    Energy Technology Data Exchange (ETDEWEB)

    Ahmadi, Rouhollah, E-mail: rouhollahahmadi@yahoo.com [Amirkabir University of Technology, PhD Student at Reservoir Engineering, Department of Petroleum Engineering (Iran, Islamic Republic of); Khamehchi, Ehsan [Amirkabir University of Technology, Faculty of Petroleum Engineering (Iran, Islamic Republic of)

    2013-12-15

    Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks and fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data.

  7. Evaluating the Impact of Business Intelligence Tools on Organizational Performance in Food and Groceries Retail

    Directory of Open Access Journals (Sweden)

    Sailaja Venuturumilli

    2016-01-01

    Full Text Available While retailers are spending a significant portion of its information technology (IT budgets on BI and related technology in order to handle the ever increasing volumes of data, the actual benefits derived from these tools needs to be explored. The study focuses on the organized food and groceries retail, and explores benefits of business intelligence (BI and hypothesis‟s a structural causal relationship among its intrinsic attributes, and impact on organizational performance. A focus group of selected senior marketing employees was used to develop and validate the research model. Based on findings from the literature survey and focus group, a survey instrument was developed to empirically validate the research model. Data collected from senior marketing executives and managers from six organized food and groceries retail was analyzed using exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. Five major categories of BI were identified: (1 access to data quality, (2 improved managerial effectiveness, (3 improved operational effectiveness, (4 improved customer orientation and (5 improved organizational efficiency. From the structural causal relationship analysis, a significant relationship was found between intrinsic attributes and benefits of BI and data quality. The structural equation model also suggests a significant relationship between BI and data quality on organizational performance.

  8. Integrating and analyzing medical and environmental data using ETL and Business Intelligence tools

    Science.gov (United States)

    Villar, Alejandro; Zarrabeitia, María T.; Fdez-Arroyabe, Pablo; Santurtún, Ana

    2018-03-01

    Processing data that originates from different sources (such as environmental and medical data) can prove to be a difficult task, due to the heterogeneity of variables, storage systems, and file formats that can be used. Moreover, once the amount of data reaches a certain threshold, conventional mining methods (based on spreadsheets or statistical software) become cumbersome or even impossible to apply. Data Extract, Transform, and Load (ETL) solutions provide a framework to normalize and integrate heterogeneous data into a local data store. Additionally, the application of Online Analytical Processing (OLAP), a set of Business Intelligence (BI) methodologies and practices for multidimensional data analysis, can be an invaluable tool for its examination and mining. In this article, we describe a solution based on an ETL + OLAP tandem used for the on-the-fly analysis of tens of millions of individual medical, meteorological, and air quality observations from 16 provinces in Spain provided by 20 different national and regional entities in a diverse array for file types and formats, with the intention of evaluating the effect of several environmental variables on human health in future studies. Our work shows how a sizable amount of data, spread across a wide range of file formats and structures, and originating from a number of different sources belonging to various business domains, can be integrated in a single system that researchers can use for global data analysis and mining.

  9. Study on Surface Integrity of AISI 1045 Carbon Steel when machined by Carbide Cutting Tool under wet conditions

    Directory of Open Access Journals (Sweden)

    Tamin N. Fauzi

    2017-01-01

    Full Text Available This paper presents the evaluation of surface roughness and roughness profiles when machining carbon steel under wet conditions with low and high cutting speeds. The workpiece materials and cutting tools selected in this research were AISI 1045 carbon steel and canela carbide inserts graded PM25, respectively. The cutting tools undergo machining tests by CNC turning operations and their performances were evaluated by their surface roughness value and observation of the surface roughness profile. The machining tests were held at varied cutting speeds of 35 to 53 m/min, feed rate of 0.15 to 0.50 mm/rev and a constant depth of cut of 1 mm. From the analysis, it was found that surface roughness increased as the feed rate increased. Varian of surface roughness was suspected due to interaction between cutting speeds and feed rates as well as nose radius conditions; whether from tool wear or the formation of a built-up edge. This study helps us understand the effect of cutting speed and feed rate on surface integrity, when machining AISI 1045 carbon steel using carbide cutting tools, under wet cutting conditions.

