Assessing the reliability of firefighting systems using fuzzy Bayesian network in the floating roof tanks of a petrochemical company

This study aims to provide a risk assessment method based on a fuzzy Bayesian network (FBN) to prevent the failure of firefighting systems (FSs).

In this research, the fault tree structure was validated, and the failure factors were identified. Triangular fuzzy numbers and the combined CoA/Sum-Product method were used to calculate the failure probability. Then, deductive and inductive reasoning and sensitivity analysis were performed using fuzzy logic and fault tree transmission in a Bayesian network (BN).

The results of a case study in methanol storage tanks showed that the combination of FBN and validation of structures can be presented as a suitable method to evaluate the reliability of FSs. The content validity index of the final basic events was over 0.79. The highest and lowest failure probabilities were related to foam system failure and valve failure, respectively. Also, the failure probability for the failure of FSs was 5.7E-6 based on a fuzzy fault tree (FFT). After updating with BN, the previous probability of failure of FSs with FBN was calculated to be 0.022978, which was greater than the value of the FFT. The reliability of the system was equal to 0.77022.

the present approach can help the decisions of managers and analysts of the petrochemical industry to prevent the failure of FSs in tanks due to changes in systems.