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An integrated model for maintenance policies and production scheduling based on immune–culture algorithm

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  • Xiaohui Chen
  • Lin Zhang
  • Ze Zhang

Abstract

The development of integrated modelling for maintenance policies of multi-component repairable system and production scheduling is challenging for two reasons. First, capturing dependency of this multi-component repairable system is difficult because different failure types associated with different components are under competing risks and their complicated relationships may lead to overall system dependency. Second, the integrated model is difficult to optimize because it is an NP-hard problem that exact optimization methods are intractable. For coping with these two difficulties, we propose a parametric statistical model using copula function to capture the overall system dependency. Under partially perfect maintenance policy at component-level, the likelihood functions for observed failures are derived and maximum likelihood method is used to estimate unknown parameters. Then relying on this parametric statistical model, the system hazard function is derived to depict the reliability-based imperfect preventive maintenance policy at system-level. Finally, to obtain the optimal solution(s) of the integrated model, we design an adaptive immune clone selection–culture algorithm, which is inspired from immune clone selection algorithm and culture algorithm. Results of the case study validate that our proposed maintenance policies and methodology have great advantages over the component-level or system-level maintenance policy and immune clone selection algorithm.

Suggested Citation

  • Xiaohui Chen & Lin Zhang & Ze Zhang, 2020. "An integrated model for maintenance policies and production scheduling based on immune–culture algorithm," Journal of Risk and Reliability, , vol. 234(5), pages 651-663, October.
    • Handle: RePEc:sae:risrel:v:234:y:2020:i:5:p:651-663
    DOI: 10.1177/1748006X20920048
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    References listed on IDEAS

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    1. Zhou, Taotao & Modarres, Mohammad & Droguett, Enrique López, 2019. "Multi-unit risk aggregation with consideration of uncertainty and bias in risk metrics," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 473-482.
    2. Zhou, Taotao & Modarres, Mohammad & Droguett, Enrique López, 2018. "An improved multi-unit nuclear plant seismic probabilistic risk assessment approach," Reliability Engineering and System Safety, Elsevier, vol. 171(C), pages 34-47.
    3. Zhou, Xiaojun & Xi, Lifeng & Lee, Jay, 2007. "Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation," Reliability Engineering and System Safety, Elsevier, vol. 92(4), pages 530-534.
    4. Nailong Zhang & Qingyu Yang, 2015. "Optimal maintenance planning for repairable multi-component systems subject to dependent competing risks," IISE Transactions, Taylor & Francis Journals, vol. 47(5), pages 521-532, May.
    5. Modarres, Mohammad & Zhou, Taotao & Massoud, Mahmoud, 2017. "Advances in multi-unit nuclear power plant probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 87-100.
    6. Patton, Andrew J, 2001. "Estimation of Copula Models for Time Series of Possibly Different Length," University of California at San Diego, Economics Working Paper Series qt3fc1c8hw, Department of Economics, UC San Diego.
    7. A. Khatab, 2018. "Maintenance optimization in failure-prone systems under imperfect preventive maintenance," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 707-717, March.
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    Cited by:

    1. Zhang, Lin & Chen, Xiaohui & Khatab, Abdelhakim & An, Youjun, 2022. "Optimizing imperfect preventive maintenance in multi-component repairable systems under s-dependent competing risks," Reliability Engineering and System Safety, Elsevier, vol. 219(C).

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