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Analyzing system safety and risks under uncertainty using a bow-tie diagram: An innovative approach

Citation

Ferdous, R and Khan, FI and Sadiq, R and Amyotte, P and Veitch, B, Analyzing system safety and risks under uncertainty using a bow-tie diagram: An innovative approach, Process Safety and Environmental Protection, 91, (1-2) pp. 1-18. ISSN 0957-5820 (2013) [Refereed Article]

DOI: doi:10.1016/j.psep.2011.08.010

Abstract

A bow-tie diagram combines a fault tree and an event tree to represent the risk control parameters on a common platform for mitigating an accident. Quantitative analysis of a bow-tie is still a major challenge since it follows the traditional assumptions of fault and event tree analyses. The assumptions consider the crisp probabilities and "independent" relationships for the input events. The crisp probabilities for the input events are often missing or hard to come by, which introduces data uncertainty. The assumption of "independence" introduces model uncertainty. Elicitation of expert's knowledge for the missing data may provide an alternative; however, such knowledge incorporates uncertainties and may undermine the credibility of risk analysis. This paper attempts to accommodate the expert's knowledge to overcome missing data and incorporate fuzzy set and evidence theory to assess the uncertainties. Further, dependency coefficient-based fuzzy and evidence theory approaches have been developed to address the model uncertainty for bow-tie analysis. In addition, a method of sensitivity analysis is proposed to predict the most contributing input events in the bow-tie analysis. To demonstrate the utility of the approaches in industrial application, a bow-tie diagram of the BP Texas City accident is developed and analyzed. © 2011 The Institution of Chemical Engineers.

Item Details

Item Type:Refereed Article
Keywords:Bow-tie analysis; Expert knowledge; Interdependence; Likelihood; Sensitivity analysis; Uncertainty; Bow tie; Expert knowledge; Interdependence; Likelihood; Uncertainty; Accidents; Fuzzy sets; Industrial applications; Sensitivity analysis
Research Division:Engineering
Research Group:Maritime Engineering
Research Field:Ocean Engineering
Objective Division:Mineral Resources (excl. Energy Resources)
Objective Group:Environmentally Sustainable Mineral Resource Activities
Objective Field:Environmentally Sustainable Mineral Resource Activities not elsewhere classified
Author:Khan, FI (Professor Faisal Khan)
ID Code:94441
Year Published:2013
Web of Science® Times Cited:37
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2014-09-09
Last Modified:2014-09-09
Downloads:0

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