A Fuzzy Decision Support System for Risk Prioritization in Fine Kinney-based Occupational Risk Analysis
Yu Chen, Xinyue Yu, Zhengyan Yang
Abstract
Analyzing Occupational Health and Safety (OHS) risks requires prioritizing risk, a vital step in hazard and effect analysis (HEA). Currently, there is no existing approach to determine the priority of risk in HEA-based occupational risk analysis that incorporates interactive risk factors and spherical fuzzy risk information. This paper presents a novel approach to address the constraints by introducing a fresh framework for evaluating job-related hazards using HEA by combining the spherical fuzzy set (SFS), the multi-attributive border approximation area comparison (MABAC) technique, and the Ordered Weighted Averaging (OWA) operator, a more sophisticated approach is achieved within this framework. The SFS is utilized in this framework to depict the more ambiguous and unsure data given by specialists, offering a more efficient approach to handling the fuzzy risk information, encompassing the non-membership degree and hesitation. In addition, an advanced MABAC method is used to prioritize occupational risk. Afterward, we provide a practical instance of utilizing the MABAC technical-oriented risk prioritization approach for evaluating potential occupational dangers in risk analysis.