Neural Networks In Design And Manufacturing
World Scientific Publishing Co Pte Ltd
Will be published approx. on 1. October 1993
Book
Hardback
316 pages
978-981-02-1281-0 (ISBN)
Description
Over the past few years, there has been a surge of research activities on artificial neural networks. Although the thrust originally came from computer scientists and electrical engineers, neural network research has recently attracted researchers in the fields of operations research, operations management and industrial engineering.Despite the huge volume of recent publications devoted to neural network research, there is no single monograph addressing the potential roles of artificial neural networks for design and manufacturing.The focus of this book is on the applications of neural network concepts and techniques to design and manufacturing. This book reviews the state-of-the-art of the research activities, highlights the recent advances in research and development, and discusses the potential directions and future trends along this stream of research.The potential readers of this book will include, but are not limited to, beginners, professionals and practitioners in industries who are applying neural networks to design and manufacturing.The topics include conceptual design, group technology, process planning and scheduling, process monitoring and others.
More details
Language
English
Place of publication
Singapore
Singapore
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 218 mm
Width: 163 mm
Thickness: 20 mm
Weight
558 gr
ISBN-13
978-981-02-1281-0 (9789810212810)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Content
The roles of artificial neural networks in design and manufacturing; a computer-based adaptive associative memory in support of design; epsodal associative memory approach for sequencing interactive feature in process planning; a self-organizing neural network for clustering part family; integrated, cost-based job-shop control using artificial neural networks; a neural network approach to lot sizing in closed job-shops; N-Queen and crossbar switch scheduling problems; multiprocessor scheduling by mean field algorithm; material handling based on neural networks; injection molding process control based on neural networks; hierachical neural network design for stochastic process change detection and multiple step predication; integration of sensors via neural networks for tool condition monitoring; a supervised learning approach to cutting tool wear monitoring.