Abstract

ABSTRACT Consumption rates of reagents and consumables are typically accounted for in mine production scheduling by simple cost adjustment factors per rock type or mining block, ignoring geological uncertainty, blending, and geometallurgical information. To overcome these limitations, this article first creates empirical geometallurgical prediction models of reagents and consumables by tracking blended rock properties that are matched with observed consumption rates at the operating processing plant. The prediction models are then integrated in a simultaneous stochastic optimisation model for short-term production scheduling. Improvements over a conventional short-term production schedule are demonstrated in a case study at the Tropicana Gold mining complex.

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