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Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency

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  • Martorell, P.
  • Martón, I.
  • Sánchez, A.I.
  • Martorell, S.

Abstract

The reliability, availability and maintainability (RAM) modelling of safety equipment has long been a topic of major concern. Some RAM models have focused on explicitly addressing the effect of component degradation and surveillance and maintenance policies, searching for an optimum level of the safety component RAM by adjusting surveillance and maintenance related parameters. As regards the reliability contribution, these components normally have two main types of failure mode that contribute to the probability of failure on demand (PFD): (1) by demand-caused and (2) standby-related failures. The former is normally associated with a demand failure probability, which is affected by the degradation caused by demand-related stress. Surveillance testing therefore not only introduces a positive effect, but also an adverse one, which it compensates by performing maintenance activities to eliminate or reduce the accumulated degradation. This paper proposes a new model for the demand failure probability that explicitly addresses all aspects of the effect of demand-induced stress (mostly test-induced stress), maintenance effectiveness (PAS or PAR model) and test efficiency. A case study is included on an application to a typical motor-operated valve in a nuclear power plant.

Suggested Citation

  • Martorell, P. & Martón, I. & Sánchez, A.I. & Martorell, S., 2017. "Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 18-27.
    • Handle: RePEc:eee:reensy:v:168:y:2017:i:c:p:18-27
    DOI: 10.1016/j.ress.2017.05.044
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    References listed on IDEAS

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    Cited by:

    1. Lin, Zhixian & Tao, Longlong & Wang, Shaoxuan & Yong, Nuo & Xia, Dongqin & Wang, Jianye & Ge, Daochuan, 2024. "A subset simulation analysis framework for rapid reliability evaluation of series-parallel cold standby systems," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Chen, Ying & Wang, Ze & Li, YingYi & Kang, Rui & Mosleh, Ali, 2018. "Reliability analysis of a cold-standby system considering the development stages and accumulations of failure mechanisms," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 1-12.
    3. Thiago Lima de Barros & Rodrigo Sampaio Lopes, 2021. "Continuous improvement of imperfect maintenance actions in PAS and PAR models," Journal of Risk and Reliability, , vol. 235(5), pages 941-958, October.
    4. Srivastav, Himanshu & Barros, Anne & Lundteigen, Mary Ann, 2020. "Modelling framework for performance analysis of SIS subject to degradation due to proof tests," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    5. Martón, I. & Sánchez, A.I. & Carlos, S. & Mullor, R. & Martorell, S., 2023. "Prognosis of wear-out effect on of safety equipment reliability for nuclear power plants long-term safe operation," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    6. Wu, Shaomin & Do, Phuc, 2017. "Editorial," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 1-3.
    7. Zhang, Aibo & Srivastav, Himanshu & Barros, Anne & Liu, Yiliu, 2021. "Study of testing and maintenance strategies for redundant final elements in SIS with imperfect detection of degraded state," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    8. Martorell, S. & Martón, I. & Sánchez, A. & Carlos, S., 2020. "Harmonisation of surveillance requirements and maintenance in a context of ageing and obsolescence based on reliability, availability and risk information," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    9. Srivastav, Himanshu & Lundteigen, Mary Ann & Barros, Anne, 2021. "Introduction of degradation modeling in qualification of the novel subsea technology," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

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