Developed Regression Models of Mining Rate Fit on Resource and Reserve Variations in Gold Mining
Journal Title: International Journal of Engineering Innovations and Research - Year 2018, Vol 7, Issue 3
Abstract
Mining rate determines profitability of a mine and when set at an optimal rate generates maximum NPV. Although mining rate depends on many parameters, ore tonnage has been used as the main determinant of mining rate in the development of empirical models for predicting mining rate. However, variable results have been obtained depending on the characteristics of ore-body and mine and also the number of mines used. The main aim in this paper is to develop regression models that can be used in predicting mining rate in any gold mining in the pre-production stage depending on resource and reserve variations. The data used in this study include mining rate, resource-tonnage and resource-grade as well as reserve-tonnage and reserve-grade of 160 gold mines/deposits obtained from Raw Material Group database. Multiple Linear Regression Analysis using stepwise method was used to develop regression models. Results indicated that mining rate in the gold mining can be estimated based on the resource-tonnage and reserve-tonnage. Resource-tonnage accounted for 68.6 per cent of the determinant variables of mining rate while reserve-tonnage accounted for 77 per cent of the total variation.
Authors and Affiliations
Karim Rajabu Baruti
Keywords
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