Data Mining for Design and Manufacturing: Methods and Applications

✍ Scribed by Ishwar K. Sethi (auth.), Dan Braha (eds.)

Publisher: Springer US
Year: 2001
Tongue: English
Leaves: 530
Series: Massive Computing 3
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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 engineering design and manufacturing, 2) to present a wide range of domains to which data mining can be applied, 3) to demonstrate the essential need for symbiotic collaboration of expertise in design and manufacturing, data mining, and information technology, and 4) to illustrate how to overcome central problems in design and manufacturing environments. The book also presents formal tools required to extract valuable information from design and manufacturing data, and facilitates interdisciplinary problem solving for enhanced decision making.
Audience: The book is aimed at both academic and practising audiences. It can serve as a reference or textbook for senior or graduate level students in Engineering, Computer, and Management Sciences who are interested in data mining technologies. The book will be useful for practitioners interested in utilizing data mining techniques in design and manufacturing as well as for computer software developers engaged in developing data mining tools.

✦ Table of Contents

Front Matter....Pages i-xviii
Data Mining: An Introduction....Pages 1-40
A Survey of Methodologies and Techniques for Data Mining and Intelligent Data Discovery....Pages 41-59
Data Mining in Scientific Data....Pages 61-85
Learning to Set Up Numerical Optimizations of Engineering Designs....Pages 87-125
Automatic Classification and Creation of Classification Systems Using Methodologies of “Knowledge Discovery in Databases (KDD)”....Pages 127-143
Data Mining for Knowledge Acquisition in Engineering Design....Pages 145-160
A Data Mining-Based Engineering Design Support System: A Research Agenda....Pages 161-178
Data Mining for High Quality and Quick Response Manufacturing....Pages 179-205
Data Mining for Process and Quality Control in the Semiconductor Industry....Pages 207-234
Analyzing Maintenance Data Using Data Mining Methods....Pages 235-254
Methodology of Mining Massive Data Sets for Improving Manufacturing Quality/Efficiency....Pages 255-288
Intelligent Process Control System for Quality Improvement by Data Mining in the Process Industry....Pages 289-309
Data Mining by Attribute Decomposition with Semiconductor Manufacturing Case Study....Pages 311-336
Derivation of Decision Rules for the Evaluation of Product Performance Using Genetic Algorithms and Rough Set Theory....Pages 337-353
An Evaluation of Sampling Methods for Data Mining with Fuzzy C-Means....Pages 355-369
Colour Space Mining For Industrial Monitoring....Pages 371-400
Non-Traditional Applications of Data Mining....Pages 401-416
Fuzzy-Neural-Genetic Layered Multi-Agent Reactive Control of Robotic Soccer....Pages 417-442
Method-Specific Knowledge Compilation....Pages 443-463
A Study of Technical Challenges in Relocation of a Manufacturing Site....Pages 465-486
Using Imprecise Analogical Reasoning to Refine the Query Answers for Heterogeneous Multidatabase Systems in Virtual Enterprises....Pages 487-503
The Use of Process Capability Data in Design....Pages 505-518
Back Matter....Pages 519-524

✦ Subjects

Data Structures, Cryptology and Information Theory;Artificial Intelligence (incl. Robotics);Statistical Physics, Dynamical Systems and Complexity

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