Download or read book Stochastic Optimization of Stope Design and Long term Underground Mining Production Scheduling for Sublevel Open Stoping Mining Operations written by Matheus Furtado E. Faria and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Underground mine planning defines the design of technically producible economic material volumes and development openings, the sequence of multiple underground activities, and the material destinations within a mineral deposit throughout the mine's life, aiming to maximize the net present value (NPV). Due to the existence of different mining methods and the inherent operational and computational complexities, this planning is commonly performed through a stepwise optimization process in which the stope layout is preliminarily designed. Subsequently, the network of developments interconnecting the production areas is conceived, defining the precedence of underground mining activities. Finally, the strategic underground mine production scheduling is optimized, the only step that accounts for the time value of money. Available optimization methods have been focused separately on each of the planning steps, which do not benefit from the synergies between the planning steps. Additionally, most of the previously mentioned methods are deterministic; that is, they neglect many sources of uncertainty, which has been extensively demonstrated to have a significant impact on the profitability and feasibility of mining operations. Therefore, this thesis proposes stochastic optimization methods for underground mines by employing a sublevel open stoping mining method and ultimately attempts to integrate the mine design and production scheduling into a single optimization framework. The first part of this thesis presents a stochastic optimization method of stope design along with the commonly used sequential underground mine planning framework. A set of geostatistical simulations is used to quantify the variability and uncertainty of grades within the mineral deposit. The proposed method aims to maximize the undiscounted profit while capitalizing on the upside potential in terms of recoverable metal of the generated stope layout. It also accounts for the development costs of potential production levels and stopes. The application of this stochastic approach at an underground gold mine achieved a 40% higher undiscounted profit and 21% recoverable metal when benchmarked against an industry-standard deterministic stope design software tool. The second part of this thesis presents an integrated stochastic optimization of stope design and long-term underground mine production scheduling by integrating time-dependent development costs and production targets. The mathematical model seeks to maximize the NPV from the scheduled stopes, as well as to minimize the shaft, drifts and crosscuts development costs and maintenance costs to keep the levels in operation while managing the risk of failing to meet yearly productions targets. Therefore, an optimal underground mine design is yielded as an output from the optimized production schedule. The method also opens new avenues to account for time-dependent sources of uncertainty that cannot be incorporated into the stope design optimization in the sequential underground mine planning framework. A case study at an underground gold mine demonstrates that the proposed method generates more selective stopes and physically different production levels, which correspond to an 11% higher NPV and a shorter life-of-mine by two years, as compared to the sequential optimization framework"--
Download or read book Geotechnical Design for Sublevel Open Stoping written by Ernesto Villaescusa and published by CRC Press. This book was released on 2014-04-01 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive work on one of the most important underground mining methods worldwide, Geotechnical Design for Sublevel Open Stoping presents topics according to the conventional sublevel stoping process used by most mining houses, in which a sublevel stoping geometry is chosen for a particular mining method, equipment availability, and work force experience. Summarizing state-of-the-art practices encountered during his 25+ years of experience at industry-leading underground mines, the author: Covers the design and operation of sublevel open stoping, including variants such as bench stoping Discusses increases in sublevel spacing due to advances in the drilling of longer and accurate production holes, as well as advances in explosive types, charges, and initiation systems Considers improvements in slot rising through vertical crater retreat, inverse drop rise, and raise boring Devotes a chapter to rock mass characterization, since increases in sublevel spacing have meant that larger, unsupported stope walls must stand without collapsing Describes methodologies to design optimum open spans and pillars, rock reinforcement of development access and stope walls, and fill masses to support the resulting stope voids Reviews the sequencing of stoping blocks to minimize in situ stress concentrations Examines dilution control action plans and techniques to back-analyze and optimize stope wall performance Featuring numerous case studies from the world-renowned Mount Isa Mines and examples from underground mines in Western Australia, Geotechnical Design for Sublevel Open Stoping is both a practical reference for industry and a specialized textbook for advanced undergraduate and postgraduate mining studies.
