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Reliability and Sensitivity Analysis Method for a Multistate System with Common Cause Failure

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  • Jinlei Qin
  • Zheng Li

Abstract

With the increasing complexity of industrial products and systems, some intermediate states, other than the traditional two states, are often encountered during reliability assessments. A system with more than two states is called a multistate system (MSS) which has already become a general phenomenon in the components and/or systems. Moreover, common cause failure (CCF) often plays a very important role in the assessment of system reliability. A method is proposed to assess the reliability and sensitivity of an MSS with CCF. Some components are not only in a failure state that can cause failure itself, but also in a state that can cause the failure of other components with a certain probability. The components that are affected by one type of CCF make up some sets which can overlap on some components. Using the technology of a universal generating function (UGF), the CCF of a component can be incorporated in the expression of its UGF. Consequently, indices of reliability can be calculated based on the UGF expression of an MSS. Sensitivity analysis can help engineers to judge which type of CCF should be eliminated first under various resource limitations. Examples illustrate and validate this method.

Suggested Citation

  • Jinlei Qin & Zheng Li, 2019. "Reliability and Sensitivity Analysis Method for a Multistate System with Common Cause Failure," Complexity, Hindawi, vol. 2019, pages 1-8, May.
    • Handle: RePEc:hin:complx:6535726
    DOI: 10.1155/2019/6535726
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    References listed on IDEAS

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    Cited by:

    1. Yuxiong Li & Xianzhen Huang & Xinong En & Pengfei Ding, 2019. "A New System Reliability Optimization Model Based on Swapping Existing Components," Complexity, Hindawi, vol. 2019, pages 1-14, November.
    2. Qin, Jinlei & Coolen, Frank P.A., 2022. "Survival signature for reliability evaluation of a multi-state system with multi-state components," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    3. Nguyen, H.D. & Gouno, E., 2020. "Bayesian inference for Common cause failure rate based on causal inference with missing data," Reliability Engineering and System Safety, Elsevier, vol. 197(C).

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