An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine-to-port Transportation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine-to-port Transportation write by Mélanie LaRoche-Boisvert. This book was released on 2021. An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine-to-port Transportation available in PDF, EPUB and Kindle. "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. As such, the second train could be allocated to another operation for better use during the first three years of operation or its purchase could be delayed. The model provides decision makers with a realistic use of the mine-to-port transportation system"--
Simultaneous Stochastic Optimization
Simultaneous Stochastic Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Simultaneous Stochastic Optimization write by Zachary Levinson. This book was released on 2019. Simultaneous Stochastic Optimization available in PDF, EPUB and Kindle. "A mining complex is a fully integrated logistics network that represents the transportation and transformation of material from the source, open-pit and underground mines, to the customers and/or the spot market. Mining enterprises around the world aim to create a strategic mine plan for each of their assets that maximizes the value generated for a company and its stakeholders. Simultaneous stochastic optimization is used to generate a production schedule that defines the extraction sequence, stockpiling, processing, blending, capital investment and waste management decisions under supply uncertainty. The optimization approach exploits synergies within the mining complex by considering the contribution of each interconnected component in a single mathematical formulation. These components may include multiple mines, processors, stockpiles, waste facilities, and methods of transportation. In this thesis, a study of simultaneous stochastic optimization is completed in two operating gold mining complexes focusing primarily on the integration of waste management and capital investment decisions under supply uncertainty.The first application presents the simultaneous stochastic optimization of a gold mining complex focusing on waste management, particularly the uncertain aspects of acid generating waste. Typically, when optimizing the production schedule, the primary focus is to deliver valuable products to the market. However, this tends to ignore the environmental and economic impact of simplifying waste management requirements, including the storage and disposal of waste material. Stricter regulations and engineering requirements are transforming past mining practices to develop more sustainable operations. These transformations increase the financial cost of waste management and identify the requirement to integrate waste management into the production schedule. Additionally, misrepresenting the material uncertainty and variability associated with the amount of waste produced can impact, both, the stakeholders and the profitability of a mining complex. In this case study, a simultaneous stochastic optimization approach is applied to generate a long-term production schedule that considers waste management. The resulting schedule leads to a 6% increase in the net present value when compared to a conventional approach, while minimizing the likelihood of deviating from production targets and ensuring permit constraints are satisfied. Second, an innovative strategic mine planning approach is applied to a multi-mine and multi-process gold mining complex that simultaneously considers feasible capital investment alternatives and capacity management decisions that a mining enterprise may undertake. The simultaneous stochastic optimization framework determines the extraction sequence, stockpiling, processing stream, blending, waste management and capital investment decisions in a single mathematical model. A production schedule branches and adapts to uncertainty based on the likelihood of purchasing a feasible investment alternative that may increase mill throughput, acid consumption, and tailings capacity. Additionally, the mining rate is determined simultaneously by selecting the number of trucks and shovels required to maximize the value of the operation. The mining complex contains several sources – two open-pit gold mines and externally sourced ore material – stockpiles, waste dumps, tailings and three different processing streams. The simultaneous optimization framework integrates the blending of sulphates, carbonates, and organic carbon at the autoclave for refractory ore while managing acid consumption. The resulting production schedule indicates an increase in net present value as the optimization model adapts to uncertainty and manages the technical risk of capital investment decisions"--
A Study of Simultaneous Stochastic Optimization of Open Pit Mining Complexes
A Study of Simultaneous Stochastic Optimization of Open Pit Mining Complexes - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook A Study of Simultaneous Stochastic Optimization of Open Pit Mining Complexes write by Ziad Saliba. This book was released on 2019. A Study of Simultaneous Stochastic Optimization of Open Pit Mining Complexes available in PDF, EPUB and Kindle. "Over the last several years advances in the field of mine planning have led to the development of cutting-edge simultaneous stochastic optimization frameworks for mining complexes. The latest methods consider mining operations as a resource-to-market integrated mineral value that transforms raw in-situ materials into sellable products, a mining complex. Simultaneous stochastic optimization frameworks make use of a paradigm shift that considers the value of the sellable products, as opposed to economic block