Manufacturing Intelligence for Industrial Engineering: Methods for System Self-organization, Learning, and Adaptation

406 Pages·2010·3.754 MB·English

by  Zude Zhou, Huaiqing Wang, Ping Lou

Manufacturing
Intelligence for
Industrial Engineering:
Methods for System
Self-Organization, Learning,
and Adaptation
Zude Zhou
Wuhan University of Technology, China
Huaiqing Wang
City University of Hong Kong, Hong Kong
Ping Lou
Wuhan University of Technology, China
EnginEEring sciEncE rEfErEncE
Hershey • New York
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Library of Congress Cataloging-in-Publication Data
Zhou, Zude, 1946-
Manufacturing intelligence for industrial engineering : methods for system self-organization, learning, and adaptation / by
Zude Zhou, Huaiqing Wang, and Ping Lou.
p. cm.
Includes bibliographical references and index.
Summary: "This book focuses on the latest innovations in the process of manufacturing in engineering"--Provided by publisher.
ISBN 978-1-60566-864-2 (hardcover) -- ISBN 978-1-60566-865-9 (ebook) 1. Technological innovations. 2. Industrial
engineering. 3. Artificial intelligence. I. Wang, Huaiqing. II. Lou, Ping. III. Title. T173.8.Z486 2010
670.285--dc22
2009034472
British Cataloguing in Publication Data
A Cataloguing in Publication record for this book is available from the British Library.
All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the
authors, but not necessarily of the publisher.
Table of Contents
Foreword .............................................................................................................................................vii
Preface ..................................................................................................................................................ix
Chapter 1
Intelligent Manufacturing and Manufacturing Intelligence ....................................................................1
Introduction .............................................................................................................................................1
Manufacturing Activities .........................................................................................................................2
Artificial Intelligence and Manufacturing Intelligence ...........................................................................3
Intelligent Manufacturing .......................................................................................................................4
Summary ...............................................................................................................................................11
References .............................................................................................................................................11
Chapter 2
Knowledge-Based Systems ...................................................................................................................13
Introduction ...........................................................................................................................................13
The Process of Building KBS-Knowledge Engineering ........................................................................16
KBS Evaluation .....................................................................................................................................31
Applications of KBS in Intelligent Manufacturing ................................................................................34
Case Study .............................................................................................................................................36
Summary ...............................................................................................................................................44
References .............................................................................................................................................44
Chapter 3
Intelligent Agents and Multi-Agent Systems ........................................................................................47
Intelligent Agents ..................................................................................................................................47
Basic Theories of Multi-Agent Systems .................................................................................................52
Communication and Interaction Protocol in MAS ...............................................................................59
Cooperation and Behavior Coordination .............................................................................................64
Applications of Agent in Intelligent Manufacturing .............................................................................70
Case Study .............................................................................................................................................74
Summary ...............................................................................................................................................81
References .............................................................................................................................................81
Chapter 4
Data Mining and Knowledge Discovery ...............................................................................................84
Introduction ...........................................................................................................................................84
Basic Analysis .......................................................................................................................................92
Methods and Tools for DMKD ..............................................................................................................96
Application of DM and KD in Manufacturing Systems ......................................................................102
Case Study ...........................................................................................................................................105
Summary .............................................................................................................................................109
References ...........................................................................................................................................110
Chapter 5
Computational Intelligence .................................................................................................................111
Introduction .........................................................................................................................................111
Artificial Neural Networks ..................................................................................................................113
Fuzzy System .......................................................................................................................................120
Evolutionary Computation ..................................................................................................................125
Case Study ...........................................................................................................................................130
Summary .............................................................................................................................................134
References ...........................................................................................................................................134
Chapter 6
Business Process Modeling and Information Systems Modeling .......................................................137
Introduction .........................................................................................................................................137
Modeling Techniques ..........................................................................................................................142
Case Study: Conceptual Modeling of Collaborative Manufacturing for Customized Products .........150
Summary .............................................................................................................................................156
References ...........................................................................................................................................156
Chapter 7
Sensor Integration and Data Fusion Theory .......................................................................................160
Introduction .........................................................................................................................................160
Data Fusion ........................................................................................................................................167
The Methods of Data Fusion ...............................................................................................................172
Applications of Multi-Sensor Information Fusion ..............................................................................174
Case Study ...........................................................................................................................................181
Summary .............................................................................................................................................186
References ...........................................................................................................................................186
Chapter 8
Group Technology ...............................................................................................................................189
Introduction .........................................................................................................................................189
Part Family Formation: Coding and Classification Systems .............................................................192
