U-HRMES: Decision theory-based model for appropriate mining equipment selection in underground hard rock stopes

Abstract

The selection of mining equipment is one of the most important parts for decision-makers, which can affect the mine and the entire planning. Underground mines are usually divided into two categories; hard rock and soft rock, each of which has its equipment according to the type of exploitation method used. There are different ways to make decisions and choose mining equipment. One of the practical approaches can be the use of the Multi-Criteria-Decision-Making models (MCDM). The main aim of this research is to develop a decision support system based on MCDM methods and use FUZZY logic to resolve uncertainties in the Underground-Hard Rock Mining Equipment Selection (U-HRMES). In this paper, the U-HRMES model has been used in Anguran underground lead and zinc mine as a case study. At present, the drilling and loading-hauling equipment of the Angoran mine does not perform properly. Therefore, to improve the performance and speed up the mining operation, it was tried to suggest suitable equipment using the U-HRMES. For this purpose, effective criteria were obtained based on a literature review, and according to the conditions of the Anguran underground lead and zinc mine, these criteria were filtered, and then, Twenty-two subcriteria with four groups of main criteria; technical specifications of the machine, economic and environmental issues, stope conditions and finally management and operational issues were obtained. It should be noted that the types of preference functions in the selection process of underground hard rock mining equipment were determined based on expert groups. Using the U-HRMES, two series of decisions were evaluated for the options of drilling equipment and loading and hauling equipment for the Anguran underground stopes. Finally, single-arm drilling with a score of 0.870 was chosen as the appropriate choice for drilling equipment, and LHD WX04 with a score of 0.252 was selected for loading and hauling equipment. Also, by analyzing the sensibility of the model results based on the change of criteria weights from ±10 % to ±20 %, there was no change in the results. The observations were that the drilling equipment selection has more sensitivity and reaction to changes in weight of the stope conditions. At the same time, the loading and transport equipment selection has this reaction and this sensitivity to changes in the weight of technical specifications of the machine.