Download or read book Ore Reserve Estimation and Strategic Mine Planning written by Roussos Dimitrakopoulos and published by Springer. This book was released on 2015-11-15 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: The mining business faces continual risks in producing metals and raw materials under fluctuating market demand. At the same time, the greatest uncertainty driving the risk and profitability of mining investments is the geological variability of mineral deposits. This supply uncertainty affects the prediction of economic value from the initial valuation of a mining project through mine planning, design and production scheduling. This book is the first of its kind, presenting state-of-the-art stochastic simulation and optimization techniques and step-by-step case studies. Quantification of geological uncertainty through new efficient conditional simulation techniques for large deposits, integration of uncertainty to stochastic optimization formulations for design and production scheduling and the concurrent management of risk are shown to create flexibility, options and oportunities, increase asset value, cashflows and return on investment. New approaches introduced include resource/reserve risk quantification, cost-effective drilling programs, pit design and long-term production scheduling optimization with simulated orebodies, ore reserve classification, geologic risk discounting, waste managing and demand driven scheduling, risk assessment in meeting project production schedules ahead of mining, risk based optimal stope design, options valuation when mining. Applications include commodities such as gold, copper, nickel, iron ore, coal and diamonds.
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." --
Download or read book Advances in Applied Strategic Mine Planning written by Roussos Dimitrakopoulos and published by Springer. This book was released on 2018-01-17 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of papers on topics in the field of strategic mine planning, including orebody modeling, mine-planning optimization and the optimization of mining complexes. Elaborating on the state of the art in the field, it describes the latest technologies and related research as well as the applications of a range of related technologies in diverse industrial contexts.
Download or read book Novel Optimization Models for Surface and Underground Mine Planning written by Yuksel Asli Sari and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mine planning and optimization affect efficiency, profitability and productivity of operations significantly. Low commodity prices, high resource degredation maintenance costs and high fixed infrastructure costs necessitate the use of optimal decision making tools for mining companies to make profit. All mines have different characteristics and planning phases. In this research, different optimization problems that suit various mining techniques and planning stages are studied. In essential, there are two types of mining: surface mining and underground mining. Surface mining operations are generally long-term because overburden must be removed to access the profitable orebody. This requires strategic long-term planning at the feasibility stage. The first publication in the scope of this research focuses on long-term surface mine planning with environmental considerations. The provided solution optimizes the problem using mixed integer linear programming (MILP). When operation starts and bench sectors are mined on a daily basis, the need for short term planning arises. The second publication addresses the dig-limit optimization problem, which is an important part of short-term planning. With the proposed MILP optimization method, the ore-waste boundaries are delineated with the equipment size constraints. Although underground mining also starts with exploration and resource estimation/simulation stages, the problems that need to be addressed are very different from surface mining techniques and it has its own unique challenges. Special focus is given to the sublevel stoping underground mining technique. Stope optimization is a complex problem, comprised of two sub-problems: stope layout optimization and stope sequencing. MILP formulations of stope layout optimization are impractical because of the large size of the problem. In the third and fourth manuscripts, two different heuristic stope layout optimization algorithms are presented where the former uses a clustering heuristic to identify stopes with high grade concentration and the latter uses a greedy heuristic based on dynamic programming to solve the sub-problems and explore the promising stope combinations. Fifth manuscript tailors the greedy heuristic algorithm to poly-metallic mines with pillars. Both heuristic approaches are shown to be near-optimal through comparing with developed novel MILP formulations case studies in smaller problem instances. When the stope layout is finalized, the sequence can be optimized to yield the optimal project value. In the sixth and final manuscript within the scope of this research, the stope sequencing problem is formulated in MILP. To account for risk emerging from geological uncertainties, chance constrained programming is implemented. This approach maximizes the expected net present value of the operation while minimizing the deviations from the expected value due to ore grade uncertainty. It focuses the search on a unique direction based on the specified desired project risk level." --
Download or read book Operations Research Applications in Underground Mine Production Scheduling written by Akshay A Chowdu and published by . This book was released on 2020 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mine planning is a multi-disciplinary process that guides decision-making at all stages of the mining operation. Owing to inherent uncertainty, the planning process relies on engineering estimates and is iterative in nature. Mining operations utilize a variety of operations research-based applications to improve decision-making capabilities across all levels of planning. The intent of this work is to review past applications in the field of underground metalliferrous mine planning, modify existing optimization procedures to create more realistic long-term production schedules, and propose a new mathematical formulation for optimizing short-term schedules. In the past decade, better solution algorithms, improvedmodeling techniques, and availability of cheap computational power have driven greater research interest in the area of long-term decision-making analysis regarding underground mining method selection, cutoff grade, mine layout, open pit-underground transition, and equipment selection. Production schedule optimization has also seen significant advances with a number of researchers utilizing a Resource Constrained Project Scheduling Problem-based approach to create long-term schedules.
