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مدیریت تجهیزات به سمت استخراج پایدار
Equipment Management towards Sustainable Mining
A typical mining company has three important assets: the human labor-force, the orebody, and the equipment. Trucks, excavators, drilling machines, crushers, grinders, classifiers, and concentrators comprise the equipment. Mining operations that want to take advantage of economies of scale have huge equipment fleet, and the worth of the equipment may easily exceed a hundred million dollars. The reliability and availability of this equipment play critical roles in increasing the efficiency and productivity of a mining operation. The losses associated with low performance or unavailability can be significant. The contribution of this thesis can be divided into two sections. The first part proposes an effective maintenance management approach to be used in the mining industry such that equipment availability and reliability are improved. The second section investigates the reduction effect on greenhouse gas emissions due to maintenance activities since most of these enormous equipment fleets used in mining are still diesel-powered.
Using failure data of a mining truck fleet in an open-pit Canadian mining operation, a case study is conducted to determine the optimal inspection intervals based on the desired reliability level to detect potential catastrophic failures. Next, a preventive maintenance scheduling plan based on systems’ rejuvenation after each repair is explored for mining equipment. Finally, the relationship between equipment reliability and CO2 emissions is quantified and a regression model to predict emission is developed. The research outcomes show that the proposed approach has the potential to increase the efficiency and productivity of the mining equipment and can be used to contribute to equipment management towards more sustainable mining operations.
کاربرد بهینه سازی تصادفی همزمان در مجتمع های معدنی و یکپارچه سازی حمل و نقل معدن به بندر
An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine-To-Port Transportation
A mineral value chain or mining complex is an integrated system representing all components of a mining operation for the extraction, transportation and transformation of material, from sources (open pit and underground mines) to customers or the spot market. Simultaneous stochastic optimization aims to optimize all components of a mineral value chain, including extraction schedules for the mines, stockpile management, processing and transportation scheduling, jointly to capitalize on the synergies that exist within the system. Additionally, the simultaneous stochastic optimization approach incorporates material supply or geological uncertainty using equally probable geostatistical (stochastic) simulations of the attributes of interest of the deposits. The incorporation of material supply uncertainty allows the approach to manage the related major technical risks.
The first contribution of this thesis is the application of simultaneous stochastic optimization at a three-mine open pit gold mining complex, incorporating material supply uncertainty using stochastic simulations of the gold grades of each deposit. The case study maximizes the net present value of the operation by generating life-of-mine schedules for each deposit considered and stockpile management plans, which maximize gold production and minimize the associated costs. The study also assesses the impacts of material hardness on the processing facilities, notably the SAG mill, and the recovered gold. This assessment indicates that the SAG mill is the bottleneck of the operation; due to the lack of availability of soft material in the considered deposits, the throughput of material at the SAG mill is significantly lowered.
The second contribution of this thesis is a new stochastic mathematical programming formulation jointly optimizing long-term extraction scheduling and mine-to-port transportation scheduling for mining complexes under supply uncertainty. Mine-to-port transportation systems represent an important component of certain mining complexes, such as iron ore mining complexes, ensuring that extracted products reach their intended clients. This component of the mineral value chain has not been included in previous simultaneous stochastic optimization formulations, ignoring the interactions between the transportation system and the other components of the mining complex. The proposed model simultaneously optimizes extraction scheduling, stockpile management, mine-to-port transportation scheduling and blending under material supply uncertainty. It aims to minimize the costs associated with meeting quantity and quality demand for the products at the port, managing the risks associated with the material supply uncertainty using stochastic simulations of grades. The model is applied to an iron ore mining complex consisting of two open pit mines, each with a waste dump, a stockpile and a loading area, connected to a single port by a railway system. Material is transported by two trains. At the port, demand for two products are considered, each with quality constraints relating to five elements. Stochastic simulations of the five elements considered are used to represent the material supply uncertainty. By optimizing the extraction and the mine-to-port transportation jointly, the case study is able to determine that only the first train is necessary to transport material to meet demand at the port for the first three years of mine life; for the remainder, the second train is also needed.