System dynamics approach for assessing the performance of safety management systems in petrochemical plants

Accidents in process industries, such as chemical, petrochemical, and refinery sectors, often stem from intricate causes. Consequently, safety management systems (SMS) have emerged as crucial mechanisms for accident prevention. In process industries, this is an interrelated and sociotechnical system consisting of numerous interacting components. However, current safety management approaches appear to be limited by linear thinking in terms of enhancing safety performance. Adopting systems thinking that considers the feedback loop and time delay is necessary to improve the efficiency and effectiveness of system performance. This study proposes a model that can predict the performance of SMS in petrochemical plants to manage risks using system dynamics (SD). Methods are proposed to build causal relationships in SMS and to develop a simulation model grounded in SD, facilitating performance evaluation within process industries. The proposed model is applied to an organization as a case study, and scenario-based simulations are performed. The case study results indicate that senior management interests are more influential to safety performance. The model is expected to be able to forecast the performance level of SMS and help decision-makers identify better policies and obtain insights to improve safety.