Quantitative risk assessment is required by some regulations in specific situations, such as major risk evaluations. The bowtie method, which combines fault and event trees and includes safety barriers, is a valid quantitative method for analyzing industrial risks and a tool for decision-making and safety management. At present, accounting for uncertainties associated with reliability data is not necessarily mandatory in quantitative risk assessment. The quantitative method, as currently implemented, introduces uncertainties that are not addressed in the bowtie. Input data uncertainties linked to choosing values among different sources lead to variability in the results. The possibility method, presented in this article corrects this bias by considering all scenarios, without excluding those with a very low probability. For an industrial company, this specificity can allow to ensure the completeness and the robustness of its risk analysis.
This study highlights the impact of uncertainties on the quantification of a bowtie. Besides obtaining a probability, it enables decision-makers to have access to the uncertainty related to the result. This information is essential to judge the trustworthiness of the analysis and to manage risks based on uncertainties. This study allows the development of an advanced bowtie method, by considering the uncertainties associated with the input data.