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.

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.

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…

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.

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.

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.

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.

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...

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.

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.

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

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.

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

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.

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.

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.

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 ...

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.

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.

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

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.

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.

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...

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.

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.

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...

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...

[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.

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.

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

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.

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...

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.

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....

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.

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...

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

[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.

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.

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.

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

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.

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...

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.

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: ...

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

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

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.

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

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

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

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 ...

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.

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

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

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

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

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…

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...

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.

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.

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

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.

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.)

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.

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...

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.)

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

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

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...

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...

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...

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.

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.))

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.

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.

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)

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.

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.

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.

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.

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.

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.

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.

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.

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)

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

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

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.

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...

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.)

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

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%.

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.

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.

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.

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.

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.

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.

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.

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...

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

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.

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.

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...

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.

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.

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.

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.

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.

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.

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...

Artificial intelligence applications in information and communication technologies

CERN Document Server

Bouguila, Nizar

2015-01-01

This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.  .

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.

Future Smart Cooking Machine System Design

Directory of Open Access Journals (Sweden)

Dewi Agushinta R.

2013-11-01

Full Text Available There are many tools make human task get easier. Cooking has become a basic necessity for human beings, since food is one of basic human needs. Until now, the cooking equipment being used is still a hand tool. However everyone has slightly high activity. The presence of cooking tools that can do the cooking work by itself is now necessary. Future Smart Cooking Machine is an artificial intelligence machine that can do cooking work automatically. With this system design, the time is minimized and the ease of work is expected to be achieved. The development of this system is carried out with System Development Life Cycle (SDLC methods. Prototyping method used in this system is a throw-away prototyping approach. At the end of this research there will be produced a cooking machine system design including physical design engine and interface design.

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.

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. .

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.

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.

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

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.

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...

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...

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)

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 ...

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

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...

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

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.

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

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.

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.

Software tool for data mining and its applications

Science.gov (United States)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

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.

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

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

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.

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...

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.

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

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...

Advanced intelligent systems

CERN Document Server

Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

2014-01-01

Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

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.

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.

Designing a holistic end-to-end intelligent network analysis and security platform

Science.gov (United States)

Alzahrani, M.

2018-03-01

Firewall protects a network from outside attacks, however, once an attack entering a network, it is difficult to detect. Recent significance accidents happened. i.e.: millions of Yahoo email account were stolen and crucial data from institutions are held for ransom. Within two year Yahoo’s system administrators were not aware that there are intruder inside the network. This happened due to the lack of intelligent tools to monitor user behaviour in internal network. This paper discusses a design of an intelligent anomaly/malware detection system with proper proactive actions. The aim is to equip the system administrator with a proper tool to battle the insider attackers. The proposed system adopts machine learning to analyse user’s behaviour through the runtime behaviour of each node in the network. The machine learning techniques include: deep learning, evolving machine learning perceptron, hybrid of Neural Network and Fuzzy, as well as predictive memory techniques. The proposed system is expanded to deal with larger network using agent techniques.

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)

Intelligence-Augmented Rat Cyborgs in Maze Solving.

Directory of Open Access Journals (Sweden)

Yipeng Yu

Full Text Available Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs. They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg has great potential in various applications, such as search and rescue in complex terrains.

Intelligence-Augmented Rat Cyborgs in Maze Solving.

Science.gov (United States)

Yu, Yipeng; Pan, Gang; Gong, Yongyue; Xu, Kedi; Zheng, Nenggan; Hua, Weidong; Zheng, Xiaoxiang; Wu, Zhaohui

2016-01-01

Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs). They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg) has great potential in various applications, such as search and rescue in complex terrains.

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.

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.

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…

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...

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.

Effective tool wear estimation through multisensory information ...

African Journals Online (AJOL)

On-line tool wear monitoring plays a significant role in industrial automation for higher productivity and product quality. In addition, an intelligent system is required to make a timely decision for tool change in machining systems in order to avoid the subsequent consequences on the dimensional accuracy and surface finish ...

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.

Considerations upon the Machine Learning Technologies

OpenAIRE

Alin Munteanu; Cristina Ofelia Sofran

2006-01-01

Artificial intelligence offers superior techniques and methods by which problems from diverse domains may find an optimal solution. The Machine Learning technologies refer to the domain of artificial intelligence aiming to develop the techniques allowing the computers to “learn”. Some systems based on Machine Learning technologies tend to eliminate the necessity of the human intelligence while the others adopt a man-machine collaborative approach.

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

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.

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.

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.

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.

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.

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.

Biomimetics in Intelligent Sensor and Actuator Automation Systems

Science.gov (United States)

Bruckner, Dietmar; Dietrich, Dietmar; Zucker, Gerhard; Müller, Brit

Intelligent machines are really an old mankind's dream. With increasing technological development, the requirements for intelligent devices also increased. However, up to know, artificial intelligence (AI) lacks solutions to the demands of truly intelligent machines that have no problems to integrate themselves into daily human environments. Current hardware with a processing power of billions of operations per second (but without any model of human-like intelligence) could not substantially contribute to the intelligence of machines when compared with that of the early AI times. There are great results, of course. Machines are able to find the shortest path between far apart cities on the map; algorithms let you find information described only by few key words. But no machine is able to get us a cup of coffee from the kitchen yet.

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...

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...

Considerations upon the Machine Learning Technologies

Directory of Open Access Journals (Sweden)

Alin Munteanu

2006-01-01

Full Text Available Artificial intelligence offers superior techniques and methods by which problems from diverse domains may find an optimal solution. The Machine Learning technologies refer to the domain of artificial intelligence aiming to develop the techniques allowing the computers to “learn”. Some systems based on Machine Learning technologies tend to eliminate the necessity of the human intelligence while the others adopt a man-machine collaborative approach.

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.

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.

BWR shutdown analyzer using artificial intelligence (AI) techniques

International Nuclear Information System (INIS)

Cain, D.G.

1986-01-01

A prototype alarm system for detecting abnormal reactor shutdowns based on artificial intelligence technology is described. The system incorporates knowledge about Boiling Water Reactor (BWR) plant design and component behavior, as well as knowledge required to distinguish normal, abnormal, and ATWS accident conditions. The system was developed using a software tool environment for creating knowledge-based applications on a LISP machine. To facilitate prototype implementation and evaluation, a casual simulation of BWR shutdown sequences was developed and interfaced with the alarm system. An intelligent graphics interface for execution and control is described. System performance considerations and general observations relating to artificial intelligence application to nuclear power plant problems are provided

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

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

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…

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 ...

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....

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.

Support vector machines applications

CERN Document Server

Guo, Guodong

2014-01-01

Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances.

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.

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

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.

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.

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.

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.

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 ...

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.

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.

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

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. 

Intelligent engineering and technology for nuclear power plant operation

International Nuclear Information System (INIS)

Wang, P.P.; Gu, X.

1996-01-01

The Three-Mile-Island accident has drawn considerable attention by the engineering, scientific, management, financial, and political communities as well as society at large. This paper surveys possible causes of the accident studied by various groups. Research continues in this area with many projects aimed at specifically improving the performance and operation of a nuclear power plant using the contemporary technologies available. In addition to the known cause of the accident and suggest a strategy for coping with these problems in the future. With the increased use of intelligent methodologies called computational intelligence or soft-computing, a substantially larger collection of powerful tools are now available for our designers to use in order to tackle these sensitive and difficult issues. These intelligent methodologies consists of fuzzy logic, genetic algorithms, neural networks, artificial intelligence and expert systems, pattern recognition, machine intelligence, and fuzzy constraint networks. Using the Three-Mile-Island experience, this paper offers a set of specific recommendations for future designers to take advantage of the powerful tools of intelligent technologies that we are now able to master and encourages the adoption of a novel methodology called fuzzy constraint network

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.

