Download or read book The Stochastic Optimization of Long and Short-term Mine Production Schedules Incorporating Uncertainty in Geology and Equipment Performance written by Matthew Quigley and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mine production scheduling consists of defining the extraction sequence and process allocation of mineralized material over some length of time. These decisions can be made at different time steps, which will entail varying objectives subject to different technical and operational constraints. Long-term mine production scheduling usually takes place at an annual scale for the entire life of mine and aims to maximize the net present value of the project while satisfying the mining and processing capacities. Short-term mine production scheduling consists of developing an extraction sequence on a shorter time scale, either months, weeks, or days. The goal is typically to maximize compliance with the production targets imposed by the long-term plan while considering more detailed operational constraints. Historically, these optimization frameworks have relied on the assumption of perfect knowledge of highly uncertain inputs. Developments in the field of stochastic mine planning have shown that incorporating uncertainty into the optimization of mine production schedules can add significant economic value while also minimizing the risk of deviating from production targets. This thesis will explore the benefits that stochastic mine planning can offer when applied to both long and short-term production scheduling problems.For the first exercise, the long-term mine production schedule of a rare earth element (REE) project is generated under geological uncertainty using a stochastic optimization framework. The uncertainty in REE grades is modelled using an efficient joint-simulation technique to preserve the strong cross-element relationships. The proposed approach avoids the use of the conventional total rare earth oxide grade. The stochastic long-term schedule is benchmarked against a deterministic schedule generated using an industry standard optimizer. The stochastic solution generates a 20% increase in expected NPV, ensures better utilization of the processing plant, and delivers a superior ore feed in terms of satisfying mineral and REE blending targets.For the second exercise, a formulation is proposed that simultaneously optimizes the short-term equipment plan and production schedule under both geological and equipment performance uncertainty. The proposed approach rectifies certain limitations of previous work in stochastic short-term planning by: incorporating a location-dependant shovel movement optimization; generating more realistic equipment performance scenarios; developing a new approach to facilitate more practical mine designs; and proposing model improvements to allow for a more efficient optimization of very large problem instances. The model is applied to a large copper mining complex and is compared to a more traditional approach, where the same formulation is implemented using averaged inputs for geology and equipment performance. The stochastic solution is more effective in mitigating the risk of deviating from tonnage targets at each processing destination, and the integration of equipment performance variability allows the stochastic optimizer to generate a block extraction sequence that is far more likely to be achieved." --