  10. Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh-Bonab plain aquifer, Iran

    Science.gov (United States)

    Fijani, Elham; Nadiri, Ata Allah; Asghari Moghaddam, Asghar; Tsai, Frank T.-C.; Dixon, Barnali

    2013-10-01

    Contamination of wells with nitrate-N (NO3-N) poses various threats to human health. Contamination of groundwater is a complex process and full of uncertainty in regional scale. Development of an integrative vulnerability assessment methodology can be useful to effectively manage (including prioritization of limited resource allocation to monitor high risk areas) and protect this valuable freshwater source. This study introduces a supervised committee machine with artificial intelligence (SCMAI) model to improve the DRASTIC method for groundwater vulnerability assessment for the Maragheh-Bonab plain aquifer in Iran. Four different AI models are considered in the SCMAI model, whose input is the DRASTIC parameters. The SCMAI model improves the committee machine artificial intelligence (CMAI) model by replacing the linear combination in the CMAI with a nonlinear supervised ANN framework. To calibrate the AI models, NO3-N concentration data are divided in two datasets for the training and validation purposes. The target value of the AI models in the training step is the corrected vulnerability indices that relate to the first NO3-N concentration dataset. After model training, the AI models are verified by the second NO3-N concentration dataset. The results show that the four AI models are able to improve the DRASTIC method. Since the best AI model performance is not dominant, the SCMAI model is considered to combine the advantages of individual AI models to achieve the optimal performance. The SCMAI method re-predicts the groundwater vulnerability based on the different AI model prediction values. The results show that the SCMAI outperforms individual AI models and committee machine with artificial intelligence (CMAI) model. The SCMAI model ensures that no water well with high NO3-N levels would be classified as low risk and vice versa. The study concludes that the SCMAI model is an effective model to improve the DRASTIC model and provides a confident estimate of the

  11. Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Alessandra Caggiano

    2018-03-01

    Full Text Available Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA is proposed. PCA allowed to identify a smaller number of features (k = 2 features, the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear (VBmax was achieved, with predicted values very close to the measured tool wear values.

  12. Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition.

    Science.gov (United States)

    Caggiano, Alessandra

    2018-03-09

    Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA) is proposed. PCA allowed to identify a smaller number of features ( k = 2 features), the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear ( VB max ) was achieved, with predicted values very close to the measured tool wear values.

  13. Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition

    Science.gov (United States)

    2018-01-01

    Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA) is proposed. PCA allowed to identify a smaller number of features (k = 2 features), the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear (VBmax) was achieved, with predicted values very close to the measured tool wear values. PMID:29522443

  14. Thermo-energetic design of machine tools a systemic approach to solve the conflict between power efficiency, accuracy and productivity demonstrated at the example of machining production

    CERN Document Server

    2015-01-01

    The approach to the solution within the CRC/TR 96 financed by the German Research Foundation DFG aims at measures that will allow manufacturing accuracy to be maintained under thermally unstable conditions with increased productivity, without an additional demand for energy for tempering. The challenge of research in the CRC/TR 96 derives from the attempt to satisfy the conflicting goals of reducing energy consumption and increasing accuracy and productivity in machining. In the current research performed in 19 subprojects within the scope of the CRC/TR 96, correction and compensation solutions that influence the thermo-elastic machine tool behaviour efficiently and are oriented along the thermo-elastic functional chain are explored and implemented. As part of this general objective, the following issues must be researched and engineered in an interdisciplinary setting and brought together into useful overall solutions:   1.  Providing the modelling fundamentals to calculate the heat fluxes and the resulti...

