Application of a trapezoidal fuzzy AHP method for work safety evaluation and early warning rating of hot and humid environments

• Published in: Safety science Vol. 50; no. 2; pp. 228 - 239
• Main Authors: Zheng, Guozhong, Zhu, Neng, Tian, Zhe, Chen, Ying, Sun, Binhui
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier India Pvt Ltd 01.02.2012; Elsevier
• Subjects: Biological and medical sciences; Early warning; Fuzzy; Fuzzy AHP; Fuzzy logic; Fuzzy set theory; Hot and humid environments; Mathematical analysis; Medical sciences; Miscellaneous; Occupational medicine; Public health. Hygiene-occupational medicine; Quality; Ratings; Safety; Safety evaluation; Trapezoidal fuzzy number; Warning; Early warning; Hot and humid environments; Fuzzy AHP; Trapezoidal fuzzy number; Safety evaluation; Human; Evaluation; Temperature; Work place; Environmental factor; Occupational exposure; Heat; Work safety; Humidity; Trapezoidal method; Environment; Fuzzy number; Application; Occupational medicine
• ISSN: 0925-7535; 1879-1042
• DOI: 10.1016/j.ssci.2011.08.042

► We establish a safety evaluation and early warning rating system for hot and humid environments. ► We adopt fuzzy AHP based on trapezoidal fuzzy numbers for the safety evaluation. ► The safety grade and early warning grade are determined. ► The results demonstrate the engineering practicability and effectiveness of this method. Hot and humid environments are prevalent in many industries. People working in hot and humid environments are at great risk of specific heat-related disorders, the productivity decrease and safety problems. In order to guarantee workers’ health and safety, safety evaluation and early warning rating of the hot and humid environments are studied in this paper. The fuzzy analytic hierarchy process (AHP) method is proposed to evaluate the work safety in hot and humid environments. Trapezoidal fuzzy numbers are adopted to handle inherent uncertainty and imprecision of the data involved in decision process. Within the proposed methodology, a decision group is firstly established. A safety evaluation framework containing three factors (work, environment, and workers) and ten sub-factors are established. The fuzzy weights of the factors and sub-factors are calculated based on the pair-wise comparisons. Then the fuzzy evaluating vectors of the sub-factors and factors can be calculated according to the initial evaluation data. Therefore, the comprehensive safety index, safety grade and early warning grade can be determined. An example is given to demonstrate the proposed method. The results demonstrate the engineering practicability and effectiveness of this method in extreme environment evaluation.