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    Uncertainty handling in fault tree based risk assessment: State of the art and future perspectives

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    Publication date
    2019-11
    Author
    Mohammad, Y.
    Kabir, Sohag
    Martin, W.
    Keyword
    Bayesian theorem
    Evidence theory
    Fault tree analysis
    Fuzzy set theory
    Process safety
    Risk assessment
    Uncertainty
    Rights
    © 2019 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Risk assessment methods have been widely used in various industries, and they play a significant role in improving the safety performance of systems. However, the outcomes of risk assessment approaches are subject to uncertainty and ambiguity due to the complexity and variability of system behaviour, scarcity of quantitative data about different system parameters, and human involvement in the analysis, operation, and decision-making processes. The implications for improving system safety are slowly being recognised; however, research on uncertainty handling during both qualitative and quantitative risk assessment procedures is a growing field. This paper presents a review of the state of the art in this field, focusing on uncertainty handling in fault tree analysis (FTA) based risk assessment. Theoretical contributions, aleatory uncertainty, epistemic uncertainty, and integration of both epistemic and aleatory uncertainty handling in the scientific and technical literature are carefully reviewed. The emphasis is on highlighting how assessors can handle uncertainty based on the available evidence as an input to FTA.
    URI
    http://hdl.handle.net/10454/17421
    Version
    Accepted manuscript
    Citation
    Mohammad Y, Kabir S and Martin W (2019) Uncertainty handling in fault tree based risk assessment: State of the art and future perspectives. Process Safety and Environmental Protection. 131: 89-104.
    Link to publisher’s version
    https://doi.org/10.1016/j.psep.2019.09.003
    Type
    Article
    Collections
    Engineering and Informatics Publications

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