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Reliability evaluation of non-repairable systems with failure mechanism trigger effect

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  • Fang, Jiayue
  • Kang, Rui
  • Chen, Ying

Abstract

Trigger effect indicates that some events occur because of the trigger of other events. This kind of effect often appears in the operation of products and leads to failure. Due to the randomness of trigger events, it is difficult to predict the reliability of a product that embraces triggering processes. In this paper, we develop a new reliability model for non-repairable systems with the trigger effect. The effect is divided into two types: degradation-degradation trigger effect and degradation-overstress trigger effect. To model this effect, the degradation process is described by the continuous or discrete stochastic process, while the overstress process is described by the homogeneous Poisson process. Furthermore, a method integrating Petri Net and Monte Carlo is proposed to evaluate the complex system reliability. To demonstrate the proposed model, a conductive slip ring in an electromechanical orientation device is introduced as a case, where the trigger effect of one trigger mechanism and three dependent basic mechanisms are considered. It is shown that the trigger time model and system modeling method can describe the trigger failure behaviors and evaluate the reliability of complex systems with the trigger effect.

Suggested Citation

  • Fang, Jiayue & Kang, Rui & Chen, Ying, 2021. "Reliability evaluation of non-repairable systems with failure mechanism trigger effect," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
  • Handle: RePEc:eee:reensy:v:210:y:2021:i:c:s0951832021000235
    DOI: 10.1016/j.ress.2021.107454
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    References listed on IDEAS

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    10. Zhao, Guilin & Xing, Liudong, 2020. "Reliability analysis of IoT systems with competitions from cascading probabilistic function dependence," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
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    Cited by:

    1. Wang, Xiaoyue & Ning, Ru & Zhao, Xian & Wu, Congshan, 2023. "Reliability assessments for two types of balanced systems with multi-state protective devices," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    2. Chen, Ying & Li, Shumin & Kang, Rui, 2021. "Epistemic uncertainty quantification via uncertainty theory in the reliability evaluation of a system with failure Trigger effect," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Chen, Ying & Wang, Yanfang & Li, Shumin & Kang, Rui, 2023. "Hybrid uncertainty quantification of dependent competing failure process with chance theory," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    4. Xia, Weifu & Wang, Yanhui & Hao, Yucheng & He, Zhichao & Yan, Kai & Zhao, Fan, 2024. "Reliability analysis for complex electromechanical multi-state systems utilizing universal generating function techniques," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    5. Sudeep Kumar & Ritu Gupta, 2023. "Reliability analysis of N-policy vacation based FTC system subject to standby switching failures," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(2), pages 53-80.
    6. Pol, Johannes C. & Kindermann, Paulina & van der Krogt, Mark G. & van Bergeijk, Vera M. & Remmerswaal, Guido & Kanning, Willem & Jonkman, Sebastiaan N. & Kok, Matthijs, 2023. "The effect of interactions between failure mechanisms on the reliability of flood defenses," Reliability Engineering and System Safety, Elsevier, vol. 231(C).

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