Production scheduling and mine fleet assignment using integer programming

Production Scheduling, extraction sequence of mining blocks in different production periods to maximize profit over the life of the mine and subjected to different constraints, is an important aspect of any mining activity. Mine production scheduling problem can be solved using various approaches, but the best approach is one which can give an optimal result. Production scheduling solely cannot result in a proper planning thus, fleet assignment problem needs to be incorporated into production scheduling problem to have a realistic mine plan. Proper fleet assignment ensures that the fleet is not under or over utilized. Fleet assignment problem is integer type programming since, size of fleet cannot be a floating number. In this thesis, production scheduling and fleet assignment problem are solved using branch and cut algorithm. Production schedule for 4736 blocks from a case study of coal mine is done with a production period of 5 years. Solution time for solving the production scheduling problem was 48.14 hours with an NPV value of Rs 4.45938x1011. Short terms production scheduling is done for one year and the NPV value obtained was Rs 7.59796x1010 with a solution time of 57.539 minutes. Fleet assignment is done for first year and is observed that the size of dumper fleet can be reduced to 30 thus saving huge amount of initial capital investment

Stochastic-optimization of equipment productivity in multi-seam formations

Short and long range planning and execution for multi-seam coal formations (MSFs) are challenging with complex extraction mechanisms. Stripping equipment selection and scheduling are functions of the physical dynamics of the mine and the operational mechanisms of its components, thus its productivity is dependent on these parameters. Previous research studies did not incorporate quantitative relationships between equipment productivities and extraction dynamics in MSFs. The intrinsic variability of excavation and spoiling dynamics must also form part of existing models. This research formulates quantitative relationships of equipment productivities using Branch-and-Bound algorithms and Lagrange Parameterization approaches. The stochastic processes are resolved via Monte Carlo/Latin Hypercube simulation techniques within @RISK framework. The model was presented with a bituminous coal mining case in the Appalachian field. The simulated results showed a 3.51% improvement in mining cost and 0.19% increment in net present value. A 76.95yd³ drop in productivity per unit change in cycle time was recorded for sub-optimal equipment schedules. The geologic variability and equipment operational parameters restricted any possible change in the cost function. A 50.3% chance of the mining cost increasing above its current value was driven by the volume of material re-handled with 0.52 regression coefficient. The study advances the optimization process in mine planning and scheduling algorithms, to efficiently capture future uncertainties surrounding multivariate random functions. The main novelty includes the application of stochastic-optimization procedures to improve equipment productivity in MSFs --Abstract, page iii

Energy efficiency and carbon dioxide emissions across different scales of iron ore mining operations in Western Australia

During the last two decades, Western Australian iron ore mining industry experienced an exponential production growth arising from increased global demand for steel. The upturn in the iron ore price and considerably lower production cost encouraged extensive mining and consequently high-grade ore reserves were gradually depleted. Despite the energy-intensive nature of mining, high profitability motivated the mining companies to extract marginal-grade deposits with additional processing requirements, which increased energy consumption and ultimately increased the cost of iron ore production. This thesis sought to identify the energy efficiencies of open-cut iron ore mining operations, in terms of scale of operation as well as within individual mining processes, so that energy consumption could be reduced, and sustainability enhanced. Efficiency indices were used to determine energy efficiency across different scales of operation. Overall energy consumption (per unit of processed ore) was directly related to the scale of operation, where large-scale mining operations are more energy efficient compared to medium and small scales requiring the lowest amount of energy to process a unit of ore. This suggests that an economy of scale based on energy efficiency can be observed in iron ore mining operations. Small-scale mining operations recorded the highest energy consumption to process a unit of ore, indicating the lowest energy efficiency among the three different scales of operation. However, the composite energy indicator indicated that the energy efficiency of a particular mining operation is also influenced by the geological and physical parameters of individual factors including the waste-ore ratio, grade of ore, average haulage distance and production capacity. The results of the regression analysis confirmed that it is the combined effect of all the aforementioned parameters that has a pronounced effect on the amount of energy consumed to process a unit of ore. Energy consumption per unit of processed ore at different process stages revealed that the loading and hauling phase is the most energy intensive process stage in an iron ore mining operation regardless of the scale at which it is operating. The milling and stockpiling phase was the second highest energy consuming process stage, while the drilling and blasting phase was the subsequent energy demanding process stage in iron ore mining operations. Small-scale operations recorded a higher energy consumption in loading and hauling than the medium-scale operations, suggesting that the equipment with high load capacities and energy efficient technologies such as overland conveyor belts, and advanced technologies including autonomous haulage trucks resulted lower energy consumption in medium scale mining operations. However, the energy consumed to mill and stockpile a unit of ore in medium-scale operations was high compared to the small-scale operations, suggesting that the energy consumption in milling and stockpiling is mainly influenced by the properties of the mill feed, such as moisture content. Further, the amount of processing needed to achieve sufficient final product quality can also influence energy consumption. Findings from this study support the idea that an economy of scale can be observed across iron ore mining operations in Western Australia based on energy efficiency. The study also provided essential baseline information for future studies on the variations in energy efficiency across different iron ore mining operational scales in Western Australia

A comparison of the fuel consumption and truck models in different production scenarios

