Likelihood-based hybrid ORESTE method for evaluating the thermal comfort in underground mines

A thermal environment has many adverse effects on the safety and health of workers. Especially in an underground mining context, thermal hazards become more serious as mining depth increases. This study aims to find a suitable method for evaluating the thermal comfort in underground mines. First, considering the ambiguity of human thinking, picture fuzzy numbers (PFNs) are adopted to indicate the subjective evaluation information. Then, the likelihood is defined to measure the priority degree of two PFNs. Subsequently, the Organisation, rangement et Synthese de donnees relarionnelles (in French) (ORESTE) is extended with hybrid evaluation information to solve the non-compensation problems of the indexes. Finally, the likelihood-based hybrid decision making framework is successfully implemented in a case study that assesses the thermal comfort in a copper mine in China. The evaluation results are reasonable and consistent with the field conditions. Additionally, the strengths of this methodology are validated through comparison analyses. The results show that the proposed decision-making framework is reliable and stable for evaluating the thermal comfort in underground mines and can provide references for the prevention and management of thermal hazards. (C) 2019 Elsevier B.V. All rights reserved.