Optimizing cut-off grades under stochastic price: A model for open-pit lateritic nickel mining with multiple products

Abstract

The open-pit mining industry faces numerous challenges. One of the key issues is the determination of the optimal cut-off grade that ensures economic viability. Nickel, as one critical commodity in the renewable energy supply chain, adds another layer of complexity, as its prices fluctuate in uncertain market conditions. These price fluctuations further intensify the challenge of selecting the most economically viable cut-off grade. This research develops a cut-off grade optimization model in an open-pit mining of laterite ores, as the main source of nickel commodities. The proposed cut-off grade model considers two product options, i.e. pure nickel and ferronickel. The uncertainty in selling prices is presumed to follow to the Geometric Brownian Motion (GBM) function. The cut-off grade model is mathematically formulated and analytically solved using derivatives analysis to achieve the global optimal solution. There are two scenarios to be analyzed, which include deterministic and stochastic scenarios. Numerical examples indicate that the proposed model can effectively optimize the cut-off grade value to obtain the maximum profit for both scenarios. An analysis of three scenarios—most likely, pessimistic, and optimistic—shows that fluctuations in selling prices significantly affect both profit and Net Present Value, with the effect amplifying at lower optimal cut-off grades. This finding highlights the importance of flexible decision-making in mine planning to maintain financial stability under the presence of market uncertainties.