Hybrid-augmented intelligence:collaboration and cognition

Institute of Scientific and Technical Information of China (English)

Nan-ning ZHENG; Zi-yi LIU; Peng-ju REN; Yong-qiang MA; Shi-tao CHEN; Si-yu YU; Jian-ru XUE

2017-01-01

The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models:one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

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...

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.

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.

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.

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.

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.

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...

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.

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.

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

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

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.

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.

Artificial Intelligence and Moral intelligence

Directory of Open Access Journals (Sweden)

Laura Pana

2008-07-01

Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

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.

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.

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

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.

A Novel Artificial Intelligence System for Endotracheal Intubation.

Science.gov (United States)

Carlson, Jestin N; Das, Samarjit; De la Torre, Fernando; Frisch, Adam; Guyette, Francis X; Hodgins, Jessica K; Yealy, Donald M

2016-01-01

Adequate visualization of the glottic opening is a key factor to successful endotracheal intubation (ETI); however, few objective tools exist to help guide providers' ETI attempts toward the glottic opening in real-time. Machine learning/artificial intelligence has helped to automate the detection of other visual structures but its utility with ETI is unknown. We sought to test the accuracy of various computer algorithms in identifying the glottic opening, creating a tool that could aid successful intubation. We collected a convenience sample of providers who each performed ETI 10 times on a mannequin using a video laryngoscope (C-MAC, Karl Storz Corp, Tuttlingen, Germany). We recorded each attempt and reviewed one-second time intervals for the presence or absence of the glottic opening. Four different machine learning/artificial intelligence algorithms analyzed each attempt and time point: k-nearest neighbor (KNN), support vector machine (SVM), decision trees, and neural networks (NN). We used half of the videos to train the algorithms and the second half to test the accuracy, sensitivity, and specificity of each algorithm. We enrolled seven providers, three Emergency Medicine attendings, and four paramedic students. From the 70 total recorded laryngoscopic video attempts, we created 2,465 time intervals. The algorithms had the following sensitivity and specificity for detecting the glottic opening: KNN (70%, 90%), SVM (70%, 90%), decision trees (68%, 80%), and NN (72%, 78%). Initial efforts at computer algorithms using artificial intelligence are able to identify the glottic opening with over 80% accuracy. With further refinements, video laryngoscopy has the potential to provide real-time, direction feedback to the provider to help guide successful ETI.

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.  

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.

Intelligent Decision Technologies : Proceedings of the 4th International Conference on Intelligent Decision Technologies

CERN Document Server

Watanabe, Toyohide; Phillips-Wren, Gloria; Howlett, Robert; Jain, Lakhmi

2012-01-01

The Intelligent Decision Technologies (IDT) International Conference encourages an interchange of research on intelligent systems and intelligent technologies that enhance or improve decision making. The focus of IDT is interdisciplinary and includes research on all aspects of intelligent decision technologies, from fundamental development to real applications. IDT has the potential to expand their support of decision making in such areas as finance, accounting, marketing, healthcare, medical and diagnostic systems, military decisions, production and operation, networks, traffic management, crisis response, human-machine interfaces, financial and stock market monitoring and prediction, and robotics. Intelligent decision systems implement advances in intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, and genetic algorithms, among others.  Emerging areas of active research include virtual decision environments, social networking, 3D human-machine interfaces, cognitive interfaces,...

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.

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.

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.

The 1988 Goddard Conference on Space Applications of Artificial Intelligence

Science.gov (United States)

Rash, James (Editor); Hughes, Peter (Editor)

1988-01-01

This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools/methodologies.

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

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

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.

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

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...

A Research Review on the Key Technologies of Intelligent Design for Customized Products

Directory of Open Access Journals (Sweden)

Shuyou Zhang

2017-10-01

Full Text Available The development of technologies such as big data and cyber-physical systems (CPSs has increased the demand for product design. Product digital design involves completing the product design process using advanced digital technologies such as geometry modeling, kinematic and dynamic simulation, multi-disciplinary coupling, virtual assembly, virtual reality (VR, multi-objective optimization (MOO, and human-computer interaction. The key technologies of intelligent design for customized products include: a description and analysis of customer requirements (CRs, product family design (PFD for the customer base, configuration and modular design for customized products, variant design for customized products, and a knowledge push for product intelligent design. The development trends in intelligent design for customized products include big-data-driven intelligent design technology for customized products and customized design tools and applications. The proposed method is verified by the design of precision computer numerical control (CNC machine tools.

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.

Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

NARCIS (Netherlands)

van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

2013-01-01

The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

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.

Intelligent systems and soft computing for nuclear science and industry

International Nuclear Information System (INIS)

Ruan, D.; D'hondt, P.; Govaerts, P.; Kerre, E.E.

1996-01-01

The second international workshop on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS) addresses topics related to intelligent systems and soft computing for nuclear science and industry. The proceedings contain 52 papers in different fields such as radiation protection, nuclear safety (human factors and reliability), safeguards, nuclear reactor control, production processes in the fuel cycle, dismantling, waste and disposal, decision making, and nuclear reactor control. A clear link is made between theory and applications of fuzzy logic such as neural networks, expert systems, robotics, man-machine interfaces, and decision-support techniques by using modern and advanced technologies and tools. The papers are grouped in three sections. The first section (Soft computing techniques) deals with basic tools to treat fuzzy logic, neural networks, genetic algorithms, decision-making, and software used for general soft-computing aspects. The second section (Intelligent engineering systems) includes contributions on engineering problems such as knowledge-based engineering, expert systems, process control integration, diagnosis, measurements, and interpretation by soft computing. The third section (Nuclear applications) focusses on the application of soft computing and intelligent systems in nuclear science and industry

Role of artificial intelligence in the care of patients with nonsmall cell lung cancer.

Science.gov (United States)

Rabbani, Mohamad; Kanevsky, Jonathan; Kafi, Kamran; Chandelier, Florent; Giles, Francis J

2018-04-01

Lung cancer is the leading cause of cancer death worldwide. In up to 57% of patients, it is diagnosed at an advanced stage and the 5-year survival rate ranges between 10%-16%. There has been a significant amount of research using machine learning to generate tools using patient data to improve outcomes. This narrative review is based on research material obtained from PubMed up to Nov 2017. The search terms include "artificial intelligence," "machine learning," "lung cancer," "Nonsmall Cell Lung Cancer (NSCLC)," "diagnosis" and "treatment." Recent studies support the use of computer-aided systems and the use of radiomic features to help diagnose lung cancer earlier. Other studies have looked at machine learning (ML) methods that offer prognostic tools to doctors and help them in choosing personalized treatment options for their patients based on molecular, genetics and histological features. Combining artificial intelligence approaches into health care may serve as a beneficial tool for patients with NSCLC, and this review outlines these benefits and current shortcomings throughout the continuum of care. We present a review of the various applications of ML methods in NSCLC as it relates to improving diagnosis, treatment and outcomes. © 2018 Stichting European Society for Clinical Investigation Journal Foundation.

