Bayesian approach for safety barrier portfolio optimization

The selection and positioning of safety barriers to improve system safety is a fundamental concern in many industrial sectors (e.g., nuclear, process, railway among others). To address it, risk analysts often rely on BowTie diagrams, which help model the system accident scenarios and describe the effects of safety barriers that prevent and mitigate the associated risks. Earlier approaches to safety barrier selection and positioning are 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 accepted threshold. However, the resulting set (i.e., portfolio) of installed barriers may be not cost-efficient. To overcome this limitation, we frame the barrier selection issue within the Portfolio Decision Analysis: the goal is to support the decision maker in the task of identifying the portfolios of safety barriers for a given Bow Tie diagram, which are optimal with respect to system residual risk, reliability and investment costs, and moreover accounting for budget limitations and barrier feasibility constraints. The optimization algorithm used to find the optimal portfolios is based on implicit enumeration, whereby the computational burden remain limited when the number of alternative safety barriers is limited. An illustrative example on the prevention and mitigation of accidental gas release in a process plant is presented to illustrate the method and to outline its possible applications.