Handbook of Expert Systems Applications in Manufacturing Structures and rules

411 Pages·1994·10.29 MB·English

by  Tsuang Kuo

Handbook of Expert Systems Applications
in Manufacturing
Intelligent Manufacturing Series
Series Editor: Andrew Kusiak
Department of Industrial Engineering
The University of Iowa, USA
Manufacturing has been issued a great challenge - the challenge of Artificial
Intelligence (AI). We are witnessing the proliferation of applications of AI
in industry, ranging from finance and marketing to design and manufactur
ing processes. AI tools have been incorporated into computer-aided design
and shop-floor operations software, as well as entering use in logistics
systems.
The success of AI in manufacturing can be measured by its growing
number of applications, releases of new software products and in the many
conferences and new publications. This series on Intelligent Manufacturing
has been established in response to these developments, and will include
books on topics such as:
• design for manufacturing
• concurrent engineering
• process planning
• production planning and scheduling
• programming languages and environments
• design, operations and management of intelligent systems
Some of the titles are more theoretical in nature, while others emphasize an
industrial perspective. Books dealing with the most recent developments will
be edited by leaders in the particular fields. In areas that are more
established, books written by recognized authors are planned.
We are confident that the titles in the series will be appreciated by
students entering the field of intelligent manufacturing, academics, design
and manufacturing managers, system engineers, analysts and programmers.
Titles available
Object-oriented Software for Manufacturing Systems
Edited by S. Adiga
Integrated Distributed Intelligence Systems in Manufacturing
M. Rao, Q. Wang and J. Cha
Artificial Neural Networks for Intelligent Manufacturing
Edited by C.H. Dagli
Handbook of Expert Systems Applications in Manufacturing
Structures and rules
Edited by A. Mital and S. Anand
Handbook of Expert Systems
Applications in Manufacturing
Structures and rules
Edited by
A. Mital
Industrial Engineering, University of Cincinnati, Cincinnati, USA
and
S. Anand
Industrial Engineering, University of Cincinnati, Cincinnati, USA
ES
SPRINGER-SCIENCE+BUSINESS MEDIA, B.V.
First edition 1994
© 1994 Springer Science+Business Media Dordrecht
Originally published by Chapman & Hall in 1994
Softcover reprint of the hardcover 1st edition 1994
Typeset in Times 10/12 by Interprint Limited, Malta
ISBN 978-94-010-4302-1 ISBN 978-94-011-0703-7 (eBook)
DOI 10.1007/978-94-011-0703-7
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To
Little Aashi and Growing Anubhav for their
Undemanding Love
And
Our Wives, Chetna and Meera, for their
Inspiration and Encouragement
Contents
List of contributors xiii
Preface xvii
1 An introduction to expert systems in production and
manufacturing engineering: the structure, development process
and applications
Tsuang Kuo, Anil Mital and Sam Anand
1.1 Introduction 1
1.2 Expert system basics 3
1.3 Development process of expert systems 8
1.4 Expert systems in production and manufacturing 10
1.5 Concluding remarks 16
References 17
2 Operations research/artificial intelligence rules for the optimal
design of manufacturing systems: machine and traffic allocation
Mario Van Vliet
2.1 Introduction 21
2.2 OR/AI models for manufacturing system design 22
2.3 Allocation problems 24
2.4 Concluding remarks 41
References 43
3 A common skeletal framework for knowledge-based solutions to
a representative set of manufacturing problems
M. M arefat and P. Banerjee
3.1 Introduction 45
3.2 A simplified framework 48
3.3 A hierarchical problem-solving framework 52
3.4 Applying the framework 56
2.5 Concluding discussion 76
Acknowledgment 77
References 78
Vlll Contents
4 A general purpose knowledge-based system and its application to
design problems
Setsuo Ohsuga and Jiebo Guan
4.1 Introduction 81
4.2 Model building 82
4.3 Knowledge bases for feedback control systems design 92
4.4 Conclusion 106
References 106
5 A knowledge-based system for selection of resource allocation
rules and algorithms
Gursel A. Suer and Cihan H. Dagli
5.1 Introduction 108
5.2 Knowledge-based scheduling systems 110
5.3 Problem definition 111
5.4 Performance measures 112
5.5 Background 112
5.6 Rules 115
5.7 Schedule generation techniques 116
5.8 Algorithms 117
5.9 An example 123
5.10 Experimentation performed 125
