Joint optimization of spare parts inventory and maintenance policies using genetic algorithms |
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Authors: | M Ali Ilgin Semra Tunali |
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Affiliation: | (1) Department of Industrial Engineering, Dokuz Eylul University, 35100, Bornova, Izmir, Turkey |
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Abstract: | In general, the maintenance and spare parts inventory policies are treated either separately or sequentially in industry.
However, since the stock level of spare parts is often dependent on the maintenance policies, it is a better practice to deal
with these problems simultaneously. In this study, a simulation optimization approach using genetic algorithms (GAs) has been
proposed for the joint optimization of preventive maintenance (PM) and spare provisioning policies of a manufacturing system
operating in the automotive sector. A factorial experiment was carried out to identify the best values for the GA parameters,
including the probabilities of crossover and mutation, the population size, and the number of generations. The computational
experiments showed that the parameter settings given by the proposed approach achieves a significant cost reduction while
increasing the throughput of the manufacturing system. |
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Keywords: | Genetic algorithms Inventory Maintenance Simulation Spare parts |
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