  15. Energy efficient drives and control engineering. Intelligent machine and plant concepts for manufacturing; Energieeffiziente Antriebs- und Steuerungstechnik. Intelligente Maschinen- und Anlagenkonzepte fuer die Fertigung

    Energy Technology Data Exchange (ETDEWEB)

    Fahrbach, Christian; Frank, Klaus; Haack, Steffen; Schemm, Eberhardt; Wittschen, Wiebke

    2010-07-01

    The book discusses the potential of intelligent and energy-efficient drive and control concepts. It shows that energy efficient components - pumps, motors, or speed-controlled pump drives - may result in a double-digit reduction of energy consumption. The effect is even more pronounced when the system is opotimized as a whole. If energy-efficient components are combined so that a direct energy flow will result, energy will be converted on demand, i.e. the right amount at the right time. The book also discusses how these design options can be applied in the various phases of the machine life cycle.

  16. Assessing Speech Intelligibility in Children with Hearing Loss: Toward Revitalizing a Valuable Clinical Tool

    Science.gov (United States)

    Ertmer, David J.

    2011-01-01

    Background: Newborn hearing screening, early intervention programs, and advancements in cochlear implant and hearing aid technology have greatly increased opportunities for children with hearing loss to become intelligible talkers. Optimizing speech intelligibility requires that progress be monitored closely. Although direct assessment of…

  17. A Comparative Analysis of the Use of Competitive Intelligence Tools in a Multinational Corporation

    Science.gov (United States)

    Breese-Vitelli, Jennifer

    2011-01-01

    With the growth of the global economy, organizations large and small are increasingly recognizing that competitive intelligence (CI) is essential to compete in industry. Competitive intelligence is used to gain an advantage in commerce and is useful for analyzing a company's strategic industry position. To remain current and profitable,…

  18. STAR- A SIMPLE TOOL FOR AUTOMATED REASONING SUPPORTING HYBRID APPLICATIONS OF ARTIFICIAL INTELLIGENCE (UNIX VERSION)

    Science.gov (United States)

    Borchardt, G. C.

    1994-01-01

    The Simple Tool for Automated Reasoning program (STAR) is an interactive, interpreted programming language for the development and operation of artificial intelligence (AI) application systems. STAR provides an environment for integrating traditional AI symbolic processing with functions and data structures defined in compiled languages such as C, FORTRAN and PASCAL. This type of integration occurs in a number of AI applications including interpretation of numerical sensor data, construction of intelligent user interfaces to existing compiled software packages, and coupling AI techniques with numerical simulation techniques and control systems software. The STAR language was created as part of an AI project for the evaluation of imaging spectrometer data at NASA's Jet Propulsion Laboratory. Programming in STAR is similar to other symbolic processing languages such as LISP and CLIP. STAR includes seven primitive data types and associated operations for the manipulation of these structures. A semantic network is used to organize data in STAR, with capabilities for inheritance of values and generation of side effects. The AI knowledge base of STAR can be a simple repository of records or it can be a highly interdependent association of implicit and explicit components. The symbolic processing environment of STAR may be extended by linking the interpreter with functions defined in conventional compiled languages. These external routines interact with STAR through function calls in either direction, and through the exchange of references to data structures. The hybrid knowledge base may thus be accessed and processed in general by either side of the application. STAR is initially used to link externally compiled routines and data structures. It is then invoked to interpret the STAR rules and symbolic structures. In a typical interactive session, the user enters an expression to be evaluated, STAR parses the input, evaluates the expression, performs any file input

  19. STAR- A SIMPLE TOOL FOR AUTOMATED REASONING SUPPORTING HYBRID APPLICATIONS OF ARTIFICIAL INTELLIGENCE (DEC VAX VERSION)

    Science.gov (United States)

    Borchardt, G. C.

