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Tables of Contents for Computational Intelligence in Design and Manufacturing Handbook
Chapter/Section Title
Page #
Page Count
PART I Overview
Computational Intelligence for Manufacturing
D. T. Pham
P. T. N. Pham
Introduction
1
1
Knowledge-Based Systems
1
3
Fuzzy Logic
4
3
Inductive Learning
7
4
Neural Networks
11
4
Genetic Algorithms
15
4
Some Applications in Engineering and Manufacture
19
6
Conclusion
25
Neural Network Applications in Intelligent Manufacturing: An Updated Survey
Jun Wang
Wai Sum Tang
Catherine Roze
Introduction
1
2
Modeling and Design of Manufacturing Systems
3
7
Modeling, Planning, and Scheduling of Manufacturing Processes
10
4
Monitoring and Control of Manufacturing Processes
14
4
Quality Control, Quality Assurance, and Fault Diagnosis
18
5
Concluding Remarks
23
Holonic Metamorphic Architectures for Manufacturing: Identifying Holonic Structures in Multiagent Systems by Fuzzy Modeling
Michaela Ulieru
Dan Stefanoiu
Douglas Norrie
Introduction
1
1
Agent-Oriented Manufacturing Systems
2
1
The MetaMorph Project
3
6
Holonic Manufacturing Systems
9
2
Holonic Self-Organization of MetaMorph via Dynamic Virtual Clustering
11
3
Automatic Grouping of Agents into Holonic System: Simulation Results
14
12
MAS Self-Organization as a Holonic System: Simulation Results
26
10
Conclusions
36
PART II Manufacturing System Modeling and Design
Neural Network Applications for Group Technology and Cellular Manufacturing
Nallan C. Suresh
Introduction
1
2
Artificial Neural Networks
3
2
A Taxonomy of Neural Network Application for GT/CM
5
14
Conclusions
19
Application of Fuzzy Set Theory in Flexible Manufacturing System Design
A. Kazerooni
K. Abhary
L. H. S. Luong
F. T. S. Chan
Introduction
1
1
A Multi-Criterion Decision-Making Approach for Evaluation of Scheduling Rules
2
2
Justification of Representing Objectives with Fuzzy Sets
4
1
Decision Points and Associated Rules
4
1
A Hierarchical Structure for Evaluation of Scheduling Rules
4
7
A Fuzzy Approach to Operation Selection
11
4
Fuzzy-Based Part Dispatching Rules in FMSs
15
2
Fuzzy Expert System-Based Rules
17
4
Selection of Routing and Part Dispatching Using Membership Functions and Fuzzy Expert System-Based Rules
21
Genetic Algorithms in Manufacturing System Design
L. H. S. Luong
M. Kazerooni
K. Abhary
Introduction
1
1
The Design of Cellular Manufacturing Systems
2
2
The Concepts of Similarity Coefficients
4
3
A Genetic Algorithm for Finding the Optimum Process Routings for Parts
7
3
A Genetic Algorithm to Cluster Machines into Machine Groups
10
2
A Genetic Algorithm to Cluster Parts into Part Families
12
1
Layout Design
13
1
A Genetic Algorithm for Layout Optimization
14
2
A Case Study
16
3
Conclusion
19
Intelligent Design Retrieving Systems Using Neural Networks
C. Alec Chang
Chieh-Yuan Tsai
Introduction
1
1
Characteristics of Intelligent Design Retrieval
2
1
Structure of an Intelligent System
3
2
Performing Fuzzy Association
5
1
Implementation Example
5
PART III Process Planning and Scheduling
Soft Computing for Optimal Planning and Sequencing of Parallel Machining Operations
Yuan-Shin Lee
Nan-Chieh Chiu
Shu-Cherng Fang
Introduction
1
2
A Mixed Integer Program
3
2
A Genetic-Based Algorithm
5
4
Tabu Search for Sequencing Parallel Machining Operations
9
3
Two Reported Examples Solved by the Proposed GA
12
6
Two Reported Examples Solved by the Proposed Tabu Search
18
4
Random Problem Generator and Further Tests
22
4
Conclusion
26
Application of Genetic Algorithms and Simulated Annealing in Process Planning Optimization
