Componentwise decomposition for an efficient reliability computation of systems with repairable components

Balakrishnan, Meera; Trivedi, Kishor S.

doi:10.1109/ftcs.1995.466972

Cited by 9 publications

(7 citation statements)

References 7 publications

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“…For systems where each component can be individually and simultaneously repaired at a constant rate, Balakrishnan and Trivedi [172] proposed to convert the model into a Markov Chain, although this method uses an approximation to reduce computational requirements.…”

Section: Repairable Fault Treesmentioning

confidence: 99%

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Ruijters

Stoelinga

2015

Computer Science Review

586

368

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Reliability Risk analysis Dynamic Fault Trees Graphical models Dependability evaluation A B S T R A C T Fault tree analysis (FTA) is a very prominent method to analyze the risks related to safety and economically critical assets, like power plants, airplanes, data centers and web shops. FTA methods comprise of a wide variety of modeling and analysis techniques, supported by a wide range of software tools. This paper surveys over 150 papers on fault tree analysis, providing an in-depth overview of the state-of-the-art in FTA. Concretely, we review standard fault trees, as well as extensions such as dynamic FT, repairable FT, and extended FT. For these models, we review both qualitative analysis methods, like cut sets and common cause failures, and quantitative techniques, including a wide variety of stochastic methods to compute failure probabilities. Numerous examples illustrate the various approaches, and tables present a quick overview of results.

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Section: Repairable Fault Treesmentioning

confidence: 99%

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Ruijters

Stoelinga

2015

Computer Science Review

586

368

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“…In addition to the extensions of the fault trees described in the above subsections, there are different other extensions such as repairable fault trees (Balakrishnan & Trivedi, 1995;Beccuti, Codetta-Raiteri, Franceschinis, & Haddad, 2008;Codetta-Raiteri, Franceschinis, Iacono, & Vittorini, 2004), temporal fault trees (Gluchowski, 2007;Palshikar, 2002;Wijayarathna & Maekawa, 2000), Stochastic Hybrid Fault Tree Automaton (SHyFTA) (Chiacchio et al, 2016), and non-coherent fault trees (Beeson, 2002;Contini, Cojazzi, & Renda, 2008) etc. Interested readers are referred to (Ruijters & Stoelinga, 2015) for more information about these fault tree extensions.…”

Section: Fuzzy Fault Treesmentioning

confidence: 99%

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

Kabir

2017

Expert Systems with Applications

325

134

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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 modelbased 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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“…The results of the sub-models are integrated into a single overall model that is small enough to be processed. Among them we have the behavioral decomposition technique [22], the hybrid hierarchical technique [23], the data structure technique for the Kroneker solution of GSPNs [24], the method of superposed GSPNs [25] or of the asynchronous communicating modules [26]. Most of these techniques are efficient when the sub-models are loosely coupled.…”

Section: Related Workmentioning

confidence: 99%

Multi‐level modeling approach for the availability assessment of e‐business applications

2003

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This paper defines a multi-level modeling approach for availability assessment of e-business applications, based on two main steps: (1) hierarchical description of the system and its interactions with the users, from the functional and structural points of view, and (2) hierarchical construction and solution of the availability models based on information from the first step. Four modeling abstraction levels are considered. The highest level (user level) describes the availability of the e-business application as perceived by the users. Intermediate levels describe the availability of functions and services provided to the users. The lowest level describes the availability of the component systems on which functions and services are implemented. The availability measures of a given level are computed based on the measures provided by the immediately lower level.

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Componentwise decomposition for an efficient reliability computation of systems with repairable components

Cited by 9 publications

References 7 publications

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

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

Multi‐level modeling approach for the availability assessment of e‐business applications

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