    1994-01-01

    The Simple Tool for Automated Reasoning program (STAR) is an interactive, interpreted programming language for the development and operation of artificial intelligence (AI) application systems. STAR provides an environment for integrating traditional AI symbolic processing with functions and data structures defined in compiled languages such as C, FORTRAN and PASCAL. This type of integration occurs in a number of AI applications including interpretation of numerical sensor data, construction of intelligent user interfaces to existing compiled software packages, and coupling AI techniques with numerical simulation techniques and control systems software. The STAR language was created as part of an AI project for the evaluation of imaging spectrometer data at NASA's Jet Propulsion Laboratory. Programming in STAR is similar to other symbolic processing languages such as LISP and CLIP. STAR includes seven primitive data types and associated operations for the manipulation of these structures. A semantic network is used to organize data in STAR, with capabilities for inheritance of values and generation of side effects. The AI knowledge base of STAR can be a simple repository of records or it can be a highly interdependent association of implicit and explicit components. The symbolic processing environment of STAR may be extended by linking the interpreter with functions defined in conventional compiled languages. These external routines interact with STAR through function calls in either direction, and through the exchange of references to data structures. The hybrid knowledge base may thus be accessed and processed in general by either side of the application. STAR is initially used to link externally compiled routines and data structures. It is then invoked to interpret the STAR rules and symbolic structures. In a typical interactive session, the user enters an expression to be evaluated, STAR parses the input, evaluates the expression, performs any file input

  20. STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

    Science.gov (United States)

    ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

  1. Prediction of ttt curves of cold working tool steels using support vector machine model

    Science.gov (United States)

    Pillai, Nandakumar; Karthikeyan, R., Dr.

    2018-04-01

    The cold working tool steels are of high carbon steels with metallic alloy additions which impart higher hardenability, abrasion resistance and less distortion in quenching. The microstructure changes occurring in tool steel during heat treatment is of very much importance as the final properties of the steel depends upon these changes occurred during the process. In order to obtain the desired performance the alloy constituents and its ratio plays a vital role as the steel transformation itself is complex in nature and depends very much upon the time and temperature. The proper treatment can deliver satisfactory results, at the same time process deviation can completely spoil the results. So knowing time temperature transformation (TTT) of phases is very critical which varies for each type depending upon its constituents and proportion range. To obtain adequate post heat treatment properties the percentage of retained austenite should be lower and metallic carbides obtained should be fine in nature. Support vector machine is a computational model which can learn from the observed data and use these to predict or solve using mathematical model. Back propagation feedback network will be created and trained for further solutions. The points on the TTT curve for the known transformations curves are used to plot the curves for different materials. These data will be trained to predict TTT curves for other steels having similar alloying constituents but with different proportion range. The proposed methodology can be used for prediction of TTT curves for cold working steels and can be used for prediction of phases for different heat treatment methods.

  2. Applying CBR to machine tool product configuration design oriented to customer requirements

    Science.gov (United States)

    Wang, Pengjia; Gong, Yadong; Xie, Hualong; Liu, Yongxian; Nee, Andrew Yehching

    2017-01-01

    Product customization is a trend in the current market-oriented manufacturing environment. However, deduction from customer requirements to design results and evaluation of design alternatives are still heavily reliant on the designer's experience and knowledge. To solve the problem of fuzziness and uncertainty of customer requirements in product configuration, an analysis method based on the grey rough model is presented. The customer requirements can be converted into technical characteristics effectively. In addition, an optimization decision model for product planning is established to help the enterprises select the key technical characteristics under the constraints of cost and time to serve the customer to maximal satisfaction. A new case retrieval approach that combines the self-organizing map and fuzzy similarity priority ratio method is proposed in case-based design. The self-organizing map can reduce the retrieval range and increase the retrieval efficiency, and the fuzzy similarity priority ratio method can evaluate the similarity of cases comprehensively. To ensure that the final case has the best overall performance, an evaluation method of similar cases based on grey correlation analysis is proposed to evaluate similar cases to select the most suitable case. Furthermore, a computer-aided system is developed using MATLAB GUI to assist the product configuration design. The actual example and result on an ETC series machine tool product show that the proposed method is effective, rapid and accurate in the process of product configuration. The proposed methodology provides a detailed instruction for the product configuration design oriented to customer requirements.

