Optimization and sequencing a semiautomated ramp design in underground mining: A case study

Abstract

Access ramp design in underground mining is an important challenge to mining engineers, however, there are few optimizing methodologies that may guide the process. These methodologies consider only very simple costs when they made the economic evaluation of the project, because they design access first and then they complete the extraction schedule. This work presents a methodology to generate ramp designs in underground mining, their development plan and the extraction of ore plan, and then apply it in a gold and silver mine extracted by Bench & Fill method. We consider two models to approach the problem, which are combined. A first model determines a ramp design that aims to minimizes both CAPEX and OPEX without considering time. The second model considers a given ramp and maximizes the net present value (NPV), i.e., it schedules the construction and production over time. Both approaches work on the block model and rely on mathematical programming for optimization. The methodology uses both models iteratively to find a design with high NPV. We apply the methodology to a case study consisting of three zones of a Bench & Fill mine, for which different scenarios are compared, including an initial design developed using traditional design methods. The results show that the methodology improves the NPV in comparison with initial designs. Interestingly enough, the result also shows there is not necessarily a direct correlation between NPV and costs, that is, the designs with best NPV are not necessarily those with the lowest costs.