Study of Hazards in Underground Mining: Using Fuzzy Cognitive Map and Z-Number Theory for Prioritizing of effective Factors on Occupational Hazards in Underground Mines

Mining industry has an essential role in the economic and industrial development of a country by providing minerals. However, the mining industry faces considerable challenges in the field of environmental health and safety of its staff. The mining industry is a high-risk activity and a large number of miners are injured/killed each year. The problems related to miners' safety due to the exceptional condition in underground mines are more complicated. To reduce hazards and risks in the case of underground mines, identifying the most important factors that affect hazards is significant. Thus, controlling the accidents is possible as well as safety will increase by distinguishing the effective factors in the underground mining risks. In this study, 21 factors that have significant roles in underground mines accidents are identified. The factors classified into three categories, i.e., direct factors, work environment factors and systematic factors. These factors were evaluated using the fuzzy cognitive mapping (FCM) method and the casual-effect relationships between them specified. Notably, theory of Z-numbers used to overcome the uncertainty corresponding to causal relationship between the factors. Finally, the relationships between concepts were analyzed utilizing a hybrid learning algorithm and the final weight of each factor was obtained during 30 iterations. The obtained weights were prioritized and the results showed that the "falling" and "insensibility to hazards" factors with weights of 0.999 and 0.641, respectively, have the highest and lowest impact on the occurrence of underground mines accidents. It should be noticed that the factor of the fall, simultaneously with other factors, affects the occurrence of accidents in underground mines.