values, to drive the optimization process and capitalize on the synergies between the central, interrelated components of a mining complex. These methods maximize the value of mining operations and manage technical risk by incorporating uncertainty directly into unified optimization formulations. This thesis studies the simultaneous stochastic optimization framework through two real-world case studies, applying the methods and assessing their characteristics and limitations. The second chapter of this thesis presents an application of a stochastic framework that simultaneously optimizes mining, destination and processing decisions for a multi-pit, multi-processor gold mining complex with challenging geochemical processing constraints. The framework accounts for supply and market uncertainty via stochastic orebody and commodity price simulations as inputs to a unified optimization model. The case study notably assesses the impacts of integrating market uncertainty as input that influences all components of the production schedule. Additionally, cut-off grade decisions are determined by the simultaneous optimization process, considering material variability and operating constraints while reducing the number of a-priori decisions to be made. This approach generates solutions that capitalize on the synergies between extraction sequencing, cut-off grade optimization, blending and processing while managing and quantifying risk in strategic plans. Which ultimately leads to more metal production and higher NPVs than traditional methods. The third chapter applies an extension of the generalized simultaneous stochastic optimization formulation that considers capital expenditure (CapEx) options as part of the life-of-asset planning process. Enabling the case study to consider environmental issues relating to tailings management and model a tailings facility expansion. The application at a multi-element open pit mining complex simultaneously optimizes the extraction sequence, cut-off grades, and downstream decisions from two open-pits with a set of stockpiling options, an autoclave and a tailings storage facility. The project bottleneck is the tailings facility volume because it stores both process tails, and potentially acid-generating waste rock from the mines. Results show that, when given the option, the optimizer chooses to make a significant CapEx investment to expand the tailings storage facility 25% by volume. This expansion allows for a meaningful expansion of both pit limits, 40% by mass, resulting in an extended metal production and revenue generation horizon that yields 14% more gold ounces and a 4% improvement in NPV for the mining complex. The framework provides decision makers with a realistic evaluation of the investment's impact on the mining complex." --
Simultaneous Short-term Decision-making in Mining Complexes Integrating Geometallurgy Assisted by Production Data
Simultaneous Short-term Decision-making in Mining Complexes Integrating Geometallurgy Assisted by Production Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Simultaneous Short-term Decision-making in Mining Complexes Integrating Geometallurgy Assisted by Production Data write by Christian Both. This book was released on 2022. Simultaneous Short-term Decision-making in Mining Complexes Integrating Geometallurgy Assisted by Production Data available in PDF, EPUB and Kindle. "A mining complex is an integrated business of mines and downstream facilities that extracts raw materials, converts extracted materials into sellable products, and transports products to markets and customers. Conventionally, individual components of a mining complex are optimized independently of each other, which causes underperformance of the mineral value chain. Simultaneous stochastic optimization of mining complexes has shown to create strategic mine plans that increase the net present value while reducing risk of meeting production targets by incorporating geological and price uncertainty. While these developments jointly optimize strategic decisions of a mining complex, short-term planning makes weekly to monthly decisions to best meet long-term production targets and maximize value. These decisions include short-term extraction sequence, destination of materials, and downstream material flow in mining complexes. Furthermore, the optimal allocation of the mining fleet is an important aspect of short-term planning; however, the joint stochastic optimization of short-term production schedules and fleet management in mining complexes has not yet been developed. Additionally, geometallurgical properties that drive revenues, costs, and the ability to meet production targets, are not integrated in the optimization of short-term production schedules in mining complexes. This thesis expands the simultaneous stochastic optimization of mining complexes for long-term planning into a decision-making framework for short-term mine planning through the incorporation of fleet management and geometallurgical prediction models of plant performances into the short-term optimization of mining complexes, which is assisted by the utilization of collected datasets from production processes in mines and processing plants. First, a new stochastic integer programming model for short-term planning is developed that extends the simultaneous stochastic optimization of mining complexes to allow the scheduling of a heterogeneous truck fleet and shovel allocations while considering the costs and loss of production caused by shovel relocation. Next to geological uncertainty, equipment performance uncertainties related to production rates, availabilities, and truck cycle times are integrated. Next, a geometallurgical model for the prediction of ball mill