Data Mining for Design and Manufacturing Methods and Applications
Data Mining for Design and Manufacturing: Methods and Applications is the first book that brings together research and applications for data mining within design and manufacturing. The aim of the book is 1) to clarify the integration of data mining in eng
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		    Data Mining for Design and Manufacturing Methods and Applications
 
 Edited by
 
 Dan Braha Ben-Gurion University
 
 SPRINGER-SCIENCE+BUSINESS MEDIA, B.V.
 
 A C.I.P. Catalogue record for this book is available from the Library of Congress.
 
 ISBN 978-1-4419-5205-9 DOI 10.1007/978-1-4757-4911-3
 
 ISBN 978-1-4757-4911-3 (eBook)
 
 Printed an acid-free paper
 
 AII Rights Reserved © 2001 Springer Science+Business Media Dordrecht Originally published by Kluwer Academic Publishers in 2001 No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written permission from the copyright owner.
 
 TABLE OF CONTENTS
 
 PREFACE Data Mining for Design and Manufacturing
 
 ix
 
 Dan Braha
 
 PART I: OVERVIEW OF DATA MINING 1 Data Mining: An Introduction
 
 1
 
 Ishwar K. Sethi
 
 2 A Survey of Methodologies and Techniques for Data Mining and Intelligent Data Discovery
 
 41
 
 Ricardo Gonzalez and Ali Kamrani
 
 PART II: DATA MINING IN PRODUCT DESIGN 3 Data Mining in Scientific Data
 
 61
 
 Stephan Rudolph and Peter Hertkorn
 
 4 Learning to Set Up Numerical Optimizations of Engineering Designs
 
 87
 
 Mark Schwabacher, Thomas Ellman, and Haym Hirsh
 
 5 Automatic Classification and Creation of Classification Systems Using Methodologies of "Knowledge Discovery in Databases (KDD)"
 
 127
 
 Hans Grabowski, Ralf-Stefan Lossack, and Jorg Wei/3kopf
 
 6 Data Mining for Knowledge Acquisition in
 
 145
 
 Engineering Design Yoko Ishino and Yan Jin
 
 7 A Data Mining-Based Engineering Design Support System: A Research Agenda Carol J Romanowski and Rakesh Nagi
 
 161
 
 vi
 
 OAT A MINING FOR DESIGN AND MANUFACTURING
 
 PART III: DATA MINING IN MANUFACTURING 8 Data Mining for High Quality and Quick Response Manufacturing
 
 179
 
 Jang-Hee Lee and Sang-Chan Park
 
 9 Data Mining for Process and Quality Control in the Semiconductor Industry
 
 207
 
 Mark Last and Abraham Kandel
 
 10 Analyzing Maintenance Data Using Data Mining Methods
 
 235
 
 Carol J Romanowski and Rakesh Nagi
 
 11 Methodology of Mining Massive Data Sets for Improving Manufacturing Quality/Efficiency
 
 255
 
 Jye-Chyi (JC) Lu
 
 12 Intelligent Process Control System for Quality Improvement by Data Mining in the Process Industry
 
 289
 
 Sewon Oh, Jooyung Han, and Hyunbo Cho
 
 13 Data Mining by Attribute Decomposition with Semiconductor Manufacturing Case Study
 
 311
 
 Oded Maimon and Lior S. Rokach
 
 14 Derivation of Decision Rules for the Evaluation of Product Performance Using Genetic Algorithms and Rough Set Theory
 
 337
 
 Zhai Lian-Yin, Khoo Li-Pheng, and Fok Sai-Cheong
 
 15 An Evaluation of Sampling Methods for Data Mining with Fuzzy C-Means
 
 355
 
 K. Josien, G. Wang, T. W. Liao, E. Triantaphyllou, and M. C. Liu
 
 16 Colour Space Mining for Industrial Monitoring K.J. Brazier, A.G. Deakin, R.D. Cooke, P.C. Russell, and G.R. Jones
 
 371
 
 TABLE OF CONTENTS
 
 17 Non-Traditional Applications of Data Mining
 
 VII
 
 401
 
 Andrew Kusiak
 
 18 Fuzzy-Neural-Genetic Layered Multi-Agent Reactive		
 
	 
	 
	 
	 
	 
	 
	 
	 
	 
	 
	