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 ...

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...

Research of a smart cutting tool based on MEMS strain gauge

Science.gov (United States)

Zhao, Y.; Zhao, Y. L.; Shao, YW; Hu, T. J.; Zhang, Q.; Ge, X. H.

2018-03-01

Cutting force is an important factor that affects machining accuracy, cutting vibration and tool wear. Machining condition monitoring by cutting force measurement is a key technology for intelligent manufacture. Current cutting force sensors exist problems of large volume, complex structure and poor compatibility in practical application, for these problems, a smart cutting tool is proposed in this paper for cutting force measurement. Commercial MEMS (Micro-Electro-Mechanical System) strain gauges with high sensitivity and small size are adopted as transducing element of the smart tool, and a structure optimized cutting tool is fabricated for MEMS strain gauge bonding. Static calibration results show that the developed smart cutting tool is able to measure cutting forces in both X and Y directions, and the cross-interference error is within 3%. Its general accuracy is 3.35% and 3.27% in X and Y directions, and sensitivity is 0.1 mV/N, which is very suitable for measuring small cutting forces in high speed and precision machining. The smart cutting tool is portable and reliable for practical application in CNC machine tool.

Issues regarding the design and acceptance of intelligent support systems for reactor operators

International Nuclear Information System (INIS)

Bernard, J.A.

1992-01-01

In this paper, factors relevant to the design and acceptance of intelligent support systems for the operation of nuclear power plants are enumerated and discussed. The central premise is that conventional expert systems which encode experiential knowledge in production rules are not a suitable vehicle for the creation of practical operator support systems. The principal difficulty is the need for real-time operation. This in turn means that intelligent support systems will have knowledge bases derived from temporally accurate plant models, inference engines that permit revisions in the search process so as to accommodate revised or new data, and man-machine interfaces that do not require any human input. Such systems will have to be heavily instrumented and the associated knowledge bases will require a hierarchical organization so as to emulate human approaches to analysis. Issues related to operator acceptance of intelligent support tools are then reviewed. Possible applications are described and the relative merits of the machine- and human-centered approaches to the implementation of intelligent support systems are enumerated. The paper concludes with a plea for additional experimental evaluations

Computational Foundations of Natural Intelligence.

Science.gov (United States)

van Gerven, Marcel

2017-01-01

New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

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.

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.

On The Subject of Thinking Machines

OpenAIRE

Olafenwa , John ,; Olafenwa , Moses

2018-01-01

An investigation of the concepts of thoughts, imagination and consciousness in learning machines.; 68 years ago, Alan Turing proposed the question "Can Machines Think" in his seminal paper [1] titled "Computing Machinery and Intelligence" and he formulated the "Imitation Game" also known as the Turing test as a way to answer this question without referring to a rather ambiguous dictionary definition of the word "Think" We have come a long way to building intelligent machines, in fact, the rat...

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...

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

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

What Is Artificial Intelligence Anyway?

Science.gov (United States)

Kurzweil, Raymond

1985-01-01

Examines the past, present, and future status of Artificial Intelligence (AI). Acknowledges the limitations of AI but proposes possible areas of application and further development. Urges a concentration on the unique strengths of machine intelligence rather than a copying of human intelligence. (ML)

The Milling Assistant, Case-Based Reasoning, and machining strategy: A report on the development of automated numerical control programming systems at New Mexico State University

Energy Technology Data Exchange (ETDEWEB)

Burd, W. [Sandia National Labs., Albuquerque, NM (United States); Culler, D.; Eskridge, T.; Cox, L.; Slater, T. [New Mexico State Univ., Las Cruces, NM (United States)

1993-08-01

The Milling Assistant (MA) programming system demonstrates the automated development of tool paths for Numerical Control (NC) machine tools. By integrating a Case-Based Reasoning decision processor with a commercial CAD/CAM software, intelligent tool path files for milled and point-to-point features can be created. The operational system is capable of reducing the time required to program a variety of parts and improving product quality by collecting and utilizing ``best of practice`` machining strategies.

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

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.

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.

Computational Foundations of Natural Intelligence

Directory of Open Access Journals (Sweden)

Marcel van Gerven

2017-12-01

Full Text Available New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

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...

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

Intelligent robots: Do we need them and can they be built?

International Nuclear Information System (INIS)

Mann, R.C.

1993-01-01

For avid watchers of science fiction movies, the mention of robotics and artificial intelligence conjures up images of humanlike machines. Often, news reports of scientific advances that enable machines to behave in a flexible manner for a limited set of tests draw parallels to science fiction robots. The effect of this unfortunate kind of publicity is that the scientific disciplines of robotics and artificial intelligence are sometimes regarded as a playground for slightly crazed scientists trying to create artificial humans. In reality, the fields of robotics and artificial intelligence can best be described by answering a few commonly asked questions: What is an intelligent robot, anyway? Why would we need things like that? Could we build them and make them reliable for certain uses? An example of an intelligent machine, or robot is presented and the question of whether intelligent robots are needed is addressed. The impact of ORNL research on uses for intelligent machines is described

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.

Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT)

Science.gov (United States)

Blasch, Erik

2015-06-01

Assessment of multi-intelligence fusion techniques includes credibility of algorithm performance, quality of results against mission needs, and usability in a work-domain context. Situation awareness (SAW) brings together low-level information fusion (tracking and identification), high-level information fusion (threat and scenario-based assessment), and information fusion level 5 user refinement (physical, cognitive, and information tasks). To measure SAW, we discuss the SAGAT (Situational Awareness Global Assessment Technique) technique for a multi-intelligence fusion (MIF) system assessment that focuses on the advantages of MIF against single intelligence sources. Building on the NASA TLX (Task Load Index), SAGAT probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points; we highlight these tools for use in a Multi-Intelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measures of product quality and QuEST of information. Building a notion of product quality from multi-intelligence tools is typically subjective which needs to be aligned with objective machine metrics.

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.

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).

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.

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.

The 1991 Goddard Conference on Space Applications of Artificial Intelligence

Science.gov (United States)

Rash, James L. (Editor)

1991-01-01

The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in this proceeding fall into the following areas: Planning and scheduling, fault monitoring/diagnosis/recovery, machine vision, robotics, system development, information management, knowledge acquisition and representation, distributed systems, tools, neural networks, and miscellaneous applications.

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

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.

[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.

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.

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.

4th Workshop on Combinations of Intelligent Methods and Applications

CERN Document Server

Palade, Vasile; Prentzas, Jim

2016-01-01

This volume includes extended and revised versions of the papers presented at the 4th Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2014) which was intended to become a forum for exchanging experience and ideas among researchers and practitioners dealing with combinations of different intelligent methods in Artificial Intelligence. The aim is to create integrated or hybrid methods that benefit from each of their components. Some of the existing presented efforts combine soft computing methods (fuzzy logic, neural networks and genetic algorithms). Another stream of efforts integrates case-based reasoning or machine learning with soft-computing methods. Some of the combinations have been more widely explored, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-based and case-based reasoning. CIMA 2014 was held in conjunction with the 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2014). .

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.

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.

