Assessment of Critical Fire Risks in an Industrial Estate Using a Combination of Fuzzy Logic, Expert Elicitation, Bow-tie, and Monte Carlo Methods

Background and Objective: Industrial estates have been described as highly prone to fire incidents. According to the baseline studies, more than 85% of the industrial accidents occurring in industrial estates during the 80s and 90s were fire incidents affecting more than one factory in 10% of the cases. Materials and Methods: After the identification of 30 high-risk industries in Abbasabad industrial estate, a fault tree was designed using the hazard and operability analysis (HAZOP). In the next stage, the weak links in the system were pinpointed using quantitative and qualitative analysis and Bayesian network. The failure rate of each area was predicted using the available data and experts’ opinions, and then calculated using the fuzzy logic and Monte Carlo methods. The data were analyzed in the Crystalball software. After the analysis of the risks, the critical risks were identified and filtered using the Bowtie method, and then subjected to the management process. Results: The consultation with industrial experts during the HAZOP process and application of filtration resulted in the identification of 15 major incidents, 9 and 6 events of which were probabilistic and fuzzy, respectively. The risks were rated based on the experts’ opinions and the given model; in this regard, the foam and paint industries gained the highest modeling score. Conclusion: The sensitivity analysis of failure probability revealed that the industries using or producing materials with a low flammable point have a higher risk; therefore, more attention should be paid to these industries to prevent the fire incidents. The application of the results of this study in the development of the required guidelines and trainings for the industrial managers resulted in a decrease in the number of accidents in Abbasaabad estate.