Group Technology in Intelligent Manufacturing ................................................................................209
Summary .............................................................................................................................................211
References ...........................................................................................................................................211
Chapter 9
Intelligent Control Theory and Technologies .....................................................................................214
Introduction .........................................................................................................................................214
Foundations of Intelligent Control .....................................................................................................215
Models for Intelligent Controllers ......................................................................................................219
Intelligent Control Technologies .........................................................................................................221
Intelligent Control Systems .................................................................................................................226
Challenges of Intelligent Control Technologies ..................................................................................236
Neural Network Based Robotic Control: A Case Study ......................................................................237
Summary .............................................................................................................................................242
References ...........................................................................................................................................242
Chapter 10
Intelligent Product Design: Intelligent CAD ......................................................................................245
Introduction .........................................................................................................................................245
Research and Application of ICAD .....................................................................................................251
Technique and Research Methods of ICAD ........................................................................................256
Case Study ...........................................................................................................................................264
Summary .............................................................................................................................................270
References ...........................................................................................................................................271
Chapter 11
Intelligent Process Planning: Intelligent CAPP ..................................................................................273
Introduction .........................................................................................................................................273
Application of GA to Computer-Aided Process Planning ...................................................................277
The Implementation of ANN in CAPP System ...................................................................................281
The Use of Case-Based Reasoning in CAPP ......................................................................................286
Multi-Agent-Based CAPP ...................................................................................................................289
Case Study ...........................................................................................................................................296
Summary .............................................................................................................................................299
References ...........................................................................................................................................299
Chapter 12
Intelligent Diagnosis and Maintenance ...............................................................................................301
Introduction .........................................................................................................................................301
Diagnosis Techniques .........................................................................................................................304
Remote Intelligent Diagnosis and Maintenance System .....................................................................312
Multi-Agent-Based Intelligent Diagnosis System ...............................................................................316
Case Study ...........................................................................................................................................319
Future of Intelligent Diagnosis ...........................................................................................................324
Summary .............................................................................................................................................325
References ...........................................................................................................................................327
Chapter 13
Intelligent Management Information System .....................................................................................229
Introduction .........................................................................................................................................229
IMIS Methodologies ............................................................................................................................330
Case Study I: Multi-Agent IDSS Based on Blackboard ......................................................................337
Case Study II: Intelligent Reconfigurable ERP System ......................................................................339
Summary .............................................................................................................................................355
References ...........................................................................................................................................355
Chapter 14
Trend and Prospect of Manufacturing Intelligence .............................................................................357
Introduction .........................................................................................................................................357
Driving Forces and Challenges of the Manufacturing Industry .........................................................359
Reviews on Forementioned MI Technologies......................................................................................367
MI vs Conventional Technologies in manufacturing ..........................................................................371
Prospect of Manufacturing Intelligence .............................................................................................377
Summary .............................................................................................................................................383
References ...........................................................................................................................................384
About the Authors .............................................................................................................................388
Index ...................................................................................................................................................390
vii
Foreword
Manufacturing engineering has come a long way, from the “black art” in the 1800s to the first scientific
analysis of machining operations by F.W. Taylor in early 1900s (On the Art of Cutting Metals, 1906).
In the early 1950s, computers were developed to take control of machine tools and NC machines were
born, and later, CNC machines. The 60s and 70s saw a rapid proliferation of software and hardware
development in support of manufacturing operations in the form of design, analysis, planning, process-
ing, measurement, dispatch and distribution. The late M Eugene Merchant, then Director of Research
Planning of Cincinnati Milacron Inc., made an exciting Delphi-type technological forecast of the future
of production engineering at the General Assembly of CIRP in Warsaw, 1971. Five years later, he made
another report on the “Future Trends in Manufacturing – Towards the Year 2000” in the 1976 CIRP GA
in Paris. He reported that between then (1976) and the year 2000, the overall future trend in manufac-
turing will be towards the implementation of the computer-integrated automatic factories. More than
30 years had since whisked past, manufacturing technologies had indeed progressed even more rapidly
than Dr Merchant’s prediction then.
Manufacturing operations have changed from programmed operations to programmable operations.
In the last two decades, many manufacturing operations and processes have become near autonomous,
i.e. they possess sufficient intelligence to diagnose, optimize, decide and correct any actions with mini-
mum human interaction. Some systems can acquire and learn from past cases and become increasingly
more “learned” through usage. Machine tools which are Internet-enabled can be continuously monitored
by their manufacturers and their “state-of-heath” is exactly known and predictable to enable the reduc-
tion of breakdown time and to ensure timely maintenance. Computer-integrated Manufacturing (CIM)
has evolved to become Computer-Human Integrated Manufacturing (CHIM). Seamless integration of
human and computer intelligence is another measure to capture the perfect complementation between
man and machine.
