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New methods to determine the importance measures of initiating and enabling events in fault tree analysis

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  • Contini, Sergio
  • Matuzas, Vaidas

Abstract

Components' importance measures play a very important role in system reliability analysis. They are used to identify the weakest parts of the system for design improvement, failure diagnosis and maintenance. This paper deals with the problem of determining the importance measures of basic events in case of unreliability analysis of binary coherent and non-coherent fault trees. This type of analysis is typical of catastrophic top events, characterised by unacceptable consequences. Since the unreliability of systems with repairable components cannot be exactly calculated via fault tree, the Expected Number of Failures – which is obtained by integrating the unconditional failure frequency – is considered as it represents a good upper bound. In these cases it is important to classify events as initiators or enablers since their roles in the system are different, their sequence of occurrence is different and consequently they must be treated differently. New equations based on system failure frequency are described in this paper for determining the exact importance measures of initiating and enabling events. Simple examples are provided to clarify the application of the proposed calculation methods. Compared with the exact methods available in the literature, those proposed in this paper are easier to apply by hand and are simpler to implement in a fault tree analyser.

Suggested Citation

  • Contini, Sergio & Matuzas, Vaidas, 2011. "New methods to determine the importance measures of initiating and enabling events in fault tree analysis," Reliability Engineering and System Safety, Elsevier, vol. 96(7), pages 775-784.
    • Handle: RePEc:eee:reensy:v:96:y:2011:i:7:p:775-784
    DOI: 10.1016/j.ress.2011.02.001
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    1. Barlow, Richard E. & Proschan, Frank, 1975. "Importance of system components and fault tree events," Stochastic Processes and their Applications, Elsevier, vol. 3(2), pages 153-173, April.
    2. Volkanovski, Andrija & ÄŒepin, Marko & Mavko, Borut, 2009. "Application of the fault tree analysis for assessment of power system reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1116-1127.
    3. Contini, S. & Cojazzi, G.G.M. & Renda, G., 2008. "On the use of non-coherent fault trees in safety and security studies," Reliability Engineering and System Safety, Elsevier, vol. 93(12), pages 1886-1895.
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    Citations

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    Cited by:

    1. Zhu, Xiaoyan & Boushaba, Mahmoud & Coit, David W. & Benyahia, Azzeddine, 2017. "Reliability and importance measures for m-consecutive-k, l-out-of-n system with non-homogeneous Markov-dependent components," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 1-9.
    2. Wu, Shaomin & Coolen, Frank P.A., 2013. "A cost-based importance measure for system components: An extension of the Birnbaum importance," European Journal of Operational Research, Elsevier, vol. 225(1), pages 189-195.
    3. Lyu, Dong & Si, Shubin, 2020. "Dynamic importance measure for the K-out-of-n: G system under repeated random load," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    4. 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).
    5. Zhu, Xiaoyan & Fu, Yuqiang & Yuan, Tao & Wu, Xinying, 2017. "Birnbaum importance based heuristics for multi-type component assignment problems," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 209-221.
    6. 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.
    7. Vaurio, Jussi K., 2016. "Importances of components and events in non-coherent systems and risk models," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 117-122.

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