An interval 2-Tuple linguistic Fine-Kinney model for risk analysis based on extended ORESTE method with cumulative prospect theory

• An improved Fine-Kinney-model is proposed for OHS risk assessment. The interval 2-Tuple linguistic variable adopted to transform information. WPA operator based on consensus degree constructed. extended ORESTE method with prospect theory prioritize risk. assessment one of the most significant procedures identifying, preventing, and controlling Occupational Health Safety (OHS) risks. One many kinds techniques Fine-Kinney model. Most Fine-Kinney-based approaches can consider relative importance parameters. Nevertheless, current do not have abilities capture reference dependence effects detailed relationships among hazards. In addition, these overlook influence deviation evaluation To overcome limitations, in this paper, an model by integrating weighted power average (WPA) operator, (Organísation, rangement et Synthèse de données relarionnelles (in French)) method, cumulative theory. First, variables are information into quantitative rating Then, fuse from decision-makers, which optimization constructed determine weights decision-makers. Next, incorporated After that, automobile components manufacturing process presented test applicability rationality a sensitivity analysis conducted further illustrate Finally, comparative analyses between approach other models led illustrating its effectiveness advantages.