Download or read book An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine to port Transportation written by Mélanie LaRoche-Boisvert and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--
Download or read book A Novel Stope Layout Optimization Based on Robust Genetic Algorithms written by Martha Villalba Matamoros and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "The underground mine planning process includes the evaluation of highly interdependent activities through optimization, which maximizes the net present value of a mining project. However, optimization is challenged by complexities introduced through the orebody deposits, geotechnical constraints, selective mining, and multiple mining methods. Also, underground mining operations are managed within the context of complex environmental, operational, and economic considerations (e.g., operation costs increase as mines go deeper, commodity price fluctuates over time, and there is a lack of optimization tools available). Based on these limitations, effective mine planning has the strong potential to improve operation performance, profitability, and productivity. This thesis proposes a heuristic stope layout formulation that moves beyond current optimization approaches by considering minimization of inherent internal dilution. The proposed formulation can also deal with multiple sectors and variable stope dimensions. Application of the technique to gold deposits showed that a profitable stope layout with minimum internal dilution could be generated while respecting geotechnical and operational requirements. Also, proposes a three-step stochastic optimization model combined with GAs to account for grade uncertainty and improve the heuristic algorithm efficiency. The first step computes the stope layout uncertainty, the second step creates an average design where feasibility evaluation breeds the initial population, and the third step uses GAs to improve this initial population over generations. This account for operational considerations whereby multiple orientations in the stope layout optimization are assessed, which avoids the cost of mining in the wrong direction. A case study in narrow gold vein deposit shows that the profit of an underground mining operation could be underestimated by 25-48% if the algorithm chooses the wrong stope layout orientation. Furthermore, this thesis proposes an approach based on the design of experiments to calibrate GA parameters such that the objective function is maximized/minimized and relative importance of the parameters is quantified. The proposed approach makes GA implementation robust. Applying the approach to the stope optimization problem of an underground mine--whose profit fluctuates ±7% only due to GA parameters--showed that (1) a larger population size does not always imply a longer solving-time, (2) the solving-time increases as the crossover and mutation rate increases, and (3) analyzing profit and solving-time as simultaneous responses illustrates the trade-off of acceptable computing time and profit desirability through GA parameter selection. This novel approach generates higher profit, less planned dilution, and a robust stope layout that is insensitive to orebody grade fluctuations and directions." --
Download or read book Applications of Tabu Search Parallel Metaheuristic for Stochastic Long term Production Scheduling written by Renaud Senecal and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "In open pit mine planning, the mine deposit is discretized into mining blocks, where the size of these mining blocks is defined by the mine's extracting equipment capacity and selectivity. Mining blocks are removed from the ground at different periods and sent to various destinations to be processed, stockpiled or dumped. Long-term production scheduling with multiple destinations is used in the mining industry, to provide guidelines for this extraction process, deciding the mining period and the destination policy that should apply for each mining block. The destination policy aims to optimize where to send the extracted material, in order to maximize the discounted cash flow according to the system capacity. Stochastic long-term production scheduling with multiple destinations includes the uncertainty associated with the grade's material in the optimization process, by maximizing the net present value, while reducing the risk of not meeting the different production targets at each destination. For deposits represented by a large number of mining blocks, the optimization leads to very complex and large mathematical programs, this cannot be solved to optimality using exact methods such as Branch and Bound. In this thesis, stochastic integer programming formulations are used to integrate the uncertainty directly into the optimization of the long-term production scheduling problem, and Parallel Tabu Search metaheuristics are presented as an approach to provide nearby optimal solution, in a reasonable amount of time. Two different approaches are presented here for the destination policy during the optimization process, based on the economic value