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Risk importance measures in the dynamic flowgraph methodology

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  • Tyrväinen, T.

Abstract

This paper presents new risk importance measures applicable to a dynamic reliability analysis approach with multi-state components. Dynamic reliability analysis methods are needed because traditional methods, such as fault tree analysis, can describe system's dynamical behaviour only in limited manner. Dynamic flowgraph methodology (DFM) is an approach used for analysing systems with time dependencies and feedback loops. The aim of DFM is to identify root causes of a top event, usually representing the system's failure. Components of DFM models are analysed at discrete time points and they can have multiple states. Traditional risk importance measures developed for static and binary logic are not applicable to DFM as such. Some importance measures have previously been developed for DFM but their ability to describe how components contribute to the top event is fairly limited. The paper formulates dynamic risk importance measures that measure the importances of states of components and take the time-aspect of DFM into account in a logical way that supports the interpretation of results. Dynamic risk importance measures are developed as generalisations of the Fussell-Vesely importance and the risk increase factor.

Suggested Citation

  • Tyrväinen, T., 2013. "Risk importance measures in the dynamic flowgraph methodology," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 35-50.
    • Handle: RePEc:eee:reensy:v:118:y:2013:i:c:p:35-50
    DOI: 10.1016/j.ress.2013.04.013
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    References listed on IDEAS

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    1. Huang, Chin-Yu & Chang, Yung-Ruei, 2007. "An improved decomposition scheme for assessing the reliability of embedded systems by using dynamic fault trees," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1403-1412.
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    5. Do Van, Phuc & Barros, Anne & Bérenguer, Christophe, 2008. "Reliability importance analysis of Markovian systems at steady state using perturbation analysis," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1605-1615.
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    8. Do Van, Phuc & Barros, Anne & Bérenguer, Christophe, 2010. "From differential to difference importance measures for Markov reliability models," European Journal of Operational Research, Elsevier, vol. 204(3), pages 513-521, August.
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    Cited by:

    1. Dui, Hongyan & Si, Shubin & Yam, Richard C.M., 2017. "A cost-based integrated importance measure of system components for preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 98-104.
    2. Dui, Hongyan & Si, Shubin & Wu, Shaomin & Yam, Richard C.M., 2017. "An importance measure for multistate systems with external factors," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 49-57.
    3. Tyrväinen, Tero, 2016. "Prime implicants in dynamic reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 146(C), pages 39-46.

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