Document Type : Case Study

Authors

1 Faculty of Mining Engineering, Kim Chaek University of Technology, Pyongyang 999093, Democratic People’s Republic of Korea

2 School of Science and Engineering, Kim Chaek University of Technology, Pyongyang 999093, Democratic People’s Republic of Korea;

3 Department of Applied Mathematics, Kim Chaek University of Technology, Pyongyang 999093, Democratic People’s Republic of Korea

10.22044/jme.2022.11713.2163

Abstract

Mining Method Selection (MMS) is the first and the most critical problem in mine design, and depends on some parameters such as the geo-technical and geological features and economic factors. The factors affecting MMS are determined by some mining experts, and the most suitable mining method is selected using the hesitant fuzzy group decision-making (HFGDM) and technique for order performance by similarity to the ideal solution (TOPSIS) method. These factors include the type of deposit, slope of deposit, thickness of orebody, depth below the surface, grade distribution, hanging wall Rock Mass Rating (RMR), footwall RMR, ore body RMR, recovery, capital cost, mining cost, annual productivity, and environmental impact. Firstly, we propose the group decision-making (GDM) method to determine the weights of multi-attributes based on the score function with the decision-makers’ weights, in which the n-dimensional hesitant fuzzy environment take the form of hesitant fuzzy sets (HFS). Then we calculate the weights of these factors using the HFGDM method. A simple case study is also presented in order to illustrate the competence of this method. Here, we compare the seven mining methods for an Apatite mine, and select the optimal mining method using the TOPSIS method. Finally, the sub-level stope mining method is selected as the most suitable method to this mine.

Keywords