2015 Chinese Intelligent Systems Conference

CERN Document Server

Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15

2016-01-01

This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

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…

Mankind, machines and people

Energy Technology Data Exchange (ETDEWEB)

Hugli, A

1984-01-01

The following questions are addressed: is there a difference between machines and men, between human communication and communication with machines. Will we ever reach the point when the dream of artificial intelligence becomes a reality. Will thinking machines be able to replace the human spirit in all its aspects. Social consequences and philosophical aspects are addressed. 8 references.

25th International Conference on Industrial, Engineering & Other Applica- tions of Applied Intelligent Systems (IEA/AIE 2012)

CERN Document Server

Jiang, He; Ali, Moonis; Li, Mingchu; Modern Advances in Intelligent Systems and Tools

2012-01-01

Intelligent systems provide a platform to connect the research in artificial intelligence to real-world problem solving applications. Various intelligent systems have been developed to face real-world applications. This book discusses the modern advances in intelligent systems and the tools in applied artificial intelligence. It consists of twenty-three chapters authored by participants of the 25th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2012) which was held in Dalian, China. This book is divided into six parts, including Applied Intelligence, Cognitive Computing and Affective Computing, Data Mining and Intelligent Systems, Decision Support Systems, Machine Learning, and Natural Language Processing. Each part includes three to five chapters. In these chapters, many approaches, applications, restrictions, and discussions are presented. The material of each chapter is self-contained and was reviewed by at least two anonymous referees t...

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.

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 ...

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.

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.

Better Diagnosis of Acute Appendicitis by Using Artificial Intelligence

OpenAIRE

Mir Mekaeal Hosseini; Reza Safdari; Lila Shahmoradi; Mojtaba Javaherzadeh

2017-01-01

Background: Acute appendicitis is the most common cause for referral of patients with abdominal pains to emergency department of hospitals and appendectomy is the most common emergency operation. Despite of introduction of the various diagnostic methods unnecessary appendectomy rate is significant. Therefore, the use of artificial intelligence and machine learning methods as a tool to aid in the diagnosis can be timely and more accurate diagnosis, reduce length of stay in hospital and improve...

Virtual NC machine model with integrated knowledge data

International Nuclear Information System (INIS)

Sidorenko, Sofija; Dukovski, Vladimir

2002-01-01

The concept of virtual NC machining was established for providing a virtual product that could be compared with an appropriate designed product, in order to make NC program correctness evaluation, without real experiments. This concept is applied in the intelligent CAD/CAM system named VIRTUAL MANUFACTURE. This paper presents the first intelligent module that enables creation of the virtual models of existed NC machines and virtual creation of new ones, applying modular composition. Creation of a virtual NC machine is carried out via automatic knowledge data saving (features of the created NC machine). (Author)

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

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...

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.

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…

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)

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.

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.

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

3rd International Workshop on Intelligent Data Analysis and Management (IDAM)

CERN Document Server

Wang, Leon; Hong, Tzung-Pei; Yang, Hsin-Chang; Ting, I-Hsien

2013-01-01

These papers on Intelligent Data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. The papers derive from the 2013 IDAM conference in Kaohsiung ,Taiwan. It is an interdisciplinary research field involving academic researchers in information technologies, computer science, public policy, bioinformatics, medical informatics, and social and behavior studies, etc. The techniques studied include (but are not limited to): data visualization, data pre-processing, data engineering, database mining techniques, tools and applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing, etc.

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.

Pattern recognition & machine learning

CERN Document Server

Anzai, Y

1992-01-01

This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

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.

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'

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...

1988 Goddard Conference on Space Applications of Artificial Intelligence, Greenbelt, MD, May 24, 1988, Proceedings

Science.gov (United States)

Rash, James L. (Editor)

1988-01-01

This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools methodologies.

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.

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.

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.

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...

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…

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.

陕西电信天翼3G双模智能机市场发展策略研究%Shanxi Telecom Tianyi 3G Dual-mode Intelligent Machine Market Development Strategy Research

Institute of Scientific and Technical Information of China (English)

贾琳

2013-01-01

中国电信陕西公司天翼3G智能终端销售在2011年至2012年间快速上升，但2012年下半年，智能机发展出现阶段性波动，增长率降低；同时竞争对手发力双模智能机，快速挖转中国移动用户。分析和论证发展天翼3G双模智能机的必要性，并从产品、价格、渠道、宣传和促销4方面提出了天翼3G双模智能机发展的具体策略，对于陕西电信进一步加快智能机的发展，拓展社会开放渠道，保持3G市场领先优势具有重要意义。%3G intelligent terminal sales of Shaanxi China Telecom Tianyi form 2011 to 2012 years the rises rapidly,but the second half of 2012, intelligent machine development stage of volatility, growth rate decreased,rival force of dual-mode intelligent machine, fast digging to China Mobile users at the same time. This paper focuses on a telecommunications enterprise employee's point of view, fully aware of the changing market environment and competition strategy, the necessity analysis and demonstration of development day wing 3G dual-mode intelligent machines, and specific strategies day wing development 3G dual-mode intelligent machine is put forward from the product, price, channel, promotion and promotion four aspects, for Shaanxi to further accelerate the development of the telecom intelligent machine, expand social open channel, it is important to keep the 3G market advantage.

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.

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.…

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.

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.

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

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.

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.

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.

Intelligent approaches for the synthesis of petrophysical logs

International Nuclear Information System (INIS)

Rezaee, M Reza; Kadkhodaie-Ilkhchi, Ali; Alizadeh, Pooya Mohammad

2008-01-01

Log data are of prime importance in acquiring petrophysical data from hydrocarbon reservoirs. Reliable log analysis in a hydrocarbon reservoir requires a complete set of logs. For many reasons, such as incomplete logging in old wells, destruction of logs due to inappropriate data storage and measurement errors due to problems with logging apparatus or hole conditions, log suites are either incomplete or unreliable. In this study, fuzzy logic and artificial neural networks were used as intelligent tools to synthesize petrophysical logs including neutron, density, sonic and deep resistivity. The petrophysical data from two wells were used for constructing intelligent models in the Fahlian limestone reservoir, Southern Iran. A third well from the field was used to evaluate the reliability of the models. The results showed that fuzzy logic and artificial neural networks were successful in synthesizing wireline logs. The combination of the results obtained from fuzzy logic and neural networks in a simple averaging committee machine (CM) showed a significant improvement in the accuracy of the estimations. This committee machine performed better than fuzzy logic or the neural network model in the problem of estimating petrophysical properties from well logs

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...

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.

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.

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.

Combining human and machine processes (CHAMP)

Science.gov (United States)

Sudit, Moises; Sudit, David; Hirsch, Michael

2015-05-01

Machine Reasoning and Intelligence is usually done in a vacuum, without consultation of the ultimate decision-maker. The late consideration of the human cognitive process causes some major problems in the use of automated systems to provide reliable and actionable information that users can trust and depend to make the best Course-of-Action (COA). On the other hand, if automated systems are created exclusively based on human cognition, then there is a danger of developing systems that don't push the barrier of technology and are mainly done for the comfort level of selected subject matter experts (SMEs). Our approach to combining human and machine processes (CHAMP) is based on the notion of developing optimal strategies for where, when, how, and which human intelligence should be injected within a machine reasoning and intelligence process. This combination is based on the criteria of improving the quality of the output of the automated process while maintaining the required computational efficiency for a COA to be actuated in timely fashion. This research addresses the following problem areas: • Providing consistency within a mission: Injection of human reasoning and intelligence within the reliability and temporal needs of a mission to attain situational awareness, impact assessment, and COA development. • Supporting the incorporation of data that is uncertain, incomplete, imprecise and contradictory (UIIC): Development of mathematical models to suggest the insertion of a cognitive process within a machine reasoning and intelligent system so as to minimize UIIC concerns. • Developing systems that include humans in the loop whose performance can be analyzed and understood to provide feedback to the sensors.

