Optimising the long-term mine waste management and truck schedule in a large-scale open pit mine

Abstract

A mine landform progression plan can provide a clear outlook of the entire mining operation. To produce such an output requires detailed placement schedule of the mined material, including the volume (or tonnage) and the allocated dumping location. However, current practices mainly focus on the ore production, over-simplifying the waste material scheduling. As a result, a rock dump is often treated as a single point in long-term planning, making it difficult to predict the progression pattern over the life of mine. Without such a guidance, it is almost impossible to carry out progressively rehabilitate of the waste rock dumps. The lack of detailed waste material dumping schedule could cause delay in development construction, i.e. tailing storage facility and Run of Mine-pad. Other downstream effect due to the over-simplification is an inaccurate estimation of required truck, which could have huge financial impact on the operation. In this paper, mixed integer programming models of different objective functions, i.e. maximise truck productivity by minimising the overall haulage distance, minimise required truck deviation between adjacent years, and a hybrid between the two objectives, are utilised to generate the long-term optimum rock placement schedules under the condition of satisfying site-specific requirements. All three models are implemented in a large-scale open pit mine. The numerical solutions from the models form three different schedules of mined material placement, based on which, the yearly truck requirements are easily calculated and compared. The graphical results show the three corresponding landform progression patterns over the life of mine, providing the optimised long-term forecast of the operation.

Keywords:

• Landform progression
• Mixed integer programming
• Truck scheduling
• Maximising truck productivity
• Waste dump scheduling and optimisation

Notes

The paper is part of a special issue on Smart Mining Complexes and Mineral Value Chains