of each block. The first approach uses a fixed destination policy, which sends each block to its more profitable destination before the optimization, whereas the second one considers optimizing the policy simultaneously within the optimization process of a life-of-mine schedule.The first part of this thesis, Chapter 3, presents three different implementations of parallel Tabu Search metaheuristics to solve a previously existing stochastic integer program, designed to provide optimal solution for the life-of-mine production schedule with multiples destinations, under geological uncertainty and under a fix destination policy. The first two methods allow a more extensive search of the solution space, the first using several independent Tabu Searches, whereas the second allows communication between the different Tabu Searches to broadcast information. The third method aims to provide a more intensive search by exploring different local area simultaneously, starting from a single solution. An application to a deposit of about 70,000 mining blocks is shown to assess the ability of all methods to generate a schedule with minimized deviations in practical amount of time.In the second part, Chapter 4, a stochastic integer program that jointly optimizes the destination and the year of extraction for each mining block is presented. A parallel multi-neighbourhood Tabu Search implementation is used to approximate the optimal solution of this formulation. The approach considers optimizing simultaneously both the destination and the period of extraction of each mining block by defining different types of neighbour solutions to explore. The computational complexity added by considering simultaneously extraction and destination variables is reduced by the use of a load balancing strategy to distribute the work equally among the different processors. An application at a deposit of about 100,000 mining blocks is made to show the ability of the method to generate a schedule where the production targets are met and the NPV is maximized in a practical amount of time." --
Download or read book Determining Optimal Open Pit to Underground Mine Transition Depth Using Stochastic Mine Planning Techniques written by James MacNeil and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Years of open pit mine production results in a pit of increased width and depth. This causes the cost of producing deeper ore to increase. The ore produced can also be more heavily diluted by surrounding waste. In order to increase the amount of economic reserves and mine life, a transition to underground mining can be made. There is a threshold where mining through underground methods becomes more profitable than open pit, and it is important to effectively identify this threshold as it can have a great impact on a mine's profits. This thesis uses stochastic mine planning methods to identify the optimal open pit to underground mining (OP-UG) transition depth. The method proposed herein decomposes the problem by identifying a series of candidate scenarios where it is feasible to make an OP-UG transition. The economic viability of each member of the set of candidate transition depths is then evaluated by producing uncertainty-based life-of-mine production plans which are used to outline expected yearly cash flows. An initial application of this proposed method is presented in Chapter 3 where the benefits of using stochastic mine planning to provide well-informed long-term strategic decision-making criteria are observed. Specifically, an application of the stochastic approach produces operational schedules which lead to a 9% or $43 M increase in net present value (NPV) over the corresponding deterministic framework. A second work presented in Chapter 4 describes the application of the proposed method at Geita gold mine, a large gold mine in Eastern Africa. At this operation, future ore production is forecasted to fall well below the mill's capacity, and to supplement this deficiency a transition from open pit to underground mining is being considered. The resulting analysis from the proposed stochastic framework shows that the most profitable decision involves forgoing underground mine development and continuing to produce through solely open pit mining for the foreseeable future. Valuable insights towards the risk associated with the proposed mine design are gained through stochastic risk analysis. Results show a 23% NPV increase for the stochastic mine plans when compared to the conventional deterministic equivalent." --
