Cost-effective maintenance of safety and security barriers in the chemical process industries via genetic algorithm

Chemical plants face safety hazards and security threats that may induce catastrophic scenarios. Safety barriers are employed widely to protect chemical from accidental intentional undesired events mitigate consequences. Managing effectively economically is a research topic with practical significance. The analysis of event scenarios, including both adverse assessing associated critical regarding cost-efficient barrier maintenance. This study proposes novel approach for optimizing maintenance strategy considering economic constraints. consists three steps: scenario building identification, modeling, determining optimal intervals. In the proposed approach, accident scenarios in terms physical constructed using extended bow-tie diagrams. After identified, system simulation model developed conduct modeling based on MATLAB/Simulink simulations, which maintenance, impacts human organizational barriers, correlations between caused by shared components considered. Finally, combination cost-effectiveness (CEA) genetic algorithm (GA) support decision-making optimization. An illustrative case this validate feasibility approach.