Affiliations: [a] School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India | [b] Department of Mining Engineering, National Institute of Technology, Rourkela, India
Correspondence:
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Corresponding author: Bhanu Chander Balusa, School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India. E-mail: bhanuchanderbalusa@gmail.com.
Abstract: In the last few decades, many underground mining methods were proposed for extractions of ores. The decision-making for selecting the most suitable mining method for a typical ore depost depnds on various intrinsic and extrinsic factors (intrinsic – dip, shape, thickness, depth, grade distribution, RMR (rock mass rating) and RSS (rock substance strength) of ore, hanging wall, footwall, and extrinsic – recovery, dilution, safety, productivity, flexibility, capital). The present study aims to develop a hierarchical Fuzzy-AHP (FAHP) model for choosing the most suitable underground mining method for an ore deposit. The structure of the proposed hierarchical FAHP model consists of five levels. The level-1 of the hierarchy defines two variables (intrinsic factors and extrinsic factors). These are further classified into quantitative or qualitative nature of variable (listed in level-2). The criteria, sub-criteria, and mining method variables are listed respectively in Level 3, Level 4, and Level 5. For each level of the hierarchy, a fuzzy pair-wise comparison matrices are developed using the corresponding levels’ listed variables. These matrices at each level are subsequently used to determine the local and global weights of each variable. The global weights are used for prioritizing the different mining methods. The proposed hierarchical FAHP model was validated by considering the field data of two different ore deposits in India. The results showed that the most appropriate mining method predicted from the decision-making model and the adopted mining method for extracting the ore deposit are same in two case studied mines.
Keywords: Multi-criteria decision making model, hierarchical fuzzy-AHP, underground mining methods
