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Journal of Applied Sciences

Year: 2011 | Volume: 11 | Issue: 15 | Page No.: 2837-2842
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Authors

Adnan Mukattash

Sahar Idwan

Moh`d Sami Ashhab

Murad Samhouri

Izzeddin A. Matar

Keywords

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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