Data Mining for Design and Manufacturing Book

	Preface
	Data Mining for Design and Manufacturing
Pt. I	Overview of Data Mining
1	Data Mining: An Introduction	1
2	A Survey of Methodologies and Techniques for Data Mining and Intelligent Data Discovery	41
Pt. II	Data Mining In Product Design
3	Data Mining in Scientific Data	61
4	Learning to Set Up Numerical Optimizations of Engineering Designs	87
5	Automatic Classification and Creation of Classification Systems Using Methodologies of "Knowledge Discovery in Databases (KDD)"	127
6	Data Mining for Knowledge Acquisition in Engineering Design	145
7	A Data Mining-Based Engineering Design Support System: A Research Agenda	161
Pt. III	Data Mining in Manufacturing
8	Data Mining for High Quality and Quick Response Manufacturing	179
9	Data Mining for Process and Quality Control in the Semiconductor Industry	207
10	Analyzing Maintenance Data Using Data Mining Methods	235
11	Methodology of Mining Massive Data Sets for Improving Manufacturing Quality/Efficiency	255
12	Intelligent Process Control System for Quality Improvement by Data Mining in the Process Industry	289
13	Data Mining by Attribute Decomposition with Semiconductor Manufacturing Case Study	311
14	Derivation of Decision Rules for the Evaluation of Product Performance Using Genetic Algorithms and Rough Set Theory	337
15	An Evaluation of Sampling Methods for Data Mining with Fuzzy C-Means	355
16	Colour Space Mining for Industrial Monitoring	371
17	Non-Traditional Applications of Data Mining	401
18	Fuzzy-Neural-Genetic Layered Multi-Agent Reactive Control of Robotic Soccer	417
Pt. IV	Enabling Technologies for Data Mining in Design and Manufacturing
19	Method-Specific Knowledge Compilation	443
20	A Study of Technical Challenges in Relocation of a Manufacturing Site	465
21	Using Imprecise Analogical Reasoning to Refine the Query Answers for Heterogeneous Multidatabase Systems in Virtual Enterprises	487
22	The Use of Process Capability Data in Design	505
	Index	519