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Occupational health and safety risk assessment using an integrated TODIM‐PROMETHEE model under linguistic spherical fuzzy environment
Author(s) -
Liu Ran,
Zhu YuJie,
Chen Yao,
Liu HuChen
Publication year - 2021
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22570
Subject(s) - ranking (information retrieval) , computer science , risk assessment , risk analysis (engineering) , multidisciplinary approach , fuzzy logic , acronym , occupational safety and health , artificial intelligence , medicine , computer security , linguistics , social science , philosophy , pathology , sociology
Abstract Occupational health and safety (OHS) is a multidisciplinary activity aimed at recognizing, evaluating and controlling hazards arising in or from the workplace that could impair the health and well‐being of workers. In dealing with an OHS risk analysis problem, it is a crucial step and also a big challenge to assess the risk of occupational hazards. Normally, domain experts tend to use qualitative words to express the risk of occupational hazards due to the fuzziness of human cognition, and multiple risk criteria are often involved in the OHS risk analysis. In this study, we develop a new OHS risk assessment framework by integrating the TODIM (an acronym in Portuguese for interactive and multicriteria decision‐making) and preference ranking organization method for enrichment evaluations (PROMETHEE) methods to assess and rank the risk of occupational hazards under linguistic spherical fuzzy environment. The linguistic spherical fuzzy sets are utilized to deal with the vague and uncertain risk assessments of occupational hazards provided by experts. An integrated TODIM‐PROMETHEE algorithm is introduced to determine the risk priority of the identified occupational hazards. Moreover, we extend the indifference threshold‐based attribute ratio analysis method to derive the relative weights of risk criteria based on linguistic spherical fuzzy information. Finally, the OHS risk analysis of medical staff in a hospital is presented to illustrate the effectiveness and availability of our proposed model. Results show that the TODIM‐PROMETHEE framework being developed in this study provides a useful, effective, and practical way for the risk assessment of occupational hazards in OHS.