A complex spherical fuzzy CRADIS method based Fine-Kinney framework for occupational risk evaluation in natural gas pipeline construction

Occupational risk evaluation is one of the most indispensable issues in the risk prevention and control process for the natural gas pipeline construction (NGPC) project. The Fine-Kinney model, recognized as an effective occu-pational risk evaluation technique, has limited capability to handle the occupational risk analysis problem under the complex spherical fuzzy (CSF) environment. Accordingly, a synthetical Fine-Kinney framework based on the compromise ranking of alternatives from distance to ideal solution (CRADIS) method is developed to overcome these downsides of occupation risk analysis in the NGPC project within the CSF context. A prioritized weighted average (PWA) operator for complex spherical fuzzy numbers (CSFNs) is incorporated into the group risk evaluation matrix generation process, which can take the priority degrees of experts into account. Then, the extended CRADIS method-based Fine-Kinney framework is generated, in which the Choquet integral for CSFNs is incorporated to reflect the impact of interactive risk factors. Next, the detailed solution procedures of the framework for handling the occupational risk evaluation problem are presented. Finally, the described frame-work is employed as an empirical example of occupational risk analysis for the NGPC project to demonstrate its feasibility in practice. After that, a sensitivity analysis of the parameter is investigated to testify to the stability and rationality of the reported synthetical Fine-Kinney framework. Subsequently, to further display the advan-tages of the developed Fine-Kinney framework, a comparative study is implemented to discuss the evaluation result of occupational risk derived from the proposed framework and those of the existing similar Fine-Kinney frameworks. The analysis results indicate that the occupational risk (attack by human or animal) with the maximum risk priority value (1.000) using the framework is identified as the most serious risk for the NGPC project.