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Open AccessJournal ArticleDOI

An overview of fault tree analysis and its application in model based dependability analysis

Sohag Kabir
- 01 Jul 2017 - 
- Vol. 77, pp 114-135
TLDR
The standard fault tree with its limitations is reviewed and a number of prominent MBDA techniques where fault trees are used as a means for system dependability analysis are reviewed and an insight into their working mechanism, applicability, strengths and challenges are provided.
Abstract
I provide an overview of the Fault Tree Analysis method.I review different extensions of fault trees.A number of model-based dependability analysis approaches are reviewed.I outline the future outlook for model-based dependability analysis. 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.

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Citations
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A Comprehensive Technological Survey on the Dependable Self-Management CPS: From Self-Adaptive Architecture to Self-Management Strategies

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Fault tree analysis improvements: A bibliometric analysis and literature review

TL;DR: Wang et al. as discussed by the authors carried out a systematic literature review of the state-of-the-art theoretical and empirical findings concerning FTA improvement from 2011 to 2021 using the Scopus database collection.
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SHyFTOO, an object-oriented Monte Carlo simulation library for the modeling of Stochastic Hybrid Fault Tree Automaton

TL;DR: A Stochastic Hybrid Fault Tree Automaton (SHyFTA) based simulation algorithm that allows the accurate dependability analysis of repairable multi-state systems and can open the way to further investigations that address the interactions between the failure behavior and the functional operation of a system and their combined effect on system dependability.
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Dynamic reliability assessment of flare systems by combining fault tree analysis and Bayesian networks

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Improving the analysis of dependable systems by mapping fault trees into Bayesian networks

TL;DR: It is shown that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former, i.e. reliability of the Top Event or of any sub-system, criticality of components, etc.
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Q1. What are the contributions mentioned in the paper "An overview of fault tree analysis and its application in model based dependability analysis" ?

Firstly, this paper reviews the standard fault tree with its limitations. 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. 

Therefore, future research associated with these approaches are likely to concern with the improvement of the power and time complexity of the tools and techniques in the context of large and complex system models. This has open new avenues for further research to develop expert systems by combining MBDA approaches with other soft computing approaches for the assurance of dependability of such open systems. One possible avenue worthy of further research is the improvement of the MBDA approaches to perform real time analysis of systems—though it will complicate the analysis process and affect the scalability of the approaches. Future trends are likely to leading to more robust integrations between different existing MBDA approaches so that different strengths ( e. g. dependability analysis and model checking capability ) of the existing approaches can be utilised in a complementary manner. 

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