Artificial neural network case study: The control of work-in-process inventory in a manufacturing line
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1997
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Abstract
The work-in-process in a middle-scale shoe factory is investigated. At the manufacturing center, there are five work departments composed of cutting, sewing, hand-leather working, assembling and quality control-packing. In these departments, there are work-in-process because of different processing time and insufficient number of labor-machines. Artificial neural network (ANN) with backpropagation is used for solving this work-in-process problem. The optimum number of labor-machines at work stations are obtained for work-in-process without hindering the production by considering processing times and flow at these work stations.