An overview of fault tree analysis and its application in model based dependability analysis
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Publication date
2017-072017-07
Author
Kabir, SohagKeyword
Dynamic fault treesExpert systems
Fault tree analysis
Model based dependability analysis
Reliability
Risk analysis
Safety analysis
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© 2017 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
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Fault Tree Analysis (FTA) is a well-established and well-understood technique, widely used for dependability evaluation of a wide range of systems. Although many extensions of fault trees have been proposed, they suffer from a variety of shortcomings. In particular, even where software tool support exists, these analyses require a lot of manual effort. Over the past two decades, research has focused on simplifying dependability analysis by looking at how we can synthesise dependability information from system models automatically. This has led to the field of model-based dependability analysis (MBDA). Different tools and techniques have been developed as part of MBDA to automate the generation of dependability analysis artefacts such as fault trees. Firstly, this paper reviews the standard fault tree with its limitations. Secondly, different extensions of standard fault trees are reviewed. Thirdly, this paper reviews a number of prominent MBDA techniques where fault trees are used as a means for system dependability analysis and provides an insight into their working mechanism, applicability, strengths and challenges. Finally, the future outlook for MBDA is outlined, which includes the prospect of developing expert and intelligent systems for dependability analysis of complex open systems under the conditions of uncertainty.Version
Accepted manuscriptCitation
Kabir S (2017) An overview of fault tree analysis and its application in model based dependability analysis. Expert Systems with Applications. 77: 114-135.Link to Version of Record
https://doi.org/10.1016/j.eswa.2017.01.058Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1016/j.eswa.2017.01.058
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