Abstract
�&72,353 We present a model that allows us to consider mine production scheduling coupled with the mining system at different levels of detail: from the standard origin-destination approach to a network considering different processing paths. Each of these is characterized by variable costs, capacities, and geometallurgical constraints. We then apply this model to a real mine, comparing the results with those obtained by traditional methodology: the destination of materials defined a priori, before computing the schedules, using standard criteria like cut-off grades. As expected, using optimization to schedule and define dynamically the best processing alternatives shows a big opportunity for potential value improvement. However, the main result is that using only origindestination and fixed cut-off grades may produce schedules that are not feasible when the actual constraints of the mining system are taken into account. Therefore, it is essential to include the considerations proposed in the planning process.
Highlights
We present a model that allows us to consider mine production scheduling coupled with the mining system at different levels of detail: from the standard origin-destination approach to a network considering different processing paths
® FIXED is a special case in which we preset the final destination of the mining reserve units (MRUs) in the same way as in standard approach (STD), and schedule using the same considerations about mining and final destination capacities and blending constraints
The economic values of the MRUs are computed for each possible processing path, and capacities and blending constraints are set at the node levels in the complete mining system
Summary
A result of the example described above is that constructing medium- and short- term production scheduling can be very difficult, because the planner must comply with production goals set in longer-term decisions which are based on less restrictive constraints. As presented, an extracted block can go straight to a waste dump, or it can be sent to either of the two available crushers In the latter case, the possibilities depend on the transportation system (whether the connection exists and its capacity) as well as the processing limitations of each facility (type of material, grades, etc). These methods are based on a block model that characterizes a mineralized body only in terms of the economic value of each block and the slope precedence constraints As a result, these models are very aggregated and ignore key elements like mining and processing capacities or the possibility of selecting the optimal block destination in a dynamic setting. Kumral (2015) includes constraints to reduce production variation between consecutive periods Both papers are, oriented to long-term scheduling, do not consider the short-term accessibility constraints included in this work, and focus on block destination and not alternative processing paths. The value of attribute a A (or a A) in MRU i is denoted by g(i, a)
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