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Study of neural network techniques for computer integrated manufacturing

Yong Yue (Faculty of Creative Arts and Technologies, University of Luton, Luton UK)
Lian Ding (Faculty of Creative Arts and Technologies, University of Luton, Luton UK)
Kemal Ahmet (Faculty of Creative Arts and Technologies, University of Luton, Luton UK)
John Painter (Faculty of Creative Arts and Technologies, University of Luton, Luton UK)
Mick Walters (Faculty of Creative Arts and Technologies, University of Luton, Luton UK)

Engineering Computations

ISSN: 0264-4401

Article publication date: 1 March 2002

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Abstract

Computer aided process planning (CAPP) is an effective way to integrate computer aided design and manufacturing (CAD/CAM). There are two key issues with the integration: design input in a feature‐based model and acquisition and representation of process knowledge especially empirical knowledge. This paper presents a state of the art review of research in computer integrated manufacturing using neural network techniques. Neural network‐based methods can eliminate some drawbacks of the conventional approaches, and therefore have attracted research attention particularly in recent years. The four main issues related to the neural network‐based techniques, namely the topology of the neural network, input representation, the training method and the output format are discussed with the current systems. The outcomes of research using neural network techniques are studied, and the limitations and future work are outlined.

Keywords

Citation

Yue, Y., Ding, L., Ahmet, K., Painter, J. and Walters, M. (2002), "Study of neural network techniques for computer integrated manufacturing", Engineering Computations, Vol. 19 No. 2, pp. 136-157. https://doi.org/10.1108/02644400210419021

Publisher

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MCB UP Ltd

Copyright © 2002, MCB UP Limited

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