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Design and Implementation of Intelligent Manufacturing Systems: From Expert Systems, Neural Networks, to Fuzzy Logic

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Design and Implementation of Intelligent Manufacturing Systems: From Expert Systems, Neural Networks, to Fuzzy Logic

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About

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  • brings together high-quality, original articles by researchers and practitioners which deal with several state-of-the-art aspects of design and implementation of intelligent systems.

Description

  • Copyright 1995
  • Dimensions: 7 x 9 1/4
  • Pages: 408
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-458217-9
  • ISBN-13: 978-0-13-458217-7
  • eBook (Adobe DRM)
  • ISBN-10: 0-13-244118-7
  • ISBN-13: 978-0-13-244118-6

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.

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Preface

The introduction of microprocessors and computer-controlled production tools into industry has given a new perspective to manufacturing processes both in the United States and abroad. Computer integrated manufacturing systems (CIMS), flexible manufacturing systems (FMS), group technology (GT), cellular manufacturing (CM), computer aided design (CAD), and computer aided manufacturing (CAM) have been considered by many as viable tools for reducing direct and indirect manufacturing costs and improving product quality and production flexibility. However, many of these new manufacturing techniques have not been able to become significantly efficient due to the inadequacy of the existing computer hardware and software.

The 1980's produced a remarkable growth in the area of the artificial intelligence (AI) which is viewed by many to be one of the most promising technologies for the factories of the future. In recent years, many papers and research results have reported the successful applications of artificial intelligence to engineering design and manufacturing planning and control.

The chapters in this book address the topics of intelligent manufacturing from a variety of theoretical, empirical, design, and implementation perspectives. The contributions to this volume represent a foundation for subsequent research work that could be done in this area that eventually would lead to efficient and intelligent manufacturing systems.

This volume consists of 15 chapters.

In the first chapter, Jana and Auslander present a workcell programming environment to model and implement prototype intelligent manufacturing systems.

In the second chapter, Reimann and Sarkis review a general conceptual system for computer aided process planning (CAPP) that was developed by the Consortium for Advanced Manufacturing - International (CAM-I). This framework specifies the structure and defines the functions necessary for automating the process planning of machined prismatic parts.

The third chapter, by Ali et al., proposes an artificial intelligence approach to metal forming processes and demonstrates the use of an intelligent hybrid tool to design and control the pack rolling process .

The fourth chapter, by Graham and Guan, describes a system for the monitoring and diagnosis of manufacturing systems which can best be described as a knowledge-based diagnosis system that uses a hybrid combination of symptom-based and functional reasoning.

An efficient real time control method for part routing using fuzzy parameters is introduced by Ben-Arieh and Lee in the fifth chapter.

Yeralan and Tan, in the sixth chapter, focus on high-level control language for embedded microcontroller applications. Their study investigates the suitability of fuzzy-logic control as a general-purpose high-level language for programming embedded microcontroller applications.

An application of neural networks to the monitoring and recognition of both periodic and aperiodic process signals that may be encountered in manufacturing processes is presented in chapter 7 by Hou and Lin.

In the eighth chapter, Indurkhya et al. report the results of study on modeling of Electro-Discharge Machining (EDM) and Wire Electro-Discharge Machining (WEDM) processes through an artificial neural network.

The ninth chapter, by Shashikumar and Kamrani, develops a knowledge-based expert system for selection of industrial robots using a LEVEL 5 expert system shell.

Chapter 10, by Chung and Vassiliadis, reports on the development of a case- based knowledge system called ShootDem-Ks which effectively troubleshoots product failures without the need of specially trained personnel.

Kamel and Ghenniwa, in chapter 11, introduce a general model of multi- machine systems that is able to represent different multi-machine environments including partially-overlapped systems. This model is based on the system's structure and its processing characteristics.

The use of an object-oriented paradigm as a means for the design and implementation of an intelligent process planning system is proposed by Usher in chapter 12.

Dong et al., in chapter 13, present a prototype feature-based automated process planning (FB APP) system to avoid costly traditional design and manufacturing processes later, and to make most product development decisions during the early stage of design.

Chapter 14, by Nnaji and Kang, discusses the role of the computer-aided design for an automatic machine programming system.

In the last chapter of this volume, Troxell et al. develop a framework to perform computer-assisted fault diagnosis of manufacturing processes.

We are indebted to our authors and reviewers for their outstanding contribution and assistance in preparation of this volume. We would also like to thank Dr. Herman R. Leep of the University of Louisville for his invaluable support and advice. Special word of thanks are due to Dongke An for providing exceptional help to make this endeavor possible. Finally, we would like to express our deepest gratitude to Bernard Goodwin and Michael Hays of Prentice-Hall for giving us the opportunity to initiate this project.

Hamid R. Parsaei

Mo Jamshidi

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