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By M. E. Gershon

Conventional methods of drill hole site selection are reviewed briefly. Two approaches using geostatistics are then discussed, both of which have been shown to yield improved results. Finally, a branch and bound algorithm is described which will select the best locations for drilling from a user specified number of possible drill sites. Two options are discussed. First, the user can specify a maximum drilling investment or a maximum number of drill holes and the program will select the locations yielding the minimum estimation variance. This amounts to getting the most for a given investment. Alternatively, a maximum tolerable estimation variance can be specified and the program will select the number and location of the drill holes to obtain the desired information at a minimum cost. Another benefit of the approach is the quantification of the tradeoffs between investment and information obtained.

Jan 1, 1985

By M. E. Gershon

Conventional methods of drill hole site selection are reviewed briefly. Two approaches using geostatistics are then discussed, both of which have been shown to yield improved results. Finally, a branch and bound algorithm is described which will select the best locations for drilling from a user specified number of possible drill sites. Two options are discussed. First, the user can specify a maximum drilling investment or a maximum number of drill holes and the program will select the locations yielding the minimum estimation variance. This amounts to getting the most for a given investment. Alternatively, a maximum tolerable estimation variance can be specified and the program will select the number and location of the drill holes to obtain the desired information at a minimum cost. Another benefit of the approach is the quantification of the tradeoffs between investment and information obtained.

Jan 1, 1985

By Mark E. Gershon

Conventional methods of drillhole site selection are reviewed briefly. Two approaches using geostatistics are then discussed, both of which have been shown to yield improved results. Finally, a branch and bound algorithm is described which will select the best locations for drilling from a user specified number of possible drill sites. Two options are discussed. First, the user can specify a maximum drilling investment or a maximum number of drillholes and the program will select the locations yielding the minimum estimation variance. This amounts to getting the most for a given investment. Alternatively, a maximum tolerable estimation variance can be specified and the program will select the number and location of the drillholes to obtain the desired information at a minimum cost. Another benefit of the approach is the quantification of the tradeoffs between investment and information obtained.

Jan 1, 1983

By L. Chunpongtong

One of the challenges of mine planning is to determine the most cost-effective replacement time for aging equipment. The lifespan of equipment, such as haul trucks and shovels, deployed in mining operations varies due to the nature of the material and ground conditions in which it operates. For engineering economists dealing with aging equipment, the options become an economic trade-off between higher maintenance cost versus the cost of new equipment. The discount rate plays a significant role in this decision; the higher the rate, the longer the economically optimal lifespan. Therefore, the ultimate question is: ?How can the relationship between the discount rate and the economically optimal lifespan be expressed mathematically??

Aug 1, 2013

By Arka Jyoti Das, Prabhat Kumar Mandal

"Coal mining in India has a strategic importance for the energy security of the country. Presently, the majority of coal production is coming from open-cast mining. Due to the fast depletion of reserves amenable to open-cast mining, future coal production will depend primarily on underground production. In conventional bard-and-pillar/room and pillar mining as it is practiced in India, the percentage of extraction is very low. In fact, within most Indian coalfields, a large number of coal seams extract only 15- 20% of coal, but no pillar extraction is done due to the presence of surface or sub-surface structures leading to huge amount of coal being locked-up in underground. Spontaneous heating and fire, the accumulation of poisonous gases, severe stability issues, unsafe workings and environmental hazards are all major problems associated with these developed coal pillars, so there is a pressing need for technology in the mining industry to extract this huge amount of coal locked up under different constraints. In this study, we propose that the locked-up coal be extracted by replacing the developed coal pillars with artificial pillars. The paper briefly discusses the extraction methodology designed for this and its evaluation through numerical modeling for applied suitability underground.INTRODUCTIONDriven by rising populations and urbanization, an expanding economy and also a quest for improved quality of life, energy usage in India is expected to increase manifold in the coming years. As for India's energy scenario and its projected future plans, there is no doubt that coal will remain a prime source of energy, even over the next few decades.The majority of coal production in India comes from open-cast mining because of large-scale mechanization, but the coal reserves amenable to open-cast mining are gradually depleting - which may impose adverse impacts on the energy sector if underground production does not increase. Underground coal extraction, meanwhile, is going to become more complicated in near future due to the fast exhaustion of easily mineable coal reserves."

Jan 1, 2016

By Rodney L. Williamson

Optimal estimation theory has been applied to the problem of estimating process variables during vacuum arc remelting (V AR), a process widely used in the specialty metals industry to cast large ingots of segregation sensitive and/or reactive metal alloys. Four state variables were used to develop a simple state-space model of the V AR process: electrode gap (G), electrode mass (M), electrode position (X) and electrode melting rate (R). The optimal estimator consists of a Kalman filter that incorporates the model and uses electrode feed rate and measurement based estimates of G, M and X to produce optimal estimates of all four state variables. Simulations show that the filter provides estimates that have error variances between one and three orders-of-magnitude less than estimates based solely on measurements. Examples are presented that verify this for electrode gap, an extremely important control parameter for the process.

Jan 1, 2001

By B Belle

In a predrained gassy coalmine, ventilation control plays a secondary role to the longwall (LW) goaf drainage systems to safely manage panel return gas levels. Typically, the LW specific gas emission (SGE) estimation models provide anticipated goaf gas emissions and arriving at required gas drainage capacity for various coal production scenarios. A study comparing the various LW goaf gas hole spacing patterns with weekly production rates of up to 270 kt/w of an operating mine with high SGE rates (~20 m3/t) was carried out. The goaf capture efficiency of LW panels ranged from 64 per cent to 85 per cent. For the first time, gas content of upper seam data post LW retreat were used to verify the current SGE prediction models. This study has shown that an average of 50 m goaf spacing is optimal for management of high production retreat gassy LW panels in presence of multiple upper and lower seams with gas emission zone influence reaching up to 200 m above workings. Due to the horizontal stress direction related geotechnical issues, goaf hole failures just behind the LW face is a recurring challenge resulting in significant and immediate increase in LW panel return gas levels. This paper highlights the shortcomings of current SGE prediction models for goaf gas estimation, and evolution of 50 m goaf hole spacing embedded in design process in managing the LW tailgate gas levels.CITATION:Belle, B, 2017. Optimal goaf hole spacing in high production gassy Australian longwall mines – operational experiences, in Proceedings Australian Mine Vent Conference 2017, pp 15–26 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 28, 2017

By K. Norrena, E. Magri

An important problem in mine operations is the classification of material as waste, low-grade stockpile and ore. This classification must often be made with blasthole data that are widely spaced and that have sampling errors. Geostatistical-simulation techniques combined with basic economic principles allow a procedure for classification that maximizes the expected profit. Geostatistical-simulation methods (Gaussian, indicator or annealing-based) allow the integration of hard and soft data in the creation of alternative, equally probable realizations of the mineral grades. At each location, for each realization one calculates the "profit" if the block were to be classified as ore or waste. The optimal classification is the one that maximizes expected profit (a maximum profit selec¬tion or MPS procedure). In this paper, the authors discuss the theoretical justification of the method and implementation details. The use of blasthole data from different types of mineral deposits, that is, different levels of continuity, are considered. The authors also show the efficacy of the procedure with different levels of sampling error. The increased revenue due to the MPS procedure and improved sampling is shown. The paper shows the geostatistical-simulation procedure and the uncertainty in block grades that result from incomplete and imperfect sampling. The optimal classification is presented. Optimal block classifications are transferred to realizable dig limits by hand-drawing polygonal boundaries. The results of the proposed method are compared to classification based on kriging. Limitations and areas of future work are identified.

Jan 1, 2000

An