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A joint optimal policy of block preventive replacement and spare part inventory

Author

Listed:
  • Ruifeng Yang

    (Mechanical Engineering College)

  • Jianshe Kang

    (Mechanical Engineering College)

Abstract

Maintenance and spare part should be considered jointly as they are related activities and maintenance generates the demand of spare parts. In this study, a joint optimization policy of block replacement and spare parts inventory for multi-components system is proposed by simulation optimization approach using Monte Carlo simulation. Through analyzing the process of maintenance replacement and spare inventory within replacement interval T, the total expected cost can be derived. The expected cost per unit time is the objective function to optimize the block replacement interval T and maximum inventory level S. Monte Carlo method is used to simulate the operate process and simulation algorithm is presented to derive the approximate optimal solution. Finally, a numerical example is presented to illustrate the effectiveness of the proposed model. Sensitivity analysis and the effect of relevant parameters on the optimal decisions are discussed.

Suggested Citation

  • Ruifeng Yang & Jianshe Kang, 2017. "A joint optimal policy of block preventive replacement and spare part inventory," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(4), pages 740-746, December.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:4:d:10.1007_s13198-017-0593-9
    DOI: 10.1007/s13198-017-0593-9
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    References listed on IDEAS

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    1. Charles H. Falkner, 1970. "Jointly Optimal Deterministic Inventory and Replacement Policies," Management Science, INFORMS, vol. 16(9), pages 622-635, May.
    2. Chelbi, Anis & Ait-Kadi, Daoud, 2001. "Spare provisioning strategy for preventively replaced systems subjected to random failure," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 183-189, December.
    3. Sheu, Shey-Huei & Chien, Yu-Hung, 2004. "Optimal age-replacement policy of a system subject to shocks with random lead-time," European Journal of Operational Research, Elsevier, vol. 159(1), pages 132-144, November.
    4. Zohrul Kabir, A. B. M. & Al-Olayan, Ahmed S., 1996. "A stocking policy for spare part provisioning under age based preventive replacement," European Journal of Operational Research, Elsevier, vol. 90(1), pages 171-181, April.
    5. A.N. Das & S.P. Sarmah, 2010. "Preventive replacement models: an overview and their application in process industries," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 4(3), pages 280-307.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Zhou, Xiaojun & Shi, Kailong, 2019. "Capacity failure rate based opportunistic maintenance modeling for series-parallel multi-station manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 46-53.
    2. Zhu, Mixin & Zhou, Xiaojun, 2022. "Hypergraph-based joint optimization of spare part provision and maintenance scheduling for serial-parallel multi-station manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    3. Rasool Motahari & Yasser Saeidi Sough & Hamed Aboutorab & Morteza Saberi, 2021. "Joint optimization of maintenance and inventory policies for multi-unit systems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 587-607, June.
    4. Ali Salmasnia & Sadegh Noori & Hadi Mokhtari, 2019. "A redundancy allocation problem by using utility function method and ant colony optimization: tradeoff between availability and total cost," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(3), pages 416-428, June.

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