Abstract
Thousands of mining accidents occur each year, especially in developing countries like China. To guarantee the safety and health of workers and reduce the probability of productivity decrease, this paper utilizes a nonlinear methodology to find the precedence of risk factors. Based on existing simulate experiments and relevant literatures, we draw a concept mapping of risk factors which involves managerial, environmental, operational and individual criteria. By using the fuzzy analytic hierarchy process (FAHP), we estimate and rank all of these factors to develop a management model and guide the safety managers in mining process. The logarithmic fuzzy preference programming (LFPP) method is applied to analyze the data. This method is new in risk assessment in coal mining process. The results are compared with that derived from the extent analysis (EA) method and with the help of the IBM SPSS Statistics the results are confirmed to be available in safety evaluation of coal mine. In addition, the proposed evaluation system is found out to be more convenient, precise and complete during the evaluation process, compared to traditional AHP and FAHP based on EA method.
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