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2014•Unpublished venueRequires access

INTEGRATE FAULT TREE ANALYSIS AND FUZZY SETS IN QUANTITATIVE RISK ASSESSMENT

Rachid Ouache, Noor Azlinna Azizan

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Abstract

Quantitative risk assessment is the most important step to judge the results of risk estimation in the process of decision making to improve level of safety. Quantitative risk assessment hasfaced big problemwith complexity of engineering systemsin term of reliability. In this study, reliability of risk Assessment proposed to solve problem of uncertainty based on fuzzysets and fault tree analysis to precise values of top event. The results demonstrated that the model proposed is the best to solve problem of uncertainty in quantitative risk assessment.

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What this paper is about

Quantitative risk assessment is the most important step to judge the results of risk estimation in the process of decision making to improve level of safety. Quantitative risk assessment hasfaced big problemwith complexity of engineering systemsin term of reliability. In this study, reliability of risk Assessment proposed to solve problem of uncertainty based on fuzzysets and fault tree analysis to precise values of top event. The results demonstrated that the model proposed is the best to solve problem of uncertainty in quantitative risk assessment.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Quantitative risk assessment is the most important step to judge the results of risk estimation in the process of decision making to improve level of safety. Quantitative risk assessment hasfaced big problemwith complexity of engineering systemsin term of reliability. In this study, reliability of risk Assessment proposed to solve problem of uncertainty based on fuzzysets and fault tree analysis to precise values of top event. The results demonstrated that the model proposed is the best to solve problem of uncertainty in quantitative risk assessment.

Key concepts: Fault tree analysis, Event tree analysis, Risk assessment, Event tree, Reliability (semiconductor), Computer science, Quantitative analysis (chemistry), Fuzzy logic

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