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Author(s): Haq, A.N. | Venkumar, P. |
Year: 2005
Citation: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY Volume: 26 Issue: 7-8 Pages: 909-916
Abstract: The primary objective of group technology (GT) is to enhance the productivity in the batch manufacturing environment. The GT cell formation problem is solved using modified binary adaptive resonance theory networks known as ART1. The input to the modified ART1 is a machine-part incidence matrix comprised of the binary digits 0 and 1. And the outputs are the list of part families and the corresponding part list, machine cells and their corresponding list of machines, and the number of exceptional elements. This method is applied to the known benchmarked problems found in the literature and it is found to outperform other algorithms in terms of minimizing the number of the exceptional elements. The relative merits of using this method with respect to other known algorithms/heuristics in terms of computational speed and consistency are presented.
Topics:
Machine Learning,
Applications:
Industrial Control,
Models:
ART 1,