5.11 The structure of the rules 127
5.12 Computational requirements 128
Acknowledgments 128
References 128
6 An intelligent shop management system for production supervision
Gary P. Moynihan
6.1 Introduction 130
6.2 Method and scope 131
6.3 Development of the supervisory model 132
6.4 Description of the prototype system 134
6.5 Shop parameters 137
6.6 Resource allocation and scheduling 137
6.7 Situation assessment 140
6.8 Projection and replanning 143
~ Coocl~~ 1~
References 146
7 Intelligent systems for conceptual design of mechanical products
Qun Wang, Ming Rao and Ji Zhou
7.1 Conceptual design automation 148
7.2 Problem-solving strategy 151
Contents IX
7.3 System configuration 158
7.4 Function and structure conceptual design 164
7.5 Parameter design 173
7.6 Scheme analysis 176
7.7 Comprehensive evaluation 178
7.8 Decision making 182
7.9 Redesign 182
7.10 Application case study 183
Acknowledgments 192
References 192
8 Knowledge-based surface treatment and coating selection in
product design
Chanan S. Syan
8.1 Introduction 194
8.2 Design for economic manufacture (DEM) and
surface T/Cs 194
8.3 The T/C selection problem 196
8.4 Knowledge elicitation in TESS 197
8.5 TESS knowledge-based system 198
8.6 TESS system methodology 198
8.7 Representation of rules in TESS 203
8.8 TESS - inference mechanism (1M) 203
8.9 User/TESS interaction 204
8.10 Explanation facilities 205
8.11 System rules, goals and uncertainty handling 205
8.12 System terminology dictionary 207
8.13 Discussion and further work 207
References 208
9 Expert system for casting design evaluation
I.e. You, e.N. Chu and R.L. Kashyap
9.1 Introduction 210
9.2 Feature-based design 213
9.3 Three-dimensional pattern model 216
9.4 Local shape analysis based on pattern primitive pairs 218
9.5 Knowledge representation and control structure for local
shape analysis 220
9.6 Global shape analysis 226
9.7 Implementation 233
9.8 Conclusions 235
Acknowledgments 235
References 236
x Contents
10 Expert system approaches to the selection of materials handling
and transfer equipment
Jacob Rubinovitz and Reuven Karni
10.1 Introduction 238
10.2 MHT and expert systems 239
10.3 MHT and engineering design 240
10.4 AI-based advisory design tools 241
10.5 A taxonomy of MHT 242
10.6 A conceptual framework for constructing expert systems for
selection 244
10.7 Paradigms for expert systems for selection 246
10.8 Attribute priority weights 249
10.9 Case studies 253
10.10 Expert system outputs - initial equipment selection 253
10.11 Using the expert system in design 258
10.12 Selecting MHT equipment 263
10.13 Discussion 267
References 267
11 A knowledge-based system for scheduling in a flexible
manufacturing system
Suranjan De and Anita Lee
11.1 Introduction 269
11.2 FMS scheduling problem 270
11.3 KBS architecture 270
11.4 Knowledge representation 272
11.5 Production schedule generation 280
11.6 Conclusion 286
References 287
12 'Optimal' rule switching for flow shops with random workloads
James C. Chen and Arne Thesen
12.1 Introduction 288
12.2 A two-machine flow shop 290
12.3 Developing the knowledge base 291
12.4 Evaluation 296
12.5 Conclusions 300
Acknowledgment 301
References 301
13 An expert system approach to surface mount pick-and-place
machine selection
Chung-Yu Liu, c.R. Emerson and K. Srihari
13.1 Introduction 303
13.2 Concepts used in this research 304
Contents Xl
13.3 Problem statement and research objective 308
13.4 System design and specifications 309
13.5 Accomplishments and limitations 319
13.6 Conclusion 319
References 320
14 FIX PERT: a rule-based system for workholding device selection
of rotational parts
B. Bibanda, P.R. Cohen and C. Tunasar
14.1 Introduction and system overview 321
14.2 Background 322
14.3 The fix turing decision package 327
14.4 System structure 330
14.5 Sample session 338
14.6 Summary and conclusions 341
References 341
15 Learning in robotic task planning
Nina M. Berry and Soundar R. T. Kumara
15.1 Introduction 343
15.2 Robotic task planning 344
15.3 Implementations of planning ideas 346
15.4 TheoAgent 359
15.5 Conclusion and future work 368
References 368
16 An expert system with an external optimization module for
quality control decisions
Alice E. Smith and Cihan R. Dagli
16.1 Introduction 370
16.2 Overview of control charts and acceptance sampling plans 371
16.3 The expert system structure 373
16.4 The system domain 376
16.5 Conclusions and implications for the future 379
Acknowledgments 380
References 380
Index 382
Paper titles and the corresponding directories and knowledge-base files