scispace - formally typeset
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.

read more

Citations
More filters
Journal ArticleDOI

Risk analysis of man overboard scenario in a small fishing vessel

TL;DR: The Objected-Oriented Bayesian Network (OOBN) application for risk assessment of the MOB scenario is presented, and the OOBN model is developed to probabilistically capture the key accident influencing factors in fragmented structures.
Journal ArticleDOI

Reliability block diagram (RBD) and fault tree analysis (FTA) approaches for estimation of system reliability and availability – a case study

TL;DR: This analysis provides the information on several aspects such as present working condition of the machines, occurrence of various potential failure modes, influence of failure modes on its performance and reliable life aspects etc.
Book ChapterDOI

Boosting Fault Tree Analysis by Formal Methods

TL;DR: This work discusses a mixture of formal method techniques resulting in a fully automated and scalable approach to analyze Dugan’s dynamic fault trees.
Journal ArticleDOI

Process Monitoring and Fault Diagnosis Based on aRegular Vine and Bayesian Network

TL;DR: This paper proposes a process monitoring and fault diagnosis method based on a regular vine (R vine) and Bayesian network and the R vine model structure is determined by searching for the maximum sum of grapes.
Journal ArticleDOI

An improved Bayesian network method for fault diagnosis

TL;DR: An improved Bayesian Network is proposed for fault diagnosis with its ability to describe the uncertain knowledge and causal reasoning and the effectiveness of the proposed method is validated on the Tennessee Eastman Process.
References
More filters
Book

Fuzzy sets

TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Book ChapterDOI

PRISM 4.0: verification of probabilistic real-time systems

TL;DR: A major new release of the PRISMprobabilistic model checker is described, adding, in particular, quantitative verification of (priced) probabilistic timed automata.
Book

Safeware: System Safety and Computers

TL;DR: This chapter discusses the role of humans in Automated Systems, the nature of risk, and elements of a Safeware Program, which aims to manage Safety and Security through design and implementation.
Book

Modelling with Generalized Stochastic Petri Nets

TL;DR: This book presents a unified theory of Generalized Stochastic Petri Nets together with a set of illustrative examples from different application fields to show how this methodology can be applied in a range of domains.
Journal ArticleDOI

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.
Related Papers (5)
Frequently Asked Questions (2)
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. 

Trending Questions (1)