  3. Inventory management performance in machine tool SMEs: What factors do influence them?

    Directory of Open Access Journals (Sweden)

    Rajeev Narayana Pillai

    2010-12-01

    Full Text Available Small and Medium Enterprises (SMEs are one of the principal driving forces in the development of an economy because of its significant contribution in terms of number of enterprises, employment, output and exports in most developing as well as developed countries. But SMEs, particularly in developing countries like India, face constraints in key areas such as technology, finance, marketing and human resources. Moreover these SMEs have been exposed to intense competition since early 1990s because of globalization. However, globalization, the process of continuing integration of the countries in the world has opened up new opportunities for SMEs of developing countries to cater to wider international market which brings out the need for these SMEs to develop competitiveness for their survival as well as growth. It is observed from literature that pursuing appropriate IM practice is one of the ways of acquiring competitiveness among others, by effectively managing and minimizing inventory investment. Inventory management can therefore be one of the crucial determinants of competitiveness as well as operational performance of SMEs in inventory intensive manufacturing industries. The key issue is whether Indian SMEs pursue better IM practices with an intension to reduce their inventory cost and enhance their competitiveness. If so, what are the IM practices pursued by these enterprises? What are the factors which influence the inventory cost and IM performance of enterprises? These questions have been addressed in this study with reference to machine tool SMEs located in the city of Bangalore, India.

  4. MODEL OF THE QUALITY MANAGEMENT SYSTEM OF A MACHINE TOOL COMPANY

    Directory of Open Access Journals (Sweden)

    Катерина Вікторівна КОЛЕСНІКОВА

    2016-02-01

    Full Text Available Development of models and methods such that would improve the competitive position of enterprises by improving management processes is an important task of project management. Lack of project management within the information technology and continuous improvement of methods for the management of the environment, interaction, community, value and trust, based on the strategic objectives of enterprises and based on models that take into account the relationship of the system, resulting in significant material and resource costs. In the current work the improvement of the quality management system machine-tool company HC MIKRON® and proved that the introduction of new processes critical analysis requirements for products, support processes of the products to consumers and enterprises in the formation of a system of responsibility, division of responsibilities and reporting (according to ISO 9001: 2009 is an important scientific and reasonable step to improve the level of technological maturity and structural modernization of enterprise management. For the improved structure of the analysis model and test the properties of ergodicity, as a condition of efficiency, a new quality management system.

  5. Numerical Control Machine Tool Fault Diagnosis Using Hybrid Stationary Subspace Analysis and Least Squares Support Vector Machine with a Single Sensor

    Directory of Open Access Journals (Sweden)

    Chen Gao

    2017-03-01

    Full Text Available Tool fault diagnosis in numerical control (NC machines plays a significant role in ensuring manufacturing quality. However, current methods of tool fault diagnosis lack accuracy. Therefore, in the present paper, a fault diagnosis method was proposed based on stationary subspace analysis (SSA and least squares support vector machine (LS-SVM using only a single sensor. First, SSA was used to extract stationary and non-stationary sources from multi-dimensional signals without the need for independency and without prior information of the source signals, after the dimensionality of the vibration signal observed by a single sensor was expanded by phase space reconstruction technique. Subsequently, 10 dimensionless parameters in the time-frequency domain for non-stationary sources were calculated to generate samples to train the LS-SVM. Finally, the measured vibration signals from tools of an unknown state and their non-stationary sources were separated by SSA to serve as test samples for the trained SVM. The experimental validation demonstrated that the proposed method has better diagnosis accuracy than three previous methods based on LS-SVM alone, Principal component analysis and LS-SVM or on SSA and Linear discriminant analysis.

  6. Dynamic analysis and vibration testing of CFRP drive-line system used in heavy-duty machine tool

    OpenAIRE

    Mo Yang; Lin Gui; Yefa Hu; Guoping Ding; Chunsheng Song

    2018-01-01

    Low critical rotary speed and large vibration in the metal drive-line system of heavy-duty machine tool affect the machining precision seriously. Replacing metal drive-line with the CFRP drive-line can effectively solve this problem. Based on the composite laminated theory and the transfer matrix method (TMM), this paper puts forward a modified TMM to analyze dynamic characteristics of CFRP drive-line system. With this modified TMM, the CFRP drive-line of a heavy vertical miller is analyzed. ...

