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Journal of Applied Sciences
  Year: 2011 | Volume: 11 | Issue: 15 | Page No.: 2837-2842
DOI: 10.3923/jas.2011.2837.2842
 
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Optimal Computerized Model for Designing Cellular Manufacturing Systems using Neural Network

Adnan Mukattash, Sahar Idwan, Moh`d Sami Ashhab, Murad Samhouri and Izzeddin A. Matar

Abstract:
In this study, a computerized model has been developed to obtain the optimal distribution of the machines on three cells based on Artificial Neural Network (ANN's). These networks rely on the historical input-output data to learn input output implicit mapping. They are trained using back propagation algorithm. Comparing the results with those in the literature, it has been proved that the artificial neural network is superior in finding all the possible optimal solution (s) since it gives the minimum sum of voids and/or exceptions for all the possible ways of forming three cells from n machines. Taking all the possible ways of forming the cells is of great advantage since; it will provide the designer with more flexibility. An important feature of the optimization model is that it finds the solution fast regardless the number of machines and parts. The distinct superiority of the proposed model is that, machine cells and part families are identified and done concurrently which will decrease the computational time. Results are verified with the aid of computer simulation.
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How to cite this article:

Adnan Mukattash, Sahar Idwan, Moh`d Sami Ashhab, Murad Samhouri and Izzeddin A. Matar, 2011. Optimal Computerized Model for Designing Cellular Manufacturing Systems using Neural Network. Journal of Applied Sciences, 11: 2837-2842.

DOI: 10.3923/jas.2011.2837.2842

URL: https://scialert.net/abstract/?doi=jas.2011.2837.2842

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