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Stockpiles are of great importance in open pit mine production scheduling and are widely used for different reasons while being placed in different locations. Near face stockpile (NFS) is a new mining concept which combines the IPCC (in-pit crushing and conveying) method with an in-pit near-face (and near crusher) stockpile. The stockpile decouples the whole mining flow into two weakly related subsystems, which are the mining subsystem and processing subsystem. There are many theoretical advantages in comparison to the traditional open-pit mining method, such as higher tolerance on uncertainties without compromising production, higher equipment utilisation, less operating cost, better blending results, etc. The introduction of NFS, however, requires reconsideration of production planning in open pit mines. In this paper, we developed a mixed integer linear programming model to solve long-term production scheduling problem in open pit mines. To quantitatively measure the performance of the NFS mining method, we implemented the model in a real mining case study and compared the results with the traditional open pit mining method with an out-of-pit crusher. The results reveal that implementing the NFS method can improve the net present value by 9.3% and decrease the plant MWT head grade deviation by 20%.

Near-face stockpile open pit mining: a method to enhance NPV and quality of the plant throughput