throughput in mining complexes is developed which utilizes drilling penetration rates and recorded throughput rates of the operating plant. The creation of hardness proportions avoids biases introduced by the change of support and blending of non-additive geometallurgical properties. By integrating the throughput prediction model into the simultaneous stochastic optimization formulation, planned production can be achieved reliably because scheduled materials match with the predicted mill performance. The throughput prediction model is extended thereafter by including recorded measurements of ball mill power draw and particle size distributions. Since the addition of new features increases the possibilities of non-linearities, a neural network is used. The prediction of metallurgical responses of the operating plant and their incorporation into short-term stochastic production scheduling is finally extended by creating prediction models of consumption rates of reagents and consumables in a gold mining complex. With the new developments presented in this thesis, the simultaneous stochastic optimization of mining complexes can now be applied for short-term planning, modelling the operational aspects of the mining fleet and metallurgical behaviour of processing plants in greater detail. The integration of these short-term aspects leads to short-term mine plans that are more likely to align with long-term production targets while benefitting from synergistic effects that maximize the profit of the mineral value chain"--
On Globally Optimizing a Mining Complex Under Supply Uncertainty
On Globally Optimizing a Mining Complex Under Supply Uncertainty - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook On Globally Optimizing a Mining Complex Under Supply Uncertainty write by Luis Montiel Petro. This book was released on 2014. On Globally Optimizing a Mining Complex Under Supply Uncertainty available in PDF, EPUB and Kindle. "Mining complexes are generally comprised of multiple deposits that contain several material types and grade elements, which are transformed in available processing destinations and transported to final stocks or ports as saleable products. These components, associated with a mining complex, encompass multiple sequential activities: (i) Mining the material from one or multiple sources; (ii) blending the material including stockpiling; (iii) transforming the material in different processing destinations considering operating modes; (iv) transporting the transformed material to final stocks or ports. Since these activities are strongly interrelated, their optimization must take place simultaneously. Conventional mining optimization methods suffer from at least one of the following drawbacks when optimizing mining complexes: some decisions are assumed when they should be dynamic (operating modes, destination of mining blocks, etc.); component based objectives are imposed, which might not coincide with global objectives; many parameters are assumed to be known when they are uncertain. Past research works have demonstrated that geological uncertainty is the main cause of the inability of meeting production targets in mining projects. This thesis presents methods to optimize mining complexes that simultaneously consider different components and account for geological uncertainty. A multistage methodology that uses simulated annealing algorithm to generate risk-based production schedules in mining complexes with multiple processing destinations is presented and implemented in Escondida Norte (Chile) copper dataset. Its implementation using Escondida Norte dataset generates expected average deviations of less than 5% regarding mill and waste targets, whereas a mine production schedule generated conventionally over a single estimated model generates expected average deviations of 20 and 12% for mill and waste targets respectively. An iterative improvement algorithm that considers operating modes at different processing destinations is developed and applied to a copper complex. The objective function seeks for maximizing discounted profits along the different periods and scenarios (orebody simulations). The implementation of the method at a copper deposit allows reducing the expected average deviations from 9 to 0.2% regarding the capacity of the first process while increasing the expected NPV by 30% when compared with an initial solution generated conventionally. A method that uses simulated annealing at different decision levels (mining, processing and transportation) is described and tested in a multipit copper operation. The implementation of the method in a multipit copper operation permits the reduction of the expected average deviations from the capacities at two mills from 18-22% to 1-3% and the expected average deviation from the targets regarding two blending elements from 7-1.8% to 0.3-0.6% when compared to an initial solution generated conventionally. The expected NPV also improves by 5%. The previous method is extended to mining complexes that combine open pit and underground operations and it is tested in a gold complex in Nevada. The implementation of the method at Twin Creeks gold complex in Nevada shows improvements in meeting the metallurgical blending requirements while increasing the expected NPV by 14%. The formulations described in this thesis encompass a large number of integer variables given the discretization of the mineral deposits. To solve the problems, efficient optimization algorithms are implemented with significant improvements when compared with conventional deterministic approaches. These algorithms outperform conventional methods regarding expected NPV and meeting targets at the different components of the value chain." --
