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Abstract

The average grades of copper mines are dropped by extracting high grade copper ores. Based on the conducted studies in the mine field, the uncertainty of economic calculations and the insufficiency of initial information is observed. This matter has drawn considerations to processing methods which not only extracts low grade copper ores but also decreases adverse environmental impacts. In this research, an optimum cut-off grades modelis developed with the objective function of Net Present Value (NPV) maximization. The costs of the processing methods are also involved in the model. In consequence, an optimization algorithm was presented to calculate and evaluate both the maximum NPV and the optimum cut-off grades. Since the selling price of the final product has always been considered as one of the major risks in the economic calculations and designing of the mines, it was included in the modeling of the price prediction algorithm. The results of the algorithm performance demonstrated that the cost of the lost opportunity and the prediction of the selling price are regarded as two main factors directed into diminishing most of the cut-off grades in the last years of the mines’ production.
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Abstract

The optimization of cut-off grades is a fundamental issue for metallic ore deposits. The cut-off grade is used to classify the material as ore or waste. Due to the time value of money, in order to achieve the maximum net present value, an optimum schedules of cut-off grades must be used. The depletion rate is the rate of depletion of a mineral deposit. Variable mining costs are to be applied to the really excavated material, as some of the depletion can be left in-situ. Due to access constraints, some of the blocks that have an average grade less than the determined cut-off grade are left in-situ, some of them are excavated and dumped as waste material. Naturally, variable mining costs should be applied to the blocks of a mineral deposit that are actually excavated. The probability density function of an exponential distribution is used to find the portion of the depletion rate over the production rate that is to be left in-situ. As a result, inverse probability density function is to be applied as the portion of the depletion rate over the production rate that is to be excavated and dumped. The parts of a mineral deposit that are excavated but will be dumped as waste material incur some additional cost of rehabilitation that is to be included in the algorithm of the cut-off grades optimization. This paper describes the general problem of cut-off grades optimization and outlines the further extension of the method including various depletion rates and variable rehabilitation cost. The author introduces the general background of the use of grid search in cut-off grades optimization by using various depletion rates and variable rehabilitation cost. The software developed in this subject is checked by means of a case study.
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