  7. IQARIS : a tool for the intelligent querying, analysis, and retrieval from information systems

    International Nuclear Information System (INIS)

    Hummel, J. R.; Silver, R. B.

    2002-01-01

    Information glut is one of the primary characteristics of the electronic age. Managing such large volumes of information (e.g., keeping track of the types, where they are, their relationships, who controls them, etc.) can be done efficiently with an intelligent, user-oriented information management system. The purpose of this paper is to describe a concept for managing information resources based on an intelligent information technology system developed by the Argonne National Laboratory for managing digital libraries. The Argonne system, Intelligent Query (IQ), enables users to query digital libraries and view the holdings that match the query from different perspectives

  8. Comparison of Advanced Machine Learning Tools for Disruption Prediction and Disruption Studies

    Czech Academy of Sciences Publication Activity Database

    Odstrčil, Michal; Murari, A.; Mlynář, Jan

    2013-01-01

    Roč. 41, č. 7 (2013), s. 1751-1759 ISSN 0093-3813 R&D Projects: GA ČR GAP205/10/2055 Institutional support: RVO:61389021 Keywords : Learning Machines * Support Vector Machines * Neural Network * ASDEX Upgrade * JET * Disruption mitigation * Tokamaks * ITER Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 0.950, year: 2013

  9. Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module

    Directory of Open Access Journals (Sweden)

    Yuan-Chieh Lo

    2018-02-01

    Full Text Available Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe. Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t| °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR technique and implemented into the real-time embedded system.

  10. NETS - A NEURAL NETWORK DEVELOPMENT TOOL, VERSION 3.0 (MACHINE INDEPENDENT VERSION)

    Science.gov (United States)

    Baffes, P. T.

    1994-01-01

    NETS, A Tool for the Development and Evaluation of Neural Networks, provides a simulation of Neural Network algorithms plus an environment for developing such algorithms. Neural Networks are a class of systems modeled after the human brain. Artificial Neural Networks are formed from hundreds or thousands of simulated neurons, connected to each other in a manner similar to brain neurons. Problems which involve pattern matching readily fit the class of problems which NETS is designed to solve. NETS uses the back propagation learning method for all of the networks which it creates. The nodes of a network are usually grouped together into clumps called layers. Generally, a network will have an input layer through which the various environment stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to some features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. NETS allows the user to customize the patterns of connections between layers of a network. NETS also provides features for saving the weight values of a network during the learning process, which allows for more precise control over the learning process. NETS is an interpreter. Its method of execution is the familiar "read-evaluate-print" loop found in interpreted languages such as BASIC and LISP. The user is presented with a prompt which is the simulator's way of asking for input. After a command is issued, NETS will attempt to evaluate the command, which may produce more prompts requesting specific information or an error if the command is not understood. The typical process involved when using NETS consists of translating the problem into a format which uses input/output pairs, designing a network configuration for the problem, and finally training the network with input/output pairs until an acceptable error is reached. NETS

  11. A friendly tool to remotely follow-up fusion machines experiments

    International Nuclear Information System (INIS)

    Signoret, J.; Balme, S.; Theis, J.M.

    2013-01-01

    Highlights: • ShotListener allows a remote user to easily follow up the shot sequence and receive information on the shot operation. • ShotListener is a java application available for Windows and Linux platform. • ShotListener is suitable for any tokamak. -- Abstract: When the international collaborations gather around a project more and more geographically scattered participants, it is imperative for them to get tools to keep in touch with the laboratory hosting the experiment, to know about the ongoing operations or even to remotely participate in them. The CEA-IRFM developed ShotListener to meet these needs, which should appear for actual or future tokamaks. This Java application intercepts the main events of a discharge sequence and notifies the user with visual or sound alerts, allowing him to follow the distant experiments easily. An API based on an MDSplus server has been developed to insure communication with the local CODAC supervision system. This API translates the Tokamak events as MDSplus events, available for any subscribers. The java application ShotListener, available for Windows and Linux platforms as an auto-installable package, connects to the MDSplus server, subscribes to a list of shot events (customizable by the end-user) and sends a visual or sound alert when a selected event occurs. For example, depending on the selected events, the user can display an extract of the shots log or visualize the video of the pulse. This architecture is obviously suitable for any machine, as long as the specific API sending MDSplus events is implemented. The aim of this paper is to describe the detailed architecture of ShotListener, to present its different functionalities and to introduce some possible enhancements