Principles of artificial intelligence

CERN Document Server

Nilsson, Nils J

1980-01-01

A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

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.

Fiscal 2000 achievement report. Research on machine tool not necessitating hydraulic system; 2000 nendo yuatsu resu kosaku kikai no kenkyu seika hokokusho

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-03-01

From the viewpoint that the manufacturing process, expendable items, and recycling should all be taken into consideration when machine tool energy consumption is the matter to discuss, it is concluded that the most important policy to follow in the effort to enhance energy conservation is to enable the tool to operate without hydraulic systems. For the realization of a general-purpose machine tool (lathe) to operate free of hydraulic systems, efforts are exerted to develop element technologies, tool rests, tail stocks, and chuck drives usable for the construction of a practical hydraulic system-free machine tool. In fiscal 2000, comprehensive evaluation of experimental machine tools continued, problems to solve for practical application were put together for the fabrication of improved units, and the improved units and an improved control method were integrated into a prototype of practical machine tools. The prototype was exhibited at Japan International Machine Tool Fair (JIMTOF) as a hydraulic system-free NC (numerically controlled) lathe Type LB300, and won a high valuation. The prototype was then tested for basic performance and for possibility of improvement, and problems to be solved before commercialization were isolated. (NEDO)

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)

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)

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.

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

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.

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

Energy Technology Data Exchange (ETDEWEB)

Harber, K.S. [ed.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning Bayesian Expert System; a natural language generation system for a heterogeneous distributed database system; ``competence-switching`` managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries. These papers have been indexed separately.

A new optimization tool path planning for 3-axis end milling of free-form surfaces based on efficient machining intervals

Science.gov (United States)

Vu, Duy-Duc; Monies, Frédéric; Rubio, Walter

2018-05-01

A large number of studies, based on 3-axis end milling of free-form surfaces, seek to optimize tool path planning. Approaches try to optimize the machining time by reducing the total tool path length while respecting the criterion of the maximum scallop height. Theoretically, the tool path trajectories that remove the most material follow the directions in which the machined width is the largest. The free-form surface is often considered as a single machining area. Therefore, the optimization on the entire surface is limited. Indeed, it is difficult to define tool trajectories with optimal feed directions which generate largest machined widths. Another limiting point of previous approaches for effectively reduce machining time is the inadequate choice of the tool. Researchers use generally a spherical tool on the entire surface. However, the gains proposed by these different methods developed with these tools lead to relatively small time savings. Therefore, this study proposes a new method, using toroidal milling tools, for generating toolpaths in different regions on the machining surface. The surface is divided into several regions based on machining intervals. These intervals ensure that the effective radius of the tool, at each cutter-contact points on the surface, is always greater than the radius of the tool in an optimized feed direction. A parallel plane strategy is then used on the sub-surfaces with an optimal specific feed direction for each sub-surface. This method allows one to mill the entire surface with efficiency greater than with the use of a spherical tool. The proposed method is calculated and modeled using Maple software to find optimal regions and feed directions in each region. This new method is tested on a free-form surface. A comparison is made with a spherical cutter to show the significant gains obtained with a toroidal milling cutter. Comparisons with CAM software and experimental validations are also done. The results show the

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 ...

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....

Design of Control System for Kiwifruit Automatic Grading Machine

Directory of Open Access Journals (Sweden)

Xingjian Zuo

2013-05-01

Full Text Available The kiwifruit automatic grading machine is an important machine for postharvest processing of kiwifruit, and the control system ensures that the machine realizes intelligence. The control system for the kiwifruit automatic grading machine designed in this paper comprises a host computer and a slave microcontroller. The host computer provides a visual grading interface for the machine with a LabVIEW software, the slave microcontroller adopts an STC89C52 microcontroller as its core, and C language is used to write programs for controlling a position sensor module, push-pull type electromagnets, motor driving modules and a power supply for controlling the operation of the machine as well as the rise or descend of grading baffle plates. The ideal control effect is obtained through test, and the intelligent operation of the machine is realized.

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)

Intelligent robot action planning

Energy Technology Data Exchange (ETDEWEB)

Vamos, T; Siegler, A

1982-01-01

Action planning methods used in intelligent robot control are discussed. Planning is accomplished through environment understanding, environment representation, task understanding and planning, motion analysis and man-machine communication. These fields are analysed in detail. The frames of an intelligent motion planning system are presented. Graphic simulation of the robot's environment and motion is used to support the planning. 14 references.

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

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

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.

Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

Science.gov (United States)

Blasch, Erik; Waltz, Ed

2016-05-01

Current analysts are inundated with large volumes of data from which extraction, exploitation, and indexing are required. A future need for next-generation analysts is an appropriate balance between machine analytics from raw data and the ability of the user to interact with information through automation. Many quantitative intelligence tools and techniques have been developed which are examined towards matching analyst opportunities with recent technical trends such as big data, access to information, and visualization. The concepts and techniques summarized are derived from discussions with real analysts, documented trends of technical developments, and methods to engage future analysts with multiintelligence services. For example, qualitative techniques should be matched against physical, cognitive, and contextual quantitative analytics for intelligence reporting. Future trends include enabling knowledge search, collaborative situational sharing, and agile support for empirical decision-making and analytical reasoning.

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.

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.

Artificial Intelligence in Cardiology.

Science.gov (United States)

Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

2018-06-12

Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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

The expressive stance: intentionality, expression, and machine art

OpenAIRE

Linson, Adam

2013-01-01

This paper proposes a new interpretive stance for interpreting artistic works and performances that is relevant to artificial intelligence research but also has broader implications. Termed the expressive stance, this stance makes intelligible a critical distinction between present-day machine art and human art, but allows for the possibility that future machine art could find a place alongside our own. The expressive stance is elaborated as a response to Daniel Dennett's notion of the intent...

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...

The design of intelligent support systems for nuclear reactor operators

International Nuclear Information System (INIS)

Bernard, J.A.

1992-01-01

This paper identifies factors relevant to the design of intelligent support systems and their use for the provision of real-time diagnostic information. As such, it constitutes a followup to the state-of-the-art review that was previously published by Bernard and Washio on the utilization of expert systems within the nuclear industry. Some major differences between intelligent-support tools and conventional expert systems are enumerated. In summary, conventional expert systems that encode experimental knowledge in production rules are not suitable vehicle for the creation of operator support systems. The principal difficulty is the need for real-time operation. This in turn means that intelligent support systems will have knowledge bases derived from temporally accurate plant models, inference engines that permit revisions in the search process to accommodate revised data, and man-machine interfaces that do not require any human input. Such systems will be heavily instrumented, and the associated knowledge bases will require a hierarchical organization to emulate human approaches to analysis

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

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.

