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A review of applications of fuzzy sets to safety and reliability engineering

Kabir, Sohag; Papadopoulos, Yiannis

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Abstract

Safety and reliability are rigorously assessed during the design of dependable systems. Probabilistic risk assessment (PRA) processes are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). In conventional PRA, failure data about components is required for the purposes of quantitative analysis. In practice, it is not always possible to fully obtain this data due to unavailability of primary observations and consequent scarcity of statistical data about the failure of components. To handle such situations, fuzzy set theory has been successfully used in novel PRA approaches for safety and reliability evaluation under conditions of uncertainty. This paper presents a review of fuzzy set theory based methodologies applied to safety and reliability engineering, which include fuzzy FTA, fuzzy FMEA, fuzzy ETA, fuzzy Bayesian networks, fuzzy Markov chains, and fuzzy Petri nets. Firstly, we describe relevant fundamentals of fuzzy set theory and then we review applications of fuzzy set theory to system safety and reliability analysis. The review shows the context in which each technique may be more appropriate and highlights the overall potential usefulness of fuzzy set theory in addressing uncertainty in safety and reliability engineering.

Journal Article Type Article
Publication Date Sep 1, 2018
Journal International Journal of Approximate Reasoning
Print ISSN 0888-613X
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 100
Pages 29-55
Series ISSN 0888-613X
DOI https://doi.org/10.1016/j.ijar.2018.05.005
Keywords Safety; Reliability; Dependability; Fuzzy Set Theory; Fault tree analysis; FMEA; Event tree analysis; Bayesian network; Markov chain; Petri Net; Uncertainty; Probabilistic Risk Assessment
Publisher URL https://www.sciencedirect.com/science/article/pii/S0888613X18301671
Copyright Statement © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

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Copyright Statement
© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/



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