  12. Machine Assistance in Collection Building: New Tools, Research, Issues, and Reflections

    Directory of Open Access Journals (Sweden)

    Steve Mitchell

    2006-12-01

    Full Text Available Digital tool making offers many challenges, involving much trial and error. Developing machine learning and assistance in automated and semi-automated Internet resource discovery, metadata generation, and rich-text identification provides opportunities for great discovery, innovation, and the potential for transformation of the library community. The areas of computer science involved, as applied to the library applications addressed, are among that discipline’s leading edges. Making applied research practical and applicable, through placement within library/collection-management systems and services, involves equal parts computer scientist, research librarian, and legacy-systems archaeologist. Still, the early harvest is there for us now, with a large harvest pending. Data Fountains and iVia, the projects discussed, demonstrate this. Clearly, then, the present would be a good time for the library community to more proactively and significantly engage with this technology and research, to better plan for its impacts, to more proactively take up the challenges involved in its exploration, and to better and more comprehensively guide effort in this new territory. The alternative to doing this is that others will develop this territory for us, do it not as well, and sell it back to us at a premium. Awareness of this technology and its current capabilities, promises, limitations, and probable major impacts needs to be generalized throughout the library management, metadata, and systems communities. This article charts recent work, promising avenues for new research and development, and issues the library community needs to understand.

  13. A friendly tool to remotely follow-up fusion machines experiments

    Energy Technology Data Exchange (ETDEWEB)

    Signoret, J., E-mail: jacqueline.signoret@cea.fr; Balme, S.; Theis, J.M.

    2013-10-15

    Highlights: • ShotListener allows a remote user to easily follow up the shot sequence and receive information on the shot operation. • ShotListener is a java application available for Windows and Linux platform. • ShotListener is suitable for any tokamak. -- Abstract: When the international collaborations gather around a project more and more geographically scattered participants, it is imperative for them to get tools to keep in touch with the laboratory hosting the experiment, to know about the ongoing operations or even to remotely participate in them. The CEA-IRFM developed ShotListener to meet these needs, which should appear for actual or future tokamaks. This Java application intercepts the main events of a discharge sequence and notifies the user with visual or sound alerts, allowing him to follow the distant experiments easily. An API based on an MDSplus server has been developed to insure communication with the local CODAC supervision system. This API translates the Tokamak events as MDSplus events, available for any subscribers. The java application ShotListener, available for Windows and Linux platforms as an auto-installable package, connects to the MDSplus server, subscribes to a list of shot events (customizable by the end-user) and sends a visual or sound alert when a selected event occurs. For example, depending on the selected events, the user can display an extract of the shots log or visualize the video of the pulse. This architecture is obviously suitable for any machine, as long as the specific API sending MDSplus events is implemented. The aim of this paper is to describe the detailed architecture of ShotListener, to present its different functionalities and to introduce some possible enhancements.

  14. Communication and control tools, systems, and new dimensions

    CERN Document Server

    MacDougall, Robert; Cummings, Kevin

    2015-01-01

    Communication and Control: Tools, Systems, and New Dimensions advocates a systems view of human communication in a time of intelligent, learning machines. This edited collection sheds new light on things as mundane yet still profoundly consequential (and seemingly "low-tech") today as push buttons, pagers and telemarketing systems. Contributors also investigate aspects of "remote control" related to education, organizational design, artificial intelligence, cyberwarfa

  15. BUSINESS INTELLIGENCE

    OpenAIRE

    Bogdan Mohor Dumitrita

    2011-01-01

    The purpose of this work is to present business intelligence systems. These systems can be extremely complex and important in modern market competition. Its effectiveness also reflects in price, so we have to exlore their financial potential before investment. The systems have 20 years long history and during that time many of such tools have been developed, but they are rarely still in use. Business intelligence system consists of three main areas: Data Warehouse, ETL tools and tools f...

