Identifying and Prioritizing of Indicators Affecting Resilience in the Event of Fire-Induced Emergencies in a Combined Cycle Power Plant Using Fuzzy Analytic Hierarchy Process (FAHP)

Abstract

Background: Increasing the level of resilience is one of the approaches to reduce the consequences of fire. Emergency resilience is one of the most important and practical concepts in crisis management that has been considered in recent years. Objectives: The current study was aim to identify and prioritize of indicators affecting resilience in the event of fire-induced emergencies in a combined cycle power plant using fuzzy analytic hierarchy process (FAHP). Methods: By reviewing the texts and semi-structured interviews with 15 experts, 20 effective indicators in fire resilience in the combined cycle power plant were identified and classified into three main groups based on the McManomen model. In the next step, the weights of the indices of each group were determined using the FAHP method. Finally, the first three indicators of each group were selected for final prioritization and pairwise comparisons were performed between them again. Results: The results showed that three indicators of structural stability (w=0.168), senior management awareness of roles and responsibilities (W = 0.145), risk perception and acceptance (W = 0.138) play the most important role. And logistics support index (0.069) is the least important in determining the level of resilience. Conclusion: By recognizing the effective indicators in determining the level of resilience against fire in emergency situations, decision makers could define and implement corrective and preventive measures to improve safety and increase resilience based on priority.