A decision-making model for blasting risk assessment in mines using FBWM and GRA methods.

Due to the extensive use of explosives, the failure to identify hazards and assess risks in blasting may lead to catastrophic consequences. However, classical risk assessment approaches are limited in their ability to address ambiguity and uncertainty, as well as in assigning weights to the criteria involved in the risk assessment process. This study employs a multi-criteria decision-making system to address these limitations and assess the risks associated with blasting. The proposed model integrates Grey Relational Analysis (GRA) to prioritize risks and the Fuzzy Best-Worst Method (FBWM) to assign weights to the criteria critical to the risk assessment process. The findings indicated that "not using personal anti-static protection devices during blasting (R12)", "placing the explosive fuse near explosive materials (R15)", and "bringing explosive materials to the explosion site before completing drilling and blasting operations (R23)" were the most significant blasting risks, respectively. These risks stem from operational processes, human factors, and the working environment, thus requiring special attention. The weighting of the study criteria, including Consequence (C), Probability (P), and Exposure (E), revealed that the C criterion, with a final weight of 0.538, was the most influential in the risk assessment process. The P and E criteria, with weights of 0.294 and 0.167, respectively, ranked second and third in importance among the assessment criteria. To ensure the applicability and accuracy of the proposed method, a validation study comprising two distinct parts-sensitivity analysis and comparative analysis-was conducted. The results of these evaluations highlighted the appropriate and reliable performance of the proposed approach. This approach can assist decision-makers, managers, and risk analysts in more accurately identifying and assessing risks by addressing some of the limitations inherent in classical risk assessment methods.