Y. F. Zhang
A. Y. C. Nee
Introduction
1
2
Modeling Process Planning Problems in an Optimization Perspective
3
10
Applying a Genetic Algorithm to the Process Planning Problem
13
5
Applying Simulated Annealing to the Process Planning Problem
18
5
Comparison between the GA and the SA Algorithm
23
1
Conclusions
24
Production Planning and Scheduling Using Genetic Algorithms
Runwei Cheng
Mitsuo Gen
Introduction
1
1
Resource-Constrained Project Scheduling Problem
1
8
Parallel Machine Scheduling Problem
9
8
Job-Shop Scheduling Problem
17
8
Multistage Process Planning
25
3
Part Loading Scheduling Problem
28
PART IV Manufacturing Process Monitoring and Control
Neural Network Predictive Process Models: Three Diverse Manufacturing Applications
Sarah S. Y. Lam
Alice E. Smith
Introduction to Neural Network Predictive Process Models
1
1
Ceramic Slip Casting Application
2
2
Abrasive Flow Machining Application
4
5
Chemical Oxidation Application
9
2
Concluding Remarks
11
Neural Network Applications to Manufacturing Processes: Monitoring and Control
Hyung Suck Cho
Introduction
1
1
Manufacturing Process Monitoring and Control
2
4
Neural Network-Based Monitoring
6
4
Quality Monitoring Applications
10
9
Neural Network-Based Control
19
3
Process Control Applications
22
9
Conclusions
31
Computational Intelligence in Microelectronics Manufacturing
Gary S. May
Introduction
1
1
The Role of Computational Intelligence
2
9
Process Modeling
11
8
Optimization
19
13
Process Monitoring and Control
32
9
Process Diagnosis
41
11
Summary
52
Monitoring and Diagnosing Manufacturing Processes Using Fuzzy Set Theory
R. Du
Yangsheng Xu
Introduction
1
1
A Brief Description of Fuzzy Set Theory
2
6
Monitoring and Diagnosing Manufacturing Processes Using Fuzzy Sets
8
15
Application Examples
23
4
Conclusions
27
Fuzzy Neural Network and Wavelet for Tool Condition Monitoring
Xiaoli Li
Introduction
1
1
Fuzzy Neural Network
2
5
Wavelet Transforms
7
3
Tool Breakage Monitoring with Wavelet Transforms
10
2
Identification of Tool Wear States Using Fuzzy Method
12
11
Tool Wear Monitoring with Wavelet Transforms and Fuzzy Neural Network
23
PART V Quality Assurance and Fault Diagnosis
Neural Networks and Neural-Fuzzy Approaches in an In-Process Surface Roughness Recognition System for End Milling Operations
Joseph C. Chen
Introduction
1
1
Methodologies
2
6
Experimental Setup and Design
8
3
The In-Process Surface Roughness Recognition Systems
11
3
Testing Results and Conclusions
14
Intelligent Quality Controllers for On-Line Parameter Design
Ratna Babu Chinnam
Introduction
1
5
An Overview of Certain Emerging Technologies Relevant to On-Line Parameter Design
6
3
Design of Quality Controllers for On-Line Parameter Design
9
5
Case Study: Plasma Etching Process Modeling and On-Line Parameter Design
14
7
Conclusion
21
A Hybrid Neural Fuzzy System for Statistical Process Control
Shing I Chang
Statistical Process Control
1
2
Neural Network Control Charts
3
1
A Hybrid Neural Fuzzy Control Chart
4
12
Design, Operations, and Guidelines for Using the Proposed Hybrid Neural Fuzzy Control Chart
16
2
Properties of the Proposed Hybrid Neural Fuzzy Control Chart
18
1
Final Remarks
19
RClass*: A Prototype Rough-Set and Genetic Algorithms Enhanced Multi-Concept Classification System for Manufacturing Diagnosis
Li-Pheng Khoo
Lian-Yin Zhai
Introduction
1
1
Basic Notions
2
5
A Prototype Multi-Concept Classification System
7
3
Validation of RClass*
10
2
Application of RClass* to Manufacturing Diagnosis
12
4
Conclusions
16
Index
I-1