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Optimal replacement policy for a repairable system with deterioration based on a renewal-geometric process

Author

Listed:
  • Caiyun Niu

    (National University of Defense Technology)

  • Xiaolin Liang

    (Changsha University of Science and Technology)

  • Bingfeng Ge

    (National University of Defense Technology)

  • Xue Tian

    (Changsha University of Science and Technology)

  • Yingwu Chen

    (National University of Defense Technology)

Abstract

The optimal replacement policy is proposed for a new maintenance model of a repairable deteriorating system to minimize the average cost rate throughout the system life cycle. It is assumed that the system undergoes deterioration with an increasing trend of deterioration probability after each repair. More specifically, a novel maintenance model is first presented based on a new defined renewal-geometric process, which splits the operation process into an early renewal process and a late geometric process to characterize such a special deterioration delay. Then, the average cost rate for the new model is formulated according to the renewal-reward theorem. Next, a theorem is presented to derive the theoretical relationships of optimal replacement policies for the geometric-process maintenance model and the new proposed model, respectively. Finally, numerical examples suggest that the optimum values can be determined to minimize the average cost rates.

Suggested Citation

  • Caiyun Niu & Xiaolin Liang & Bingfeng Ge & Xue Tian & Yingwu Chen, 2016. "Optimal replacement policy for a repairable system with deterioration based on a renewal-geometric process," Annals of Operations Research, Springer, vol. 244(1), pages 49-66, September.
    • Handle: RePEc:spr:annopr:v:244:y:2016:i:1:d:10.1007_s10479-016-2133-4
    DOI: 10.1007/s10479-016-2133-4
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    References listed on IDEAS

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    1. Shey-Huei Sheu & Chin-Chih Chang & Yu-Hung Chien, 2011. "Optimal age-replacement time with minimal repair based on cumulative repair-cost limit for a system subject to shocks," Annals of Operations Research, Springer, vol. 186(1), pages 317-329, June.
    2. Yu-Hung Chien & Chin-Chih Chang & Shey-Huei Sheu, 2010. "Optimal age-replacement model with age-dependent type of failure and random lead time based on a cumulative repair-cost limit policy," Annals of Operations Research, Springer, vol. 181(1), pages 723-744, December.
    3. Ruey Yeh & Wen Chang & Hui-Chiung Lo, 2010. "Optimal threshold values of age and two-phase maintenance policy for leased equipments using age reduction method," Annals of Operations Research, Springer, vol. 181(1), pages 171-183, December.
    4. Richard Barlow & Larry Hunter, 1960. "Optimum Preventive Maintenance Policies," Operations Research, INFORMS, vol. 8(1), pages 90-100, February.
    5. Reza Ahmadi, 2014. "Optimal maintenance scheduling for a complex manufacturing system subject to deterioration," Annals of Operations Research, Springer, vol. 217(1), pages 1-29, June.
    6. Tang, Ya-yong & Lam, Yeh, 2006. "A [delta]-shock maintenance model for a deteriorating system," European Journal of Operational Research, Elsevier, vol. 168(2), pages 541-556, January.
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    Cited by:

    1. Nooshin Salari & Viliam Makis, 2020. "Joint maintenance and just-in-time spare parts provisioning policy for a multi-unit production system," Annals of Operations Research, Springer, vol. 287(1), pages 351-377, April.
    2. Yonit Barron, 2018. "Group maintenance policies for an R-out-of-N system with phase-type distribution," Annals of Operations Research, Springer, vol. 261(1), pages 79-105, February.
    3. Caiyun Niu & Jiang Jiang & Bingfeng Ge & Yingwu Chen, 2022. "Preventive maintenance model based on the renewal-geometric process," Journal of Risk and Reliability, , vol. 236(2), pages 348-356, April.

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