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Condition-based inspection policies for boiler heat exchangers

Author

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  • Truong-Ba, Huy
  • Cholette, Michael E.
  • Borghesani, Pietro
  • Ma, Lin
  • Kent, Geoff

Abstract

This study considers the inspection and maintenance of boiler heat exchangers, which are examples of a system composed of degrading, non-repairable components in series whose operation can be restored by removing failed components from service (albeit at a performance loss). For such systems, the increased failure risk due to component degradation may be managed through inspections and preventive removal of high failure risk components from service (again at a performance loss for remaining life of systems). In this study, a new joint inspection and preventive maintenance policy is developed, which uses condition information obtained at an inspection to optimize decisions regarding maintenance and future inspections to optimally balance the risks of system failure, future performance losses, and maintenance costs. The policy is optimized using the Markov Decision Process paradigm and is applied to a case study of a boiler heat exchanger operating in an Australian sugar factory. The results show that the proposed policy yields significant savings compared to benchmark policies that represent the factory's current practice.

Suggested Citation

  • Truong-Ba, Huy & Cholette, Michael E. & Borghesani, Pietro & Ma, Lin & Kent, Geoff, 2021. "Condition-based inspection policies for boiler heat exchangers," European Journal of Operational Research, Elsevier, vol. 291(1), pages 232-243.
    • Handle: RePEc:eee:ejores:v:291:y:2021:i:1:p:232-243
    DOI: 10.1016/j.ejor.2020.09.030
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    References listed on IDEAS

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    Cited by:

    1. Truong-Ba, Huy & Cholette, Michael E. & Rebello, Sinda & Kent, Geoff, 2024. "Joint planning of inspection, replacement, and component decommissioning for a series system with non-identically degrading components," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Li, Guolong & Li, Yanjun & Fang, Chengyue & Su, Jian & Wang, Haotong & Sun, Shengdi & Zhang, Guolei & Shi, Jianxin, 2023. "Research on fault diagnosis of supercharged boiler with limited data based on few-shot learning," Energy, Elsevier, vol. 281(C).

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