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The introduction of artificial intelligence, neural networks, and fuzzy logic into industry has given a new perspective to manufacturing processes in the U.S. and abroad. To help readers keep pace, this book addresses topics of intelligent manufacturing from a variety of theoretical, empirical, design, and implementation perspectives.
Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management addresses prominent concepts and applications of AI technologies in the management of networked manufacturing enterprises. The aim of this book is to align latest practices, innovation and case studies with academic frameworks and theories, where AI techniques are used efficiently for networked manufacturing enterprises. More specifically, it includes the latest research results and projects at different levels addressing quick-response system, theoretical performance analysis, performance and capability demonstration. The role of emerging AI technologies in the modelling, evaluation and optimisation of networked enterprises’ activities at different decision levels is also covered. Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management is a valuable guide for postgraduates and researchers in industrial engineering, computer science, automation and operations research.
This book is aimed at both researchers and practitioners, and provides a collection of expert systems in manufacturing and production engineering along with their knowledge base and rules. We believe that inclusion of the knowledge base and associated rules is essential if practitioners are to derive full benefit from these expert systems. This unique book is the result of our belief and the efforts of our distinguished colleagues who subscribe to this philosophy. A total of 15 different expert systems are included in this book. These expert systems are preceded by an introductory chapter written by Kuo, Preface XVll Mital and Anand. The expert system rules are included on a floppy disk in ASCII and can be easily accessed. These rules and the description of the expert system's structure should assist the users in customizing these systems. Overall, the expert systems included in this volume cover a fairly wide variety of manufacturing and production engineering topics.
Defining structure and functions of knowledge-based systems, this book presents hardware and software components of flexible machining, flexible assembly and computer-integrated manufacturing systems. Discussed are such areas as process planning, group technology and lay-out design.
This book focuses on the basic common technologies of smart manufacturing system and smart workshop. The applications of artificial intelligence in manufacturing system have been addressed from different perspectives, for example, smart optimization of cutting parameters, smart process planning, smart workshop and scheduling, and smart integration of process planning and scheduling. In the process of writing, this book highlights the combination of basic theory and engineering practice. In the basic theory part, the book clearly explains the basic issues of smart manufacturing system, including the core support technology of smart manufacturing, the basic theories and models of cutting parameter optimization, process optimization and scheduling, and the basic concepts and intelligence of smart manufacturing workshop model, optimization methods, etc. In the engineering practice part, this book enumerates a large number of research cases, trying to clearly demonstrate the basic problems of manufacturing system intelligence, and each chapter is accompanied by typical cases to help readers better understand and master the basic theories involved in stamping.
This six-volume set presents cutting-edge advances and applications of expert systems. Because expert systems combine the expertise of engineers, computer scientists, and computer programmers, each group will benefit from buying this important reference work. An "expert system" is a knowledge-based computer system that emulates the decision-making ability of a human expert. The primary role of the expert system is to perform appropriate functions under the close supervision of the human, whose work is supported by that expert system. In the reverse, this same expert system can monitor and double check the human in the performance of a task. Human-computer interaction in our highly complex world requires the development of a wide array of expert systems. Expert systems techniques and applications are presented for a diverse array of topics including Experimental design and decision support The integration of machine learning with knowledge acquisition for the design of expert systems Process planning in design and manufacturing systems and process control applications Knowledge discovery in large-scale knowledge bases Robotic systems Geograhphic information systems Image analysis, recognition and interpretation Cellular automata methods for pattern recognition Real-time fault tolerant control systems CAD-based vision systems in pattern matching processes Financial systems Agricultural applications Medical diagnosis
The quest for building systems that can function automatically has attracted a lot of attention over the centuries and created continuous research activities. As users of these systems we have never been satisfied, and demand more from the artifacts that are designed and manufactured. The current trend is to build autonomous systems that can adapt to changes in their environment. While there is a lot to be done before we reach this point, it is not possible to separate manufacturing systems from this trend. The desire to achieve fully automated manufacturing systems is here to stay. Manufacturing systems of the twenty-first century will demand more flexibility in product design, process planning, scheduling and process control. This may well be achieved through integrated software and hardware archi tectures that generate current decisions based on information collected from manufacturing systems environment, and execute these decisions by converting them into signals transferred through communication network. Manufacturing technology has not yet reached this state. However, the urge for achieving this goal is transferred into the term 'Intelligent Systems' that we started to use more in late 1980s. Knowledge-based systems, our first efforts in this endeavor, were not sufficient to generate the 'Intelligence' required - our quest still continues. Artificial neural network technology is becoming an integral part of intelligent manufacturing systems and will have a profound impact on the design of autonomous engineering systems over the next few years.
As we move towards the 21st century, industries are compelled to turn from "high productivity and high precision" to "more intelligent and more human-oriented technology". This volume presents the existing state of the art of production/precision engineering and illuminates areas in which future work may proceed.
Presents the findings of experts and practitioners from the major soft-computing themes Provides an overview of the theory and applications of IMS systems The Area of Intelligence in manufacturing has generated a considerable amount of interest occasionally verging on controversy, both in the research community and in the industrial sector. This proceedings looks at the broad manufacturing domain dealing with both technical and organizational issues, intelligent control is only part, albeit important, of optimal integration and control of intelligent techniques. The importance of creating a synergy of efforts aiming at efficient employment of intelligence in global technological development for manufacturing was recognized by the international IMS (intelligent manufacturing Systems) Initiative and is discussed in this proceedings volume.