Download or read book The Optimization of Mine Planning Aspects Under Uncertainty written by Rein Dirkx and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mining operations typically face critical operational decisions based on uncertain information. This uncertainty is inherent to the mining process and cannot be overcome, as materials have to be extracted from underground, which can never be fully explored. This thesis addresses two pertinent aspects of many mining operations while directly incorporating this inherent uncertainty into the optimization. The uncertainty is used to our advantage by minimizing the resulting downside risk while maximizing the upside potential. The first aspect, addressed in Chapter 2, is the optimization of infill drilling schemes, a decision faced by every single mining operation on various scales. The second aspect, addressed in Chapter 3, focuses on the stochastic optimization of a production schedule of a block caving operation, a popular mass mining alternative to open pit mines. The optimization of infill drilling is based on a multi-armed bandit (MAB) framework. The novelty of this approach is the application of an advanced machine learning method like MAB to find an elegant solution to the infill drilling problem. The method is applied to a case study of a gold mining complex. The main issue in this mining complex is the uncertainty in their long-term, multi-element stockpiles on which the infill drilling optimization is performed. Stockpiles are often very variable, but their uncertainty can be quantified using conventional stochastic orebody modelling. Although the infill drilling optimization is applied to a stockpile, the proposed method is more general and can be applied to any deposit. The approach proposed in Chapter 3 is the first stochastic optimization approach for scheduling a block cave mine that explicitly includes grade and hang-up uncertainty into the optimization. Hang-up uncertainty is defined as the uncertainty related to ore that clogs the draw points due to aberrant fracturing. The grade uncertainty is incorporated via stochastic orebody simulations, similar to what has been employed for open pit operations in the past, while hang-up uncertainty, the main contribution of this work, is incorporated by tracking and minimizing the delays caused by hang-ups over multiple scenarios. The results of the case study show a reduction of the annual overtime incurred due to delays of 95 % when the hang-up uncertainty is included in the optimization compared to when hang-ups are ignored." --
Download or read book Short term Production Scheduling and Equipment Dispatching for Underground Metal Mines written by Chabva M. Tsomondo and published by . This book was released on 1996 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Exploring Stochastic Optimization in Open Pit Mine Design written by Francisco Rosendo Albor Consuegra and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Operations Research in Natural Resources written by Andres Weintraub and published by Springer Science & Business Media. This book was released on 2007-09-19 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is the first systematic handbook treatment of quantitative modeling natural resource problems, their allocated efficient use, and societal and economic impact. Andrés Weintraub is the very top person in Natural Resource research. He has selected co-editors who are at the top of the sub-fields in natural resources: agriculture, fisheries, forestry, and mining. The book covers these areas with contributions from researchers on, among others, modeling natural research problems, quantifying data, and developing algorithms.
Download or read book Application of Underground Mine Planning Optimization Tools to a Narrow vein Mine written by Alberto Ramos San Miguel and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization tools for underground mines have seen significant technological advances over the last 15 years. Complete solutions for optimizing the underground mine planning process, comparable to what is currently available for open-pit mining (Lerchs-Grossmann and Pseudoflow algorithms), are not yet available. Yet, mine planning software vendors have recently implemented optimization tools specifically for underground mining that, in combination, provide a process that reduces planning time and increases the net present value of an underground mine. This project introduces a new method termed the Stope Pseudoflow-Selection. This process combines commercially available mine planning design software tools, i.e., Deswik, to optimize underground mines. The tools consist of algorithms and heuristics that are used to create stope shapes (the Stope Optimizer), determine the location of lateral development to access the stopes (Underground Network Optimization tool), and evaluate the mine design limits (Pseudoflow algorithm). The Pseudoflow algorithm, in this application, denotes the mine design layouts that allow engineers to choose the stope and lateral development infrastructure designs that maximize a project’s net present value. This research presents a polymetallic, underground mining project characterized as a narrow-vein mineral deposit that uses long-hole stoping mining methods. The results after integrating the proposed Stope Pseudoflow Selection process into the mine design and scheduling activities maximizes the project’s net present value by 20% and reduces the overall time to create the strategic mine plan by 41%, when compared to manual design methods.
Download or read book Simultaneous Stochastic Optimization written by Zachary Levinson and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--
