Resumen

GITHIRIA, J.  y  MUSINGWINI, C.. A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value. J. S. Afr. Inst. Min. Metall. [online]. 2019, vol.119, n.3, pp.217-228. ISSN 2411-9717.  http://dx.doi.org/10.17159/2411-9717/2019/v119n3a1.

Cut-off grade is a decision-making criterion often used for determining the quantities of material (ore and waste) to be mined, ore processed, and saleable product. It therefore directly affects the cash flows from a mining operation and the net present value (NPV) of a mining project. A series of different cut-off grades that are applied over the life of mine (LOM) of an operation defines a cut-off grade policy. Due to the complexity of the calculation process, previous work on cut-off grade calculation has mostly focused on deterministic approaches. However, deterministic approaches fail to capture the uncertainty inherent in input parameters such as commodity price and grade-tonnage distribution. This paper presents a stochastic cut-off grade optimization model that extends Lane's deterministic theory for calculating optimal cut-off grades over the LOM. The model, code-named 'NPVMining', uses realistic grade-tonnage realizations and commodity price distribution to account for uncertainty. NPVMining was applied to a gold mine case study and produced an NPV ranging between 7% and 186% higher than NPVs from deterministic approaches, thus demonstrating improved project value from using stochastic optimization approaches.

Palabras clave : optimization; cut-off grade policy; deterministic approach; heuristic approach; stochastic approach; grade-tonnage realization; uncertainty.

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