Bayesian approach for safety barrier portfolio optimization

Selecting and positioning safety barriers to improve system safety is nowadays a fundamental issue in many industrial sectors (e.g., nuclear, process, railway among others). To address it, risk analysts often rely on Bow Tie diagrams, which are useful to model the system accident scenarios and appreciate the effects of safety barriers that prevent and mitigate the associated risks. However, the current approach to safety barrier selection and positioning is mainly based on what-if analyses, through which the analysts, based on their experience, add barriers throughout the Bow Tie diagram until the risk of severe accident decreases beyond the given threshold. This way, the set (i.e., portfolio) of barriers finally installed may be not cost-efficient. To overcome this limitation, in this paper we frame the barrier selection issue within the Portfolio Decision Analysis: the goal is supporting the decision maker to identify the portfolios of safety barriers for a given Bow Tie scheme, which are optimal with respect to system residual risk, reliability and investment costs, also accounting for budget limitations and barrier feasibility constraints. The optimization algorithm used to find the optimal portfolios is based on implicit enumeration, which keeps small the computational burden in case of a limited number of alternative safety barriers. An illustrative example concerning the gas release in a process plant presents the method and outlines its possible applications