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Control-limit preventive maintenance policies for components subject to imperfect preventive maintenance and variable operational conditions

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  • You, Ming-Yi
  • Li, Hongguang
  • Meng, Guang

Abstract

This paper develops two component-level control-limit preventive maintenance (PM) policies for systems subject to the joint effect of partial recovery PM acts (imperfect PM acts) and variable operational conditions, and investigates the properties of the proposed policies. The extended proportional hazards model (EPHM) is used to model the system failure likelihood influenced by both factors. Several numerical experiments are conducted for policy property analysis, using real lifetime and operational condition data and typical characterization of imperfect PM acts and maintenance durations. The experimental results demonstrate the necessity of considering both factors when they do exist, characterize the joint effect of the two factors on the performance of an optimized PM policy, and explore the influence of the loading sequence of time-varying operational conditions on the performance of an optimized PM policy. The proposed policies extend the applicability of PM optimization techniques.

Suggested Citation

  • You, Ming-Yi & Li, Hongguang & Meng, Guang, 2011. "Control-limit preventive maintenance policies for components subject to imperfect preventive maintenance and variable operational conditions," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 590-598.
    • Handle: RePEc:eee:reensy:v:96:y:2011:i:5:p:590-598
    DOI: 10.1016/j.ress.2010.12.015
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    References listed on IDEAS

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    Cited by:

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    2. Bensmain, Yassir & Dahane, Mohammed & Bennekrouf, Mohammed & Sari, Zaki, 2019. "Preventive remanufacturing planning of production equipment under operational and imperfect maintenance constraints: A hybrid genetic algorithm based approach," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 546-566.
    3. Coria, V.H. & Maximov, S. & Rivas-Dávalos, F. & Melchor, C.L. & Guardado, J.L., 2015. "Analytical method for optimization of maintenance policy based on available system failure data," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 55-63.
    4. Nishit Kumar Srivastava & Sandeep Mondal, 2016. "Development of Predictive Maintenance Model for N-Component Repairable System Using NHPP Models and System Availability Concept," Global Business Review, International Management Institute, vol. 17(1), pages 105-115, February.
    5. M. López-Campos & F. Kristjanpoller & P. Viveros & R. Pascual, 2018. "Reliability Assessment Methodology for Massive Manufacturing Using Multi-Function Equipment," Complexity, Hindawi, vol. 2018, pages 1-8, February.
    6. Jiawen Hu & Zuhua Jiang & Hong Wang, 2017. "Joint Optimization of Production Plan and Preventive Maintenance Schedule by Stackelberg Game," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(04), pages 1-28, August.
    7. Mengyao Gu & Youling Chen, 2019. "Two improvements of similarity-based residual life prediction methods," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 303-315, January.
    8. 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).
    9. Lei Zhang & Yifan Zhou & Chuanhui Huang, 2017. "An approximate hybrid approach to maintenance optimisation for a system with multistate components," 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(1), pages 189-196, March.
    10. Chien, Yu-Hung & Sheu, Shey-Huei & Zhang, Zhe George, 2012. "Optimal maintenance policy for a system subject to damage in a discrete time process," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 1-10.
    11. Jiawen Hu & Zuhua Jiang & Hong Wang, 2016. "Preventive maintenance for a single-machine system under variable operational conditions," Journal of Risk and Reliability, , vol. 230(4), pages 391-404, August.
    12. Braglia, Marcello & Carmignani, Gionata & Frosolini, Marco & Zammori, Francesco, 2012. "Data classification and MTBF prediction with a multivariate analysis approach," Reliability Engineering and System Safety, Elsevier, vol. 97(1), pages 27-35.
    13. Hu, Jiawen & Jiang, Zuhua & Liao, Haitao, 2017. "Preventive maintenance of a single machine system working under piecewise constant operating condition," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 105-115.
    14. Gössinger, Ralf & Helmke, Hanna & Kaluzny, Michael, 2017. "Condition-based release of maintenance jobs in a decentralised production-maintenance system – An analysis of alternative stochastic approaches," International Journal of Production Economics, Elsevier, vol. 193(C), pages 528-537.
    15. Dao, Cuong D. & Zuo, Ming J., 2017. "Optimal selective maintenance for multi-state systems in variable loading conditions," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 171-180.
    16. Zheng, Rui & Wang, Jingjing & Zhang, Yingzhi, 2023. "A hybrid repair-replacement policy in the proportional hazards model," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1011-1021.

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