  16. Artificial Consciousness or Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Spanache Florin

    2017-05-01

    Full Text Available Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

  17. Market structure, industrial organisation and technological development: the case of the Japanese electronics-based nc-machine tool industry.

    OpenAIRE

    Watanabe, S

    1983-01-01

    ILO pub-WEP pub. Working paper on the impact of market structure and business organization on technological change in the automatic control machine tool industry in Japan - based on a 1982 sample survey of 40 industrial enterprises, discusses research and development trends, demand, production, subcontracting, competition, etc.; investigates the impact of electronics Innovation on small scale industry, the international division of labour and on developing countries. Bibliography and graphs.

  18. Study of PVD AlCrN Coating for Reducing Carbide Cutting Tool Deterioration in the Machining of Titanium Alloys.

    Science.gov (United States)

    Cadena, Natalia L; Cue-Sampedro, Rodrigo; Siller, Héctor R; Arizmendi-Morquecho, Ana M; Rivera-Solorio, Carlos I; Di-Nardo, Santiago

    2013-05-24

    The manufacture of medical and aerospace components made of titanium alloys and other difficult-to-cut materials requires the parallel development of high performance cutting tools coated with materials capable of enhanced tribological and resistance properties. In this matter, a thin nanocomposite film made out of AlCrN (aluminum-chromium-nitride) was studied in this research, showing experimental work in the deposition process and its characterization. A heat-treated monolayer coating, competitive with other coatings in the machining of titanium alloys, was analyzed. Different analysis and characterizations were performed on the manufactured coating by scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDXS), and X-ray diffraction (XRD). Furthermore, the mechanical behavior of the coating was evaluated through hardness test and tribology with pin-on-disk to quantify friction coefficient and wear rate. Finally, machinability tests using coated tungsten carbide cutting tools were executed in order to determine its performance through wear resistance, which is a key issue of cutting tools in high-end cutting at elevated temperatures. It was demonstrated that the specimen (with lower friction coefficient than previous research) is more efficient in machinability tests in Ti6Al4V alloys. Furthermore, the heat-treated monolayer coating presented better performance in comparison with a conventional monolayer of AlCrN coating.

  19. The application of a Business Intelligence tool for strategic planning in a higher education institution: a case study of the University of the Witwatersrand

    Directory of Open Access Journals (Sweden)

    Vincent Nyalungu

    2011-07-01

    Full Text Available This article presents a discussion on the importance of business intelligence (BI and the role that a specific BI tool, Business Intelligence Enterprise Edition, plays in the strategic decision-making processes in an organisation. The University of the Witwatersrand, often referred to as Wits, was used as a case study. The main objective of a business intelligence tool is to improve the quality and timeliness of the input of data to the organisational decision-making process. The quality of the data, which is an organisational asset, is therefore of the utmost importance. Approaches for the identification of business intelligence from corporate information and knowledge management were also assessed. A questionnaire was administered among key informants within the university in order to address some of the pertinent issues at higher education institutions. In addition, the role of a data warehouse within the business intelligence framework was presented. The paper itself covers a wide range of disciplines from information technology, knowledge management to decision sciences. The article also presents a proposed framework to be used in line with the best practices in the implementation of business intelligence solutions. Keywords: Business Intelligence (BI, Business Intelligence Enterprise Edition (BIEE, Data Warehouse, Strategic Decision Making, Strategic Planning, Higher Education Institutions and Knowledge Management. Disciplines: Information Technology, Knowledge Management, Management Sciences, Decision Sciences & Management

  20. Automated Parallel Computing Tools for Multicore Machines and Clusters, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to improve productivity of high performance computing for applications on multicore computers and clusters. These machines built from one or more chips...