Mine planning and mine design are crucial stages of a project in the mining industry. This study aimed to determine the impact of different constraints on the design and planning of a mine. Some of the deposit characteristics and parameters that influence the economic feasibility of a project were studied. Using economic criteria such as NPV, scenarios were established based on the best conditions to obtain higher profitability. Production was identified as the most relevant variable. Subsequently, the mining design was evaluated through technical parameters such as slope gradients and ramp widths, and it was identified that they have lower sensitivity in the final design and higher sensitivity in terms of economic feasibility, performance, and environmental implications. Using operational production, the performance of the loading and haulage equipment fleets was evaluated for each of the techno-economic scenarios. Additionally, the environmental cost was compared using equipment fuel consumption and CO2 emissions. This study presents a practical methodology for analyzing relevant variables in mining projects, their interactions, and identifying potential scenarios.Peer ReviewedObjectius de Desenvolupament Sostenible::12 - Producció i Consum ResponsablesPostprint (published version

A novel powder factor based bench blast design method for large surface coal mines

Large surface coal mines in Wyoming\u27s Powder River Basin ship millions of tons of coal per annum, moving millions of cubic yards of overburden to mine the coal. Much of this volume is blasted in the form of benches, a common mining technique. Increases in production and scale of equipment in the past thirty-five years have created a paradigm shift for drill and blast personnel at these large surface mines, and the explosives industry has yet to create a blast design method specifically tailored for large surface coal mine bench blasting. This research examines the typical scale of bench blasting at large surface coal mines, develops a new method of design tailored for these operations, and tests the new method against two widely accepted traditional blast design methods. Novel contributions of the research include a new universal scale of energy distribution known as Available Energy, and an entirely powder factor based blast design method that uses cut width as part of the design process. Numerical comparison testing is done at both small borehole diameters (corresponding to the original domain of the traditional blast design methods) and at large borehole diameters. A comparison of the new method and existing major methods of traditional blast design is monitored graphically, and linear regression is used to track the improvement of the accuracy of the match. Finally, the new design method is presented in nomograph form to facilitate use in the field. Development of the nomograph is discussed and sample nomographs for specific design conditions are included. Recommendations for future work and broader applications of the Available Energy paradigm are given to conclude the dissertation. --Abstract, page iii

Applications of simulation and optimization techniques in optimizing room and pillar mining systems

The goal of this research was to apply simulation and optimization techniques in solving mine design and production sequencing problems in room and pillar mines (R&P). The specific objectives were to: (1) apply Discrete Event Simulation (DES) to determine the optimal width of coal R&P panels under specific mining conditions; (2) investigate if the shuttle car fleet size used to mine a particular panel width is optimal in different segments of the panel; (3) test the hypothesis that binary integer linear programming (BILP) can be used to account for mining risk in R&P long range mine production sequencing; and (4) test the hypothesis that heuristic pre-processing can be used to increase the computational efficiency of branch and cut solutions to the BILP problem of R&P mine sequencing. A DES model of an existing R&P mine was built, that is capable of evaluating the effect of variable panel width on the unit cost and productivity of the mining system. For the system and operating conditions evaluated, the result showed that a 17-entry panel is optimal. The result also showed that, for the 17-entry panel studied, four shuttle cars per continuous miner is optimal for 80% of the defined mining segments with three shuttle cars optimal for the other 20%. The research successfully incorporated risk management into the R&P production sequencing problem, modeling the problem as BILP with block aggregation to minimize computational complexity. Three pre-processing algorithms based on generating problem-specific cutting planes were developed and used to investigate whether heuristic pre-processing can increase computational efficiency. Although, in some instances, the implemented pre-processing algorithms improved computational efficiency, the overall computational times were higher due to the high cost of generating the cutting planes --Abstract, page iii

Investigating the effect of Iron ore wastes transportation and environmental pollution in Chadermalo

Mines have a considerable role in polluting the environment. Greenhouse gases and wastes mainly cause pollution. In this regard, trucks that carry ores in a mine are a primary source of these pollutants. Selecting trucks with low fuel consumption can help to reduce pollution. The present research seeks to evaluate the effects of the objectives (Cost objectives, Production objectives, and Environmental objectives) in mines on the type of trucks to select and the routes they take, as well as the effect of the duration of stone transportation on pollution. The study's data were obtained from the Chadormalu iron mine in Yazd Province. As the results showed, the objectives set in the mine affect the CO2 level, and the goals followed with human health concerns induce lower CO2 emissions. It found that the time ores are transported by trucks affects the CO2 level. However, only the objective type affects the waste level resulting from tailings, not the speed of trucks. It is recommended that the duration of truck loading and unloading and the time the trucks waste waiting in lines be reduced to the extent possible to lower CO2 emission

Loading and haulage in quarries: criteria for the selection of excavator - dumper system

The optimisation of loading and haulage is one of the most important issues for the yield of quarrying activities. Many external factors may affect loading and haulage system selection: amongst them a very important role is played by local topography, stability conditions, size of the excavated material and capacity of the crusher. Of course, loading and haulage equipments affect one another and should be matched in order to get an efficient system, considering both production and economical aspects; selection criteria should be mainly based on: optimisation of loading system (sometimes working as excavation equipment too); optimisation of haulage system (in terms of both single equipment and fleet); optimisation of maintenance programs and organisation (in terms of availability of the system). In particular, the paper deals with the hydraulic excavator – dumper (or truck) system, focusing on the relations between the technical characteristics of the equipments. Many loading and haulage operations have been analysed in different Italian open cast mines and quarries, in order to identify the best working relations and to derive a simple procedure for a proper selection