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Condition-based fault tree analysis (CBFTA): A new method for improved fault tree analysis (FTA), reliability and safety calculations

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  • Shalev, Dan M.
  • Tiran, Joseph

Abstract

Condition-based maintenance methods have changed systems reliability in general and individual systems in particular. Yet, this change does not affect system reliability analysis. System fault tree analysis (FTA) is performed during the design phase. It uses components failure rates derived from available sources as handbooks, etc. Condition-based fault tree analysis (CBFTA) starts with the known FTA. Condition monitoring (CM) methods applied to systems (e.g. vibration analysis, oil analysis, electric current analysis, bearing CM, electric motor CM, and so forth) are used to determine updated failure rate values of sensitive components. The CBFTA method accepts updated failure rates and applies them to the FTA. The CBFTA recalculates periodically the top event (TE) failure rate (λTE) thus determining the probability of system failure and the probability of successful system operation—i.e. the system's reliability.

Suggested Citation

  • Shalev, Dan M. & Tiran, Joseph, 2007. "Condition-based fault tree analysis (CBFTA): A new method for improved fault tree analysis (FTA), reliability and safety calculations," Reliability Engineering and System Safety, Elsevier, vol. 92(9), pages 1231-1241.
    • Handle: RePEc:eee:reensy:v:92:y:2007:i:9:p:1231-1241
    DOI: 10.1016/j.ress.2006.05.015
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    Citations

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    Cited by:

    1. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2012. "Dynamic risk analysis using bow-tie approach," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 36-44.
    2. Luo, Pengcheng & Hu, Yang, 2013. "System risk evolution analysis and risk critical event identification based on event sequence diagram," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 36-44.
    3. Jibiao Zhou & Xinhua Mao & Yiting Wang & Minjie Zhang & Sheng Dong, 2019. "Risk Assessment in Urban Large-Scale Public Spaces Using Dempster-Shafer Theory: An Empirical Study in Ningbo, China," IJERPH, MDPI, vol. 16(16), pages 1-28, August.
    4. Liu, Aihua & Chen, Ke & Huang, Xiaofei & Li, Didi & Zhang, Xiaochun, 2021. "Dynamic risk assessment model of buried gas pipelines based on system dynamics," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    5. Zhang, Yimin & Shortle, John & Sherry, Lance, 2015. "Methodology for collision risk assessment of an airspace flow corridor concept," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 444-455.
    6. Babaleye, Ahmed O. & Kurt, Rafet Emek & Khan, Faisal, 2019. "Safety analysis of plugging and abandonment of oil and gas wells in uncertain conditions with limited data," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 133-141.
    7. He, Rui & Zhu, Jingyu & Chen, Guoming & Tian, Zhigang, 2022. "A real-time probabilistic risk assessment method for the petrochemical industry based on data monitoring," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    8. Yılmaz, Emre & German, Brian J. & Pritchett, Amy R., 2023. "Optimizing resource allocations to improve system reliability via the propagation of statistical moments through fault trees," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    9. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    10. Darwish, Molham & Almouahed, Shaban & de Lamotte, Florent, 2017. "The integration of expert-defined importance factors to enrich Bayesian Fault Tree Analysis," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 81-90.
    11. Kim, Jaehoon & Jeong, Hyun- Yong, 2013. "Evaluation of the adequacy of maintenance tasks using the failure consequences of railroad vehicles," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 30-39.
    12. Xing, Jinduo & Zeng, Zhiguo & Zio, Enrico, 2019. "A framework for dynamic risk assessment with condition monitoring data and inspection data," Reliability Engineering and System Safety, Elsevier, vol. 191(C).

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