Stochastic short-term production scheduling accounting for fleet allocation, operational considerations, blending restrictions and future multi-element ore control data

Mine production scheduling may be long-term or short-term based on the time period considered and the final objective. The optimization goal of short-term production scheduling is to minimize the mining cost expected from a mine while satisfying operational constraints, such as mining slope, grade blending, metal production, mining capacity and processing capacity; however some parameters may be uncertain, such as metal quality and fleet parameters. Traditional short-term production planning is carried out by two sequential optimizations, production schedule is defined at the first step and the available fleet is evaluated for this schedule as a second step, however; the fleet availability, hauling time and mining considerations do not influence the schedule decision. In addition, the fleet optimization algorithms do not consider uncertainty in their parameters and do not take into account the local mineralization of the deposit because a single possibly misleading total aggregated block tonnage is linked to each sector to be mined. The local mineralization or local scale variability between blocks assists in the blending process and metal quality control; however, the traditional short-term production scheduling is based on exploration drilling or a sparse data ore body model, while in practice grade control data or close spacing blasthole drilling classify the material as ore and waste because their short-scale information is not available at the time of the monthly short-term planning. The local variability is relevant in the short-term production scheduling to define the destination of the material.The short-term mine production scheduling in this thesis is developed as a single formulation where mining considerations, production constraints, uncertainty in the orebody metal quantity, as well as fleet parameters, are evaluated together to define a well informed sequence of mining that results in high performance at the mine operation. The formulation is implemented at a multi-element iron mine and the resulting monthly schedules show lower cost, minable patterns and, efficient fleet allocation, that ensures a higher and less variable utilization of the fleet over the conventional schedule approach.Uninformed and ultimately costly decisions can be taken because of imperfect geological knowledge or information effect. The orebody uncertainty may be updated by simulated future ore control data to account for local scale grade variability, and the information used to discriminate ore and waste in practice. Multi-element orebody uncertainty models are updated based on the correlation of exploration data and past ore control data, this orebody uncertainty is then used to optimize the short-term production scheduling that leads to better performance in terms of matching ore quality targets and delivering recoverable reserves.

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