Machine Translation in Post-Contemporary Era

Science.gov (United States)

Lin, Grace Hui Chin

2010-01-01

This article focusing on translating techniques via personal computer or laptop reports updated artificial intelligence progresses before 2010. Based on interpretations and information for field of MT [Machine Translation] by Yorick Wilks' book, "Machine Translation, Its scope and limits," this paper displays understandable theoretical frameworks…

Teaching machine learning to design students

NARCIS (Netherlands)

Vlist, van der B.J.J.; van de Westelaken, H.F.M.; Bartneck, C.; Hu, J.; Ahn, R.M.C.; Barakova, E.I.; Delbressine, F.L.M.; Feijs, L.M.G.; Pan, Z.; Zhang, X.; El Rhalibi, A.

2008-01-01

Machine learning is a key technology to design and create intelligent systems, products, and related services. Like many other design departments, we are faced with the challenge to teach machine learning to design students, who often do not have an inherent affinity towards technology. We

Artificial Intelligence approaches in hematopoietic cell transplant: A review of the current status and future directions.

Science.gov (United States)

Muhsen, Ibrahim N; ElHassan, Tusneem; Hashmi, Shahrukh K

2018-06-08

Currently, the evidence-based literature on healthcare is expanding exponentially. The opportunities provided by the advancement in artificial intelligence (AI) tools i.e. machine learning are appealing in tackling many of the current healthcare challenges. Thus, AI integration is expanding in most fields of healthcare, including the field of hematology. This study aims to review the current applications of AI in the field hematopoietic cell transplant (HCT). Literature search was done involving the following databases: Ovid-Medline including in-Process and Other Non-Indexed Citations and google scholar. The abstracts of the following professional societies: American Society of Haematology (ASH), American Society for Blood and Marrow Transplantation (ASBMT) and European Society for Blood and Marrow Transplantation (EBMT) were also screened. Literature review showed that the integration of AI in the field of HCT has grown remarkably in the last decade and confers promising avenues in diagnosis and prognosis within HCT populations targeting both pre and post-transplant challenges. Studies on AI integration in HCT have many limitations that include poorly tested algorithms, lack of generalizability and limited use of different AI tools. Machine learning techniques in HCT is an intense area of research that needs a lot of development and needs extensive support from hematology and HCT societies / organizations globally since we believe that this would be the future practice paradigm. Key words: Artificial intelligence, machine learning, hematopoietic cell transplant.

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

Prediction of pork loin quality using online computer vision system and artificial intelligence model.

Science.gov (United States)

Sun, Xin; Young, Jennifer; Liu, Jeng-Hung; Newman, David

2018-06-01

The objective of this project was to develop a computer vision system (CVS) for objective measurement of pork loin under industry speed requirement. Color images of pork loin samples were acquired using a CVS. Subjective color and marbling scores were determined according to the National Pork Board standards by a trained evaluator. Instrument color measurement and crude fat percentage were used as control measurements. Image features (18 color features; 1 marbling feature; 88 texture features) were extracted from whole pork loin color images. Artificial intelligence prediction model (support vector machine) was established for pork color and marbling quality grades. The results showed that CVS with support vector machine modeling reached the highest prediction accuracy of 92.5% for measured pork color score and 75.0% for measured pork marbling score. This research shows that the proposed artificial intelligence prediction model with CVS can provide an effective tool for predicting color and marbling in the pork industry at online speeds. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluation of Machine Learning Methods for LHC Optics Measurements and Corrections Software

CERN Document Server

AUTHOR|(CDS)2206853; Henning, Peter

The field of artificial intelligence is driven by the goal to provide machines with human-like intelligence. However modern science is currently facing problems with high complexity that cannot be solved by humans in the same timescale as by machines. Therefore there is a demand on automation of complex tasks. To identify the category of tasks which can be performed by machines in the domain of optics measurements and correction on the Large Hadron Collider (LHC) is one of the central research subjects of this thesis. The application of machine learning methods and concepts of artificial intelligence can be found in various industry and scientific branches. In High Energy Physics these concepts are mostly used in offline analysis of experiments data and to perform regression tasks. In Accelerator Physics the machine learning approach has not found a wide application yet. Therefore potential tasks for machine learning solutions can be specified in this domain. The appropriate methods and their suitability for...

Self-Assessing of the Emotional Intelligence and Organizational Intelligence in Schools

Science.gov (United States)

Dagiene, Valentina; Juškeviciene, Anita; Carneiro, Roberto; Child, Camilla; Cullen, Joe

2015-01-01

The paper presents the results of an evaluation of the Emotional Intelligence (EI) and Organisational Intelligence (OI) competences self-assessment tools developed and applied by the IGUANA project. In the paper Emotional Intelligence and Organisational Intelligence competences are discussed, their use in action research experiments to assess and…

Quantum Machine Learning

OpenAIRE

Romero García, Cristian

2017-01-01

[EN] In a world in which accessible information grows exponentially, the selection of the appropriate information turns out to be an extremely relevant problem. In this context, the idea of Machine Learning (ML), a subfield of Artificial Intelligence, emerged to face problems in data mining, pattern recognition, automatic prediction, among others. Quantum Machine Learning is an interdisciplinary research area combining quantum mechanics with methods of ML, in which quantum properties allow fo...

How People Interact with Technology based on Natural and Artificial Intelligence

Directory of Open Access Journals (Sweden)

Vasile MAZILESCU

2017-04-01

Full Text Available This paper aims to analyse the different forms of intelligence within organizations in a systemic and inclusive vision, in order to design an integrated environment based on Artificial Intelligence (AI and Collective Intelligence (CI. This way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow, of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals, to the current approaches of connecting people on the use (automatic of operational knowledge to solve problems and make decisions based on intellectual cooperation. Few technologies have the big potential to review how we live, move, and work. Artificial intelligence (AI is nowdays equivalent of electricity and the Internet. AI is expected to bring massive shifts in how people perceive and interact with technology, with machines performing a wider range of tasks, in many cases doing a better job than humans.

Sense-making for intelligence analysis on social media data

Science.gov (United States)

Pritzkau, Albert

2016-05-01

Social networks, in particular online social networks as a subset, enable the analysis of social relationships which are represented by interaction, collaboration, or other sorts of influence between people. Any set of people and their internal social relationships can be modelled as a general social graph. These relationships are formed by exchanging emails, making phone calls, or carrying out a range of other activities that build up the network. This paper presents an overview of current approaches to utilizing social media as a ubiquitous sensor network in the context of national and global security. Exploitation of social media is usually an interdisciplinary endeavour, in which the relevant technologies and methods are identified and linked in order ultimately demonstrate selected applications. Effective and efficient intelligence is usually accomplished in a combined human and computer effort. Indeed, the intelligence process heavily depends on combining a human's flexibility, creativity, and cognitive ability with the bandwidth and processing power of today's computers. To improve the usability and accuracy of the intelligence analysis we will have to rely on data-processing tools at the level of natural language. Especially the collection and transformation of unstructured data into actionable, structured data requires scalable computational algorithms ranging from Artificial Intelligence, via Machine Learning, to Natural Language Processing (NLP). To support intelligence analysis on social media data, social media analytics is concerned with developing and evaluating computational tools and frameworks to collect, monitor, analyze, summarize, and visualize social media data. Analytics methods are employed to extract of significant patterns that might not be obvious. As a result, different data representations rendering distinct aspects of content and interactions serve as a means to adapt the focus of the intelligence analysis to specific information

Support vector machine in machine condition monitoring and fault diagnosis

Science.gov (United States)

Widodo, Achmad; Yang, Bo-Suk

2007-08-01

Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works.

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.

