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Design of parts for cellular manufacturing using neural network-based approach

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Abstract

A neural network approach is applied to the problem of integrating design and manufacturing engineering. The self organising map (SOM) neural network recognizes products and parts which are modeled as boundary representation (B-rep) solids using a modified face complexity code scheme adopted, and forms the necessary feature families. Based on the part features, machines, tools and fixtures are selected. These information are then fed into a four layer feed-forward neural network that provides a designer with the desired features that meet the current manufacturing constraints for design of a new product or part. The proposed methodology does not involve training of the neural networks used and is seen to be a significant potential for application in concurrent engineering where design and manufacturing are integrated.

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Authors and Affiliations

  1. Department of Industrial Engineering, National University of Science and Technology, PO Box AC, 939, ASCOT, Bulawayo, Zimbabwe

    Godfrey C. Onwubolu

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  1. Godfrey C. Onwubolu
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Onwubolu, G.C. Design of parts for cellular manufacturing using neural network-based approach. Journal of Intelligent Manufacturing 10, 251–265 (1999). https://doi.org/10.1023/A:1008947824050

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