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A common cause failure model for components under age-related degradation

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  • Zhou, Taotao
  • Droguett, Enrique López
  • Modarres, Mohammad

Abstract

This paper discusses component age-related degradation and failure initiated from a shared cause and coupling factor (or mechanism) and the likelihood of the resulting common cause failure (CCF). For these components a CCF model that includes the impacts of any maintenance-related renewal is proposed. Limitations and gaps in the state-of-the-art parametric CCF models for properly handling impacts of shared causes leading to accelerated degradation and aging have been discussed. The proposed approach characterizes the likelihood of CCF based on the conventional parametric CCF model, but unlike the parametric CCF models, time-dependent CCF parameters are estimated from the degradation states including any component rejuvenation achieved through preventive maintenance. Accelerated degradation tests of three identical centrifugal pumps under shared but harsh operating conditions generated several types of sensor monitoring data until failure. Correlation between the sensor monitoring data and observed aging and pump failure times were used to infer the degradation states of the pumps tested. The results concluded that undetected shared causes that could accelerate degradation and aging, for example due to poor maintenance, could significantly affect the CCF parametric model and CCF probability. This could potentially underestimate risk estimates as the undetected components degradation accumulates. The proposed parametric CCF model would be able to determine component-specific dynamic CCF probability, for condition monitored comments using sensor information relatable to degradation and aging.

Suggested Citation

  • Zhou, Taotao & Droguett, Enrique López & Modarres, Mohammad, 2020. "A common cause failure model for components under age-related degradation," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
  • Handle: RePEc:eee:reensy:v:195:y:2020:i:c:s0951832018303107
    DOI: 10.1016/j.ress.2019.106699
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    References listed on IDEAS

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    1. KanÄ ev, DuÅ¡ko & ÄŒepin, Marko, 2012. "A new method for explicit modelling of single failure event within different common cause failure groups," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 84-93.
    2. W Wang & A H Christer, 2000. "Towards a general condition based maintenance model for a stochastic dynamic system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(2), pages 145-155, February.
    3. 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.
    4. Enrique López Droguett & Ali Mosleh, 2008. "Bayesian Methodology for Model Uncertainty Using Model Performance Data," Risk Analysis, John Wiley & Sons, vol. 28(5), pages 1457-1476, October.
    5. Si, Xiao-Sheng & Wang, Wenbin & Hu, Chang-Hua & Zhou, Dong-Hua, 2011. "Remaining useful life estimation - A review on the statistical data driven approaches," European Journal of Operational Research, Elsevier, vol. 213(1), pages 1-14, August.
    6. O’Connor, Andrew & Mosleh, Ali, 2016. "A general cause based methodology for analysis of common cause and dependent failures in system risk and reliability assessments," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 341-350.
    7. Liu, Bin & Wu, Shaomin & Xie, Min & Kuo, Way, 2017. "A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost," European Journal of Operational Research, Elsevier, vol. 263(3), pages 879-887.
    8. 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.
    9. Vaurio, Jussi K., 2005. "Uncertainties and quantification of common cause failure rates and probabilities for system analyses," Reliability Engineering and System Safety, Elsevier, vol. 90(2), pages 186-195.
    10. Troffaes, Matthias C.M. & Walter, Gero & Kelly, Dana, 2014. "A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 13-21.
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    6. Jafary, Bentolhoda & Mele, Andrew & Fiondella, Lance, 2020. "Component-based system reliability subject to positive and negative correlation," Reliability Engineering and System Safety, Elsevier, vol. 202(C).

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