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Intelligent Quality Systems /

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This study discusses Quality Systems employing techniques from the field of Artificial Intelligence (AI). It focuses upon expert systems and neural networks, two of the most popular AI techniques. Expert Systems encapsulate human expertise for solving complex problems. Neural Networks are able to le...

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Bibliographic Details
Main Author: Pham, D. T.
Corporate Author: SpringerLink (Online service)
Other Authors: Oztemel, Ercan
Format: eBook
Language:English
Published: London : Springer London, 1996.
Series:Advanced manufacturing.
Subjects:
Engineering.
Artificial intelligence.
Industrial engineering.
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary:This study discusses Quality Systems employing techniques from the field of Artificial Intelligence (AI). It focuses upon expert systems and neural networks, two of the most popular AI techniques. Expert Systems encapsulate human expertise for solving complex problems. Neural Networks are able to learn problem solving from examples. The authors illustrate applications of these techniques to the design and operation of effective quality systems. Readers with a background in quality engineering and manufacturing will be able to learn about the uses of expert systems and neural networks to achieve intelligent Statistical Process Control, monitor processes and detect incipient faults in them, design experiments and predict performance, inspect products and monitor and diagnose plants and processes. Readers with an AI background will find a wealth of ideas for practical problems on which to deploy and test their techniques.
Item Description:Electronic resource.
Physical Description:1 online resource (xii, 201 pages 92 illustrations)
Format:Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
Bibliography:Includes bibliographical references and indexes.
ISBN:9781447114987 (electronic bk.)
1447114981 (electronic bk.)
ISSN:1431-0155