Intelligent Modeling, Diagnosis And Control Of Manufacturing Processes
Will be published approx. on 1. August 1992
Book
Hardback
272 pages
978-981-02-0817-2 (ISBN)
Description
This volume demonstrates that the key to the modeling, diagnosis and control of the next generation manufacturing processes is to integrate knowledge-based systems with traditional techniques. An up-to-date study is given here of this relatively recent development.The book is for those working primarily with traditional techniques and those working in the knowledge-based systems field. Both sets of readers will find it to be a source of many specific ideas about the integration of knowledge-based systems with traditional techniques, and carrying a wealth of useful references.
Reviews / Votes
"This book can be taken as an introduction to the people who may not be familiar with these issues. It also provides some promotion to further research activities in this area." Pixin Zhang European Journal of Mechanics, 1994More details
Series
Language
English
Place of publication
Singapore
Singapore
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
ISBN-13
978-981-02-0817-2 (9789810208172)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Content
Part 1 Knowledge-based statistical approach: chronological equipment diagnosis using evidence integration, N. Chang and C. Spanos; process control system for VLSI fabrication, E. Sachs et al. Part 2 Model-based approach: model-based plant diagnosis and control expert system, J. Suzuki et al; knowledge representation for multiple fault resolution and corrective action planning in chemical diagnosis, J. McDowell and J. Davies. Part 3 Machine learning and neural network approach: intelligent diagnosis systems for manufacturing using abductive technology, G. Mongermory et al; a connectionist approach to diagnostic problem solving, Y. Peng and J. Reggia; and others.