An integrated Z-number and intuitionistic fuzzy sets for considering uncertainty in the risk assessment using the SHIPP methodology

Abstract

Uncertainty presents a challenge in assessing risks, often resulting in outcomes that diverge from reality. System Hazard Identification, Prediction and Prevention (SHIPP), as one of the emerging risk assessment methods, aims to predict and effectively prevent accidents. This study aims to enhance the prediction potential of the SHIPP method by reducing uncertainty by combining Z-numbers and intuitionistic fuzzy logic. The experts' opinions and confidence levels regarding the prior probability of basic events (BEs) were measured using Intuitionistic Z-numbers (IZN). Subsequently, the SHIPP method utilized the obtained results and the actual data on unusual events in the industry to determine the posterior probability of barrier failure and consequences. The practical application of the developed methodology was demonstrated by selecting spherical tanks containing LPG. The results indicated that employing IZN to estimate the prior probability of BEs reduces uncertainty in determining the posterior probability of barrier failure and subsequent consequences. Consequently, enhancing the predictive accuracy of the SHIPP method in estimating the likelihood of unusual events will significantly improve the quality of risk management.