It is with great pleasure to witness this new book ‘Manufacturing Intelligence for Industrial Engineer-
ing: Methods for System Self-Organization, Learning and Adaption’ by Zude Zhou, Qinghuai Wang and
Ping Lou. It is a timely capture of the state-of-the-art development of intelligent manufacturing processes,
covering a vast amount of materials from design, planning, diagnosis, information control, agents, and
many enabling platforms and supporting theories. I have, beyond doubt, that this contribution will be
invaluable to researchers as well graduate students in the field of manufacturing engineering.
I sincerely congratulate the authors on having produced this splendid new book
A. Y. C. Nee, DEng, PhD
National University of Singapore
Regional Editor IJAMT
Regional Editor IJMTM
viii
A. Y. C. Nee received his PhD from the Victoria University of Manchester in 1973 and Doctor of Engineering (DEng) degree
from UMIST in 2002. He joined then University of Singapore as a faculty member in 1974. He has held various administrative
positions including Head of Department of Mechanical Engineering from 1993 to 1996, Dean of Faculty of Engineering from
1995 to 1998, other appointments include: Director of Office of Quality Management, Dean of Admissions, CEO of Design
Technology Institute, Co-Director Singapore-MIT Alliance, Deputy Executive Director, then NSTB SERC, Director of Office of
Research. Prof Nee received his National Day Award in Public Administration—PPA(P) in 2007. Professor Nee is well known
in the field of manufacturing engineering. His research focuses on computer-aided design of fixtures, molds and dies, distrib-
uted manufacturing systems, AI and augmented reality applications in manufacturing. He was selected a Fellow of the Society
of Manufacturing Engineers with citation in 1990, and a Fellow of the International Academy for Production Engineering
(CIRP) in the same year. He was elected as Vice-President (Elect) at the CIRP recent senate meeting in August 2009, and will
be Vice President in August 2010 and President of CIRP from August 2011. He has published over 250 papers in international
refereed journals, 5 authored and 5 edited books. Professor Nee is regional editor of International Journal of Machine Tools
and Manufacture, and International Journal of Advanced Manufacturing Technology. In addition, he is editorial board member
and associate editor of another 20 refereed journals. He is also Chairman of an NUS spin-off company—Manusoft Technolo-
gies Pte Ltd established in 1997.
ix
Preface
The environment of the manufacturing industry has changed impressively during this half century. New
theories and technologies in the field of computers, networks, distributed computation, and artificial
intelligence are extensively used in the manufacturing area. Integration and intelligence have become
the developing trends of future manufacturing systems. These inform the concept of manufacturing
change from the narrow sense of fabrication technique to the broad sense of extensive manufacture,
that is, from the transformation of raw materials into finished goods, to the whole process of the prod-
uct life cycle involving product design, fabrication, planning, managing, and distribution. Intelligent
manufacturing will become one the most promising manufacturing technologies in the next generation
of manufacturing industries.
Manufacturing Intelligence (MI), as a new discipline of manufacturing engineering, focuses on sci-
entific foundations and key technologies for developing, describing, integrating, sharing, and processing
intelligent activities in the process of manufacturing. It mainly covers intelligent-control theory and
technology for manufacturing equipment, intelligent management and decision making for the manu-
facturing process, intelligent processing of manufacturing information, representation and reasoning of
manufacturing knowledge, as well as intelligent surveillance and diagnosis for manufacturing equipment
and systems.
Clearly, MI is different from Artificial Intelligence (AI). AI is one aspect of theoretical research led
by the requirements of mimicking human intelligence. It mainly focuses on exploring the mechanism of
the process of human intelligent activities and emphasizes general theories, which highlight explorations
of theory, as well as having serious logicality and reasoning. By contrast, MI mainly studies the mimicry
of human intelligence to solve issues with intelligent computers (including software and hardware), and
is a type of foundational research led by the requirements of applications in the manufacturing field.
Although these two disciplines are different, they are related each other. AI is one of the main founda-
tions of MI and the development of MI and the solution to the issues unsolved by AI will accelerate the
development of AI.
This book consists of four parts with fourteen chapters which include engineering background, founda-
tions, technologies, applications, implementations, case studies, trends of intelligent manufacturing, and
prospects for manufacturing intelligence. Part I contains one chapters, viz. chapter 1, which introduces
manufacturing intelligence, the development of intelligent manufacturing, and the features of intelligent
activities in the process of manufacturing. Part II and Part III including twelve chapters constitute the
main part of this book. In these two parts, scientific foundations, key technologies and pragmatic appli-
cations of manufacturing intelligence are analyzed. Among them, chapters 2 to 8 composing the Part II
offer an extensive presentation of the engineering scientific foundations in manufacturing intelligence.
Chapter 2 describes knowledge-based systems which mainly details general approaches for knowledge
representation, acquirement, and general techniques for searching and reasoning. Chapter 3 presents