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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 review of applications of fuzzy sets to safety and reliability engineering

TL;DR: 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 is presented.
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Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability

TL;DR: A method incorporating fuzzy probability and Bayesian network (BN) into multi-state systems (MSSs) with CCFs is proposed and can improve the ability of BN on reliability evaluation of complex system with uncertainty issues.
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Fault Tree Analysis of floating offshore wind turbines

TL;DR: In this article, the authors used the Fault Tree Analysis (FTA) method for both qualitative and quantitative evaluation of semi-submersible floating offshore wind turbine failure characteristics, indicating that most of the failures are caused by several basic factors.
Journal ArticleDOI

Application of fuzzy fault tree analysis based on modified fuzzy AHP and fuzzy TOPSIS for fire and explosion in the process industry.

TL;DR: This study aimed at establishing fault tree analysis (FTA) using expert opinion to compute the probability of an event using Boolean algebra, and the effectiveness of the proposed approach is demonstrated with a real-life case study.
References
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Dissertation

Non coherent fault tree analysis

TL;DR: Extensions for seven of the most commonly used measures of importance have been proposed to enable accurate analysis of non-coherent systems and demonstrate the gains to be made in terms of efficiency and accuracy.
Book ChapterDOI

Quantification of Simultaneous-AND Gates in Temporal Fault Trees

TL;DR: This work extends the Simultaneous-AND gate to include a parameterized interval – referred to as pSAND – such that the output event occurs if the input events occur within a defined period of time.
Proceedings ArticleDOI

Towards model-driven safety analysis

TL;DR: SAML is a tool-independent modeling framework that allows for the construction of models with both non-deterministic and probabilistic behavior that makes it an ideal intermediate language for a model-driven safety analysis approach.
Book ChapterDOI

A method for constructing fault trees from AADL models

TL;DR: A whole method for constructing fault trees from AADL models by dynamically tracing the possible fault sources of the specified fault objective, store them into a proposed database structure, and then construct fault trees based on the extracted fault information in the database structure is proposed.
Journal ArticleDOI

System Dependability Modelling and Analysis Using AADL and HiP-HOPS

TL;DR: A model transformation technique is used to automate a translation between AADL and the dependability analysis tool HiP-HOPS by using model transformation techniques.
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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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