Production planning decisions in the mining industry are affected by geological, geometallurgical, economic and operational information. However, the traditional approach to address this problem often relies on simplified models that ignore the variability and uncertainty of these parameters. In this paper, two main sources of uncertainty are combined to obtain multiple simulated block models in an iron ore deposit that include the rock type and seven quantitative variables (grades of Fe, SiO₂, S, P and K, magnetic ratio and specific gravity). To assess the effect of integrating these two sources of uncertainty in mine planning decision, stochastic and deterministic production scheduling models are applied based on the simulated block models. The results show the capacity of the stochastic mine planning model to identify and minimize risks, obtaining valuable information in ore content or quality at early stages of the project, and improving decision-making with respect to the deterministic production scheduling. Numerically speaking, the stochastic mine planning model improves 6% expected cumulative discounted cash flow and generates 16% more iron ore than deterministic model.

中文翻译：

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随机露天矿的生产计划：以铁矿床为例

采矿业的生产计划决策会受到地质，地质冶金，经济和运营信息的影响。但是，解决此问题的传统方法通常依赖于简化的模型，而这些模型忽略了这些参数的可变性和不确定性。本文将两种主要的不确定性来源结合在一起，以获得铁矿石矿床中的多个模拟块模型，其中包括岩石类型和七个定量变量（Fe，SiO _2的等级）。，S，P和K，磁比和比重）。为了评估在矿山规划决策中整合这两种不确定性来源的效果，在模拟区块模型的基础上应用了随机和确定性的生产调度模型。结果表明，随机采矿计划模型具有识别和最小化风险，在项目早期获得矿石含量或质量方面有价值的信息以及改善确定性生产计划方面的决策的能力。从数字上讲，随机采矿计划模型比确定性模型提高了6％的预期累积折现现金流量，并产生了16％的铁矿石。