4.7 Article

Human health and safety risks management in underground coal mines using fuzzy TOPSIS

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 488, 期 -, 页码 85-99

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.scitotenv.2014.04.076

关键词

Risk management; Human health and safety; Fuzzy TOPSIS; Kerman coal deposit; Underground mining

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The scrutiny of health and safety of personnel working in underground coal mines is heightened because of fatalities and disasters that occur every year worldwide. A methodology based on fuzzy TOPSIS was proposed to assess the risks associated with human health in order to manage control measures and support decisionmaking, which could provide the right balance between different concerns, such as safety and costs. For this purpose, information collected from three hazardous coal mines namely Hashouni, Hojedk and Babnizu located at the Kerman coal deposit, Iran, were used to manage the risks affecting the health and safety of their miners. Altogether 86 hazards were identified and classified under eight categories: geomechanical, geochemical, electrical, mechanical, chemical, environmental, personal, and social, cultural and managerial risks. Overcoming the uncertainty of qualitative data, the ranking process is accomplished by fuzzy TOPSIS. After running the model, twelve groups with different risks were obtained. Located in the first group, the most important risks with the highest negative effects are: materials falling, catastrophic failure, instability of coalface and immediate roof, firedamp explosion, gas emission, misfire, stopping of ventilation system, wagon separation at inclines, asphyxiation, inadequate training and poor site management system. According to the results, the proposed methodology can be a reliable technique for management of the minatory hazards and coping with uncertainties affecting the health and safety of miners when performance ratings are imprecise. The proposed model can be primarily designed to identify potential hazards and help in taking appropriate measures to minimize or remove the risks before accidents can occur. (C) 2014 Elsevier B.V. All rights reserved.

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