Machine learning for the meta-analyses of microbial pathogens' volatile signatures.

Science.gov (United States)

Palma, Susana I C J; Traguedo, Ana P; Porteira, Ana R; Frias, Maria J; Gamboa, Hugo; Roque, Ana C A

2018-02-20

Non-invasive and fast diagnostic tools based on volatolomics hold great promise in the control of infectious diseases. However, the tools to identify microbial volatile organic compounds (VOCs) discriminating between human pathogens are still missing. Artificial intelligence is increasingly recognised as an essential tool in health sciences. Machine learning algorithms based in support vector machines and features selection tools were here applied to find sets of microbial VOCs with pathogen-discrimination power. Studies reporting VOCs emitted by human microbial pathogens published between 1977 and 2016 were used as source data. A set of 18 VOCs is sufficient to predict the identity of 11 microbial pathogens with high accuracy (77%), and precision (62-100%). There is one set of VOCs associated with each of the 11 pathogens which can predict the presence of that pathogen in a sample with high accuracy and precision (86-90%). The implemented pathogen classification methodology supports future database updates to include new pathogen-VOC data, which will enrich the classifiers. The sets of VOCs identified potentiate the improvement of the selectivity of non-invasive infection diagnostics using artificial olfaction devices.

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.

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.

Screen-Printed Washable Electronic Textiles as Self-Powered Touch/Gesture Tribo-Sensors for Intelligent Human-Machine Interaction.

Science.gov (United States)

Cao, Ran; Pu, Xianjie; Du, Xinyu; Yang, Wei; Wang, Jiaona; Guo, Hengyu; Zhao, Shuyu; Yuan, Zuqing; Zhang, Chi; Li, Congju; Wang, Zhong Lin

2018-05-22

Multifunctional electronic textiles (E-textiles) with embedded electric circuits hold great application prospects for future wearable electronics. However, most E-textiles still have critical challenges, including air permeability, satisfactory washability, and mass fabrication. In this work, we fabricate a washable E-textile that addresses all of the concerns and shows its application as a self-powered triboelectric gesture textile for intelligent human-machine interfacing. Utilizing conductive carbon nanotubes (CNTs) and screen-printing technology, this kind of E-textile embraces high conductivity (0.2 kΩ/sq), high air permeability (88.2 mm/s), and can be manufactured on common fabric at large scales. Due to the advantage of the interaction between the CNTs and the fabrics, the electrode shows excellent stability under harsh mechanical deformation and even after being washed. Moreover, based on a single-electrode mode triboelectric nanogenerator and electrode pattern design, our E-textile exhibits highly sensitive touch/gesture sensing performance and has potential applications for human-machine interfacing.

Computational Intelligence in Early Diabetes Diagnosis: A Review

Science.gov (United States)

Shankaracharya; Odedra, Devang; Samanta, Subir; Vidyarthi, Ambarish S.

2010-01-01

The development of an effective diabetes diagnosis system by taking advantage of computational intelligence is regarded as a primary goal nowadays. Many approaches based on artificial network and machine learning algorithms have been developed and tested against diabetes datasets, which were mostly related to individuals of Pima Indian origin. Yet, despite high accuracies of up to 99% in predicting the correct diabetes diagnosis, none of these approaches have reached clinical application so far. One reason for this failure may be that diabetologists or clinical investigators are sparsely informed about, or trained in the use of, computational diagnosis tools. Therefore, this article aims at sketching out an outline of the wide range of options, recent developments, and potentials in machine learning algorithms as diabetes diagnosis tools. One focus is on supervised and unsupervised methods, which have made significant impacts in the detection and diagnosis of diabetes at primary and advanced stages. Particular attention is paid to algorithms that show promise in improving diabetes diagnosis. A key advance has been the development of a more in-depth understanding and theoretical analysis of critical issues related to algorithmic construction and learning theory. These include trade-offs for maximizing generalization performance, use of physically realistic constraints, and incorporation of prior knowledge and uncertainty. The review presents and explains the most accurate algorithms, and discusses advantages and pitfalls of methodologies. This should provide a good resource for researchers from all backgrounds interested in computational intelligence-based diabetes diagnosis methods, and allows them to extend their knowledge into this kind of research. PMID:21713313

Computational intelligence in early diabetes diagnosis: a review.

Science.gov (United States)

Shankaracharya; Odedra, Devang; Samanta, Subir; Vidyarthi, Ambarish S

2010-01-01

The development of an effective diabetes diagnosis system by taking advantage of computational intelligence is regarded as a primary goal nowadays. Many approaches based on artificial network and machine learning algorithms have been developed and tested against diabetes datasets, which were mostly related to individuals of Pima Indian origin. Yet, despite high accuracies of up to 99% in predicting the correct diabetes diagnosis, none of these approaches have reached clinical application so far. One reason for this failure may be that diabetologists or clinical investigators are sparsely informed about, or trained in the use of, computational diagnosis tools. Therefore, this article aims at sketching out an outline of the wide range of options, recent developments, and potentials in machine learning algorithms as diabetes diagnosis tools. One focus is on supervised and unsupervised methods, which have made significant impacts in the detection and diagnosis of diabetes at primary and advanced stages. Particular attention is paid to algorithms that show promise in improving diabetes diagnosis. A key advance has been the development of a more in-depth understanding and theoretical analysis of critical issues related to algorithmic construction and learning theory. These include trade-offs for maximizing generalization performance, use of physically realistic constraints, and incorporation of prior knowledge and uncertainty. The review presents and explains the most accurate algorithms, and discusses advantages and pitfalls of methodologies. This should provide a good resource for researchers from all backgrounds interested in computational intelligence-based diabetes diagnosis methods, and allows them to extend their knowledge into this kind of research.

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.

Pure intelligent monitoring system for steam economizer trips

Directory of Open Access Journals (Sweden)

Basim Ismail Firas

2017-01-01

Full Text Available Steam economizer represents one of the main equipment in the power plant. Some steam economizer's behavior lead to failure and shutdown in the entire power plant. This will lead to increase in operating and maintenance cost. By detecting the cause in the early stages maintain normal and safe operational conditions of power plant. However, these methodologies are hard to be achieved due to certain boundaries such as system learning ability and the weakness of the system beyond its domain of expertise. The best solution for these problems, an intelligent modeling system specialized in steam economizer trips have been proposed and coded within MATLAB environment to be as a potential solution to insure a fault detection and diagnosis system (FDD. An integrated plant data preparation framework for 10 trips was studied as framework variables. The most influential operational variables have been trained and validated by adopting Artificial Neural Network (ANN. The Extreme Learning Machine (ELM neural network methodology has been proposed as a major computational intelligent tool in the system. It is shown that ANN can be implemented for monitoring any process faults in thermal power plants. Better speed of learning algorithms by using the Extreme Learning Machine has been approved as well.

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.

Load Forecasting with Artificial Intelligence on Big Data

OpenAIRE

Glauner, Patrick; State, Radu

2016-01-01

In the domain of electrical power grids, there is a particular interest in time series analysis using artificial intelligence. Machine learning is the branch of artificial intelligence giving computers the ability to learn patterns from data without being explicitly programmed. Deep Learning is a set of cutting-edge machine learning algorithms that are inspired by how the human brain works. It allows to self-learn feature hierarchies from the data rather than modeling hand-crafted features. I...

