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    Uncertainty-aware dynamic reliability analysis framework for complex systems

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    Kabir_IEEE_Access_Final.pdf (9.011Mb)
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    Publication date
    2018-06-07
    Author
    Kabir, Sohag
    Yazdi, M.
    Aizpurua, J.I.
    Papadopoulos, Y.
    Keyword
    Dynamic systems
    Fault tree analysis
    Fuzzy set theory
    Petri nets
    Reliability analysis
    Rights
    This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Critical technological systems exhibit complex dynamic characteristics such as time-dependent behavior, functional dependencies among events, sequencing and priority of causes that may alter the effects of failure. Dynamic fault trees (DFTs) have been used in the past to model the failure logic of such systems, but the quantitative analysis of DFTs has assumed the existence of precise failure data and statistical independence among events, which are unrealistic assumptions. In this paper, we propose an improved approach to reliability analysis of dynamic systems, allowing for uncertain failure data and statistical and stochastic dependencies among events. In the proposed framework, DFTs are used for dynamic failure modeling. Quantitative evaluation of DFTs is performed by converting them into generalized stochastic Petri nets. When failure data are unavailable, expert judgment and fuzzy set theory are used to obtain reasonable estimates. The approach is demonstrated on a simplified model of a cardiac assist system.
    URI
    http://hdl.handle.net/10454/17425
    Version
    Published version
    Citation
    Kabir S, Yazdi M, Aizpurua JI et al (2018) Uncertainty-aware dynamic reliability analysis framework for complex systems. IEEE Access. 6: 29499-29515.
    Link to publisher’s version
    https://doi.org/10.1109/ACCESS.2018.2843166
    Type
    Article
    Collections
    Engineering and Informatics Publications

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