Background and Objective: Probabilistic risk assessment through fault tree analysis is an effective tool to estimate the probability of hazardous event occurrence in chemical process industries. The probability of failure occurrence for basic events is not often available in process industries. The aim of this study was to calculate the basic event failure occurrence probability when these events have no precise failure data. Materials and Methods:In this study, the proposed risk assessment framework was based on two fuzzy-based approaches, including five and six scales. Firstly, the fault tree diagram was constructed using the risk identification methods. Subsequently, the failure occurrence probability of the basic events were calculated by applying the two types of failure possibility distributions. Finally, the critical minimal cut sets were ranked using the importance measure analysis. Results: According to the results, the failure occurrence probabilities calculated by the five-scale and six-scale approaches for the 32 basic events were closed to each other. The occurrence probability of the top event calculated by the five-scale and six-scale approaches were 3.64E-04 and 4.76E-04 per year, respectively. After ranking the minimal cut sets based on their calculated importance measures, the process failures were determined as the critical causes of top event. Conclusion: As the findings indicated, the fuzzy-based approach seems to be a good alternative for the conventional Fault tree analysis approach for dealing with the basic events, which have no failure rate data for obtaining the failure occurrence probabilities. This study confirmed the consistency of fuzzy-based approach for the assessment of the basic event failure occurrence probabilities.
Background: If shutdown scenario of burner of the sulfur recovery unit takes place, toxic release, fire, and explosion accident can easily occur. Therefore, it is essential to assess the basic causes of burner shutdown scenario. Fault Tree Analysis (FTA) could be used to assess the occurrence probabilities of burner shutdown scenario and its basic causes/events. The failure occurrence probability of these Basic Events (BE) are often not available in lack of data and uncertain conditions. Objectives: This study was done to provide a comprehensive approach for analyzing and calculating BEs failure occurrence probability affecting the shutdown scenario, using combined fuzzy logic, expert judgment, and FTA. Methods: The study was carried out from June to December, 2016. In this study, a fuzzy-based approach based on expert judgment was proposed to calculate the occurrence probability of burner shutdown scenario in lack of data and uncertain conditions. The brainstorming and FMEA, and HAZOP study were first used to identify fault events of the fault tree. Then, based on these methods, the fault tree was constructed. Subsequently, the failure occurrence probabilities of BEs and shutdown scenario were calculated using the fuzzy-based approach and a conventional approach. Finally, the Fussell-Vesely importance analysis was used to rank the BEs in FTA. Results: Results showed that the occurrence probability of shutdown scenario was 4.76E-04 per year. Since the failure occurrence probabilities of some BEs were not available, using failure probability functions in the conventional approach cannot provide failure occurrence probabilities of those BEs. Therefore, the occurrence probability of shutdown scenario based on the conventional approach was not available. Based on the Fussell-Vesely importance measure analysis, it was determined that the blower failure while running, air pre-heater blockage, and shut-off valve fail close were 3 major causes of "burner shutdown scenario". Conclusions: The fuzzy-based approach could derive a failure occurrence probability of BEs based on expert subjective judgments using the failure possibility distributions (FPDs) in lack of data conditions. This study overcame the weaknesses of the conventional approach, to calculate BEs failure occurrence probabilities via fuzzy logic.
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