جستجوی مقالات مرتبط با کلیدواژه « نقشه شناختی فازی » در نشریات گروه « مهندسی معدن »

The application of new technologies has a significant effect on increasing the efficiency and improving the productivity of production factors in various industries, such as the mining industry. This requires implementing correct and practical strategies, and any incorrect procedure can cause companies and businesses to waste resources. Accordingly, the main aim of this study is to determine attractive strategies for the use of so-called fourth-generation technologies (industry 4.0) in the mining sector of Iran. To do this, a multi-criteria decision-making (MCDM) problem was employed. Therefore, this study presents a new method for evaluating and prioritizing smart mine strategies using a combination of Z-number theory and fuzzy weighted VIKOR technique with a fuzzy cognitive map (FCM). In this regard, questionnaires containing five strategies (options) and 11 criteria were designed and presented to a team of eight experts. The results obtained from the prioritization of the proposed hybrid model confirm that the strategy of "provision of government incentives to mines to use up-to-date technologies" is the most appropriate alternative for implementing industries 4.0 in large-scale mines in Iran. Furthermore, a parametric sensitivity analysis was performed to determine the effectiveness of the proposed strategies. Results showed that the proposed strategy is a fixed mechanism for ranking smart mining engineering strategies. Meanwhile, the weight of the strategy does not affect their ranking.

Mines as non-renewable resources have a significant role in the economic and social development of countries. However, at the end of the mine's life, to achieve sustainable development, the mine's pits reclamation is vital. Due to the situation of most mines that are located in remote areas, mine's reclamation based on renewable energies can be an appropriate strategy. In this study, a new hybrid method using the Fuzzy Cognitive Mapping (FCM) method, grey Complex Proportional Assessment (COPRAS-G), and Z-theory reliability is introduced for prioritization and selecting of the mine's reclamation strategies. The proposed method, for reclamation of an open-pit lead-zinc mine by considering several criteria and strategies is applied. The results of the FCM show that the average wind speed criterion has the highest weight. Also, the prioritization of the strategies showed that "closing the mine and building wind turbines" is the best strategy for reclamation of the investigated mine. Therefore, considering the windy situations in the study area, building a wind farm to supply electricity is a suitable strategy to achieve sustainable development in the region.

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.

The occupational and health hazards associated with working in coal mines are known as the main concerns despite the high importance of coal production in the economic development of countries. Irreparable damages to personal and financial losses can be avoided if the effective factors result in the occupational risks of underground coal mines are identified. In this research, these factors were initially identified in the case of underground coal mines in Iran. Then, the direct and interaction effects of the identified factors were evaluated and determined using fuzzy cognitive map approach that is based on the analysis of the cause and effect interaction between the identified effective factors. Results indicated that dust concentration, individual negligence and mistakes, inappropriate and inadequate ventilation, errors in design, planning, and execution, and the volume and concentration of methane gas are respectively determined the important factors caused the occupational hazards in the underground coal mines of Iran. The statistical study of the accidents occurred in Iran's underground coal mines, especially recent events, confirms the results of this research.