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.
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Produkt-Hinweis
Fadenheftung
Gewebe-Einband
Maße
Höhe: 218 mm
Breite: 163 mm
Dicke: 20 mm
Gewicht
ISBN-13
978-981-02-1281-0 (9789810212810)
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Schweitzer Klassifikation
Herausgeber*in
Keio Univ, Japan
Chinese Univ Of Hong Kong, Hong Kong
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.