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

Energy Technology Data Exchange (ETDEWEB)

Harber, K.S. (ed.)

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning bayesian expert system; a natural language generation system for a heterogeneous distributed database system; competence-switching'' managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries. These papers have been indexed separately.

The role of the artificial intelligence within the context of the human factors in the nuclear safety

Energy Technology Data Exchange (ETDEWEB)

Bayout Alvarenga, M A [Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil)

1994-12-31

The effective evaluation of a human-machine system depends heavily on a cognitive model of the human behaviour. The basic question is: How can we model the human cognition? The response should be found in the five disciplines that form the Cognitive Sciences: Artificial Intelligence, Cognitive Psychology, Neurophysiology, Linguistic, and Philosophy. Among them, the Artificial Intelligence appears as the catalyzer of the contributions and discoveries in the other four, trying to realize that cognitive model with the tools of the Computer Science. Sometimes, it seems as if these disciplines spoke different languages to describe the same ideas. It is necessary a holistic treatment of such questions that include the human cognition and its modelling. This becomes more clear when we observe that there are nowadays different methodologies that must be integrated in some way. This is the case of the symbolic approach (artificial intelligence), connectionist approach (neural networks) and the fuzzy logic. This paper makes a review of the available methodologies, showing the problems and the current solutions to answer the following question. How is possible to develop a human-machine system and an intelligent interface based on the Artificial Intelligence that fulfills the following characteristics: human-centered design, cognitive simulation of the human behaviour, and dynamic function allocation. This paper concludes with proposals of national projects to be applied to the Brazilian situation. (author). 28 refs.

The role of the artificial intelligence within the context of the human factors in the nuclear safety

International Nuclear Information System (INIS)

Bayout Alvarenga, M.A.

1994-01-01

The effective evaluation of a human-machine system depends heavily on a cognitive model of the human behaviour. The basic question is: How can we model the human cognition? The response should be found in the five disciplines that form the Cognitive Sciences: Artificial Intelligence, Cognitive Psychology, Neurophysiology, Linguistic, and Philosophy. Among them, the Artificial Intelligence appears as the catalyzer of the contributions and discoveries in the other four, trying to realize that cognitive model with the tools of the Computer Science. Sometimes, it seems as if these disciplines spoke different languages to describe the same ideas. It is necessary a holistic treatment of such questions that include the human cognition and its modelling. This becomes more clear when we observe that there are nowadays different methodologies that must be integrated in some way. This is the case of the symbolic approach (artificial intelligence), connectionist approach (neural networks) and the fuzzy logic. This paper makes a review of the available methodologies, showing the problems and the current solutions to answer the following question. How is possible to develop a human-machine system and an intelligent interface based on the Artificial Intelligence that fulfills the following characteristics: human-centered design, cognitive simulation of the human behaviour, and dynamic function allocation. This paper concludes with proposals of national projects to be applied to the Brazilian situation. (author). 28 refs

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.

Emerging Paradigms in Machine Learning

CERN Document Server

Jain, Lakhmi; Howlett, Robert

2013-01-01

This  book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The  multidisciplinary nature of machine learning makes it a very fascinating and popular area for research.  The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems.  Several chapters are devoted to computational learning models such as granular computing, rough sets and fuzzy sets An account of applications of well-known learning methods in biometrics, computational stylistics, multi-agent systems, spam classification including an extremely well-written survey on Bayesian networks shed light on the strengths and weaknesses of the methods. Practical studies yielding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary ...

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.

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.

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.

Challenging problems and solutions in intelligent systems

CERN Document Server

Grzegorzewski, Przemysław; Kacprzyk, Janusz; Owsiński, Jan; Penczek, Wojciech; Zadrożny, Sławomir

2016-01-01

This volume presents recent research, challenging problems and solutions in Intelligent Systems– covering the following disciplines: artificial and computational intelligence, fuzzy logic and other non-classic logics, intelligent database systems, information retrieval, information fusion, intelligent search (engines), data mining, cluster analysis, unsupervised learning, machine learning, intelligent data analysis, (group) decision support systems, intelligent agents and multi-agent systems, knowledge-based systems, imprecision and uncertainty handling, electronic commerce, distributed systems, etc. The book defines a common ground for sometimes seemingly disparate problems and addresses them by using the paradigm of broadly perceived intelligent systems. It presents a broad panorama of a multitude of theoretical and practical problems which have been successfully dealt with using the paradigm of intelligent computing.

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.

Artificial Intelligence: Threat or Boon to Radiologists?

Science.gov (United States)

Recht, Michael; Bryan, R Nick

2017-11-01

The development and integration of machine learning/artificial intelligence into routine clinical practice will significantly alter the current practice of radiology. Changes in reimbursement and practice patterns will also continue to affect radiology. But rather than being a significant threat to radiologists, we believe these changes, particularly machine learning/artificial intelligence, will be a boon to radiologists by increasing their value, efficiency, accuracy, and personal satisfaction. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Extreme learning machines 2013 algorithms and applications

CERN Document Server

Toh, Kar-Ann; Romay, Manuel; Mao, Kezhi

2014-01-01

In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability.   This book contains some selected papers from the International Conference on Extreme Learning Machine 2013, which was held in Beijing China, October 15-17, 2013. This conference aims to bring together the researchers and practitioners of extreme learning machine from a variety of fields including artificial intelligence, biomedical engineering and bioinformatics, system modelling and control, and signal and image processing, to promote research and discu...

Study of Tool Wear Mechanisms and Mathematical Modeling of Flank Wear During Machining of Ti Alloy (Ti6Al4V)

Science.gov (United States)

Chetan; Narasimhulu, A.; Ghosh, S.; Rao, P. V.

2015-07-01

Machinability of titanium is poor due to its low thermal conductivity and high chemical affinity. Lower thermal conductivity of titanium alloy is undesirable on the part of cutting tool causing extensive tool wear. The main task of this work is to predict the various wear mechanisms involved during machining of Ti alloy (Ti6Al4V) and to formulate an analytical mathematical tool wear model for the same. It has been found from various experiments that adhesive and diffusion wear are the dominating wear during machining of Ti alloy with PVD coated tungsten carbide tool. It is also clear from the experiments that the tool wear increases with the increase in cutting parameters like speed, feed and depth of cut. The wear model was validated by carrying out dry machining of Ti alloy at suitable cutting conditions. It has been found that the wear model is able to predict the flank wear suitably under gentle cutting conditions.

Simulation research on the process of large scale ship plane segmentation intelligent workshop

Science.gov (United States)

Xu, Peng; Liao, Liangchuang; Zhou, Chao; Xue, Rui; Fu, Wei

2017-04-01

Large scale ship plane segmentation intelligent workshop is a new thing, and there is no research work in related fields at home and abroad. The mode of production should be transformed by the existing industry 2.0 or part of industry 3.0, also transformed from "human brain analysis and judgment + machine manufacturing" to "machine analysis and judgment + machine manufacturing". In this transforming process, there are a great deal of tasks need to be determined on the aspects of management and technology, such as workshop structure evolution, development of intelligent equipment and changes in business model. Along with them is the reformation of the whole workshop. Process simulation in this project would verify general layout and process flow of large scale ship plane section intelligent workshop, also would analyze intelligent workshop working efficiency, which is significant to the next step of the transformation of plane segmentation intelligent workshop.

Affective Computing and Intelligent Interaction