Massive Computing

Methods and Applications

By: D. Braha (Editor)

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Hardcover | 31 October 2001

At a Glance

Hardcover
548 Pages

Dimensions(cm)
24.13 x 16.51 x 3.18

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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.

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

Massive Computing

Methods and Applications

At a Glance

Hardcover

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How to return your order

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