Abstract
A joint strategy, referred to as periodical condition-based repair-by-replacement and continuous reviewed (S,s) type spare provisioning policy, is presented for continuous deteriorating systems with a known number of identical repairable components. Maintenance consists of replacing all failed and/or deteriorated components, and then deteriorated components being repaired off-line. With assumptions of random repair time, random lead time for spare parts ordering and imperfect maintenance effect, a stochastic simulation model is developed to determine the jointly optimal strategy. The objective function of the model represents the average cost per component per unit time over an infinite time span, while inspection interval, preventive replacement threshold, spare part inventory levels and repair capacity are chosen as decision variables. The optimal result is obtained using integrating approach with discrete event simulation and genetic algorithm (GA). Simulation results indicate that there are trades-off among maintenance policy, spare parts inventory and repair capacity.
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Acknowledgments
The authors would like to thank the support of Shanxi Scholarship Council of China (No. 2013-089), the Key Science and Technology Program of Shanxi Province (No. 20130321006-01) and National Natural Science Foundation of China (No. 61403271).
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Zhang, Xh., Zeng, Jc. (2016). Joint Optimization of Condition-Based Repair-by-Replacement and Spare Parts Provisioning Policy with Random Maintenance Time and Lead Time. In: Qi, E., Shen, J., Dou, R. (eds) Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-180-2_34
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DOI: https://doi.org/10.2991/978-94-6239-180-2_34
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