A Neural Network/Expert System Approach for Design Improvement of Products Manufactured by EDM-Reference-Cited by-同舟云学术

A Neural Network/Expert System Approach for Design Improvement of Products Manufactured by EDM

Published:1999-11-01 Issue:4 Volume:121 Page:733-738
ISSN:1087-1357
Container-title:Journal of Manufacturing Science and Engineering
language:en
Short-container-title:

Author:

Katz Z.¹,Naude J.¹

Affiliation:

1. Rand Afrikaans University, Johannesburg, South Africa

Abstract

The stochastic nature of the electro discharge machining (EDM) process does not allow for a precise prediction of its effect on the machined features. However, there is a direct interrelation between feature design and the process results. The objective of this work is to suggest a neural network based system to facilitate and optimize the design process of products to be machined by EDM. A comprehensive analysis by a neural network and expert system is presented. Aspects of features coding and relations with the process parameters are discussed. Experimental results confirm design improvements and a practical system is described.

Publisher

ASME International

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering

Link

http://asmedigitalcollection.asme.org/manufacturingscience/article-pdf/121/4/733/5633718/733_1.pdf

Reference10 articles.

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2. Erden, A., 1982, “Role of Dielectric Flushing on Electrical Discharge Machining Performance,” Middle East Technical University Mechanical Engineering Department, Ankara, Turkey, Proc. of the 22nd Int MTDR Conf., pp. 283–289.

3. Huang, S. H., and Zhang, H. C., 1994, “Artificial Neural Networks in Manufacturing: Concepts, Applications, and Perspectives,” IEEE Trans. on Components, Packaging and Manufacturing Technology-Part A, Vol. 17, No. 2.

4. Indurkhya G. , and RajurkarK. P., 1992, “Artificial Neural Network Approach in Modelling of EDM Process,” Intelligent Engineering Systems through Artificial Neural Networks, Vol. 2, pp. 845–850.

5. Indurkhya, G., 1992, Artificial Neural Network Approach for Modelling of EDM and WEDM Processes, M.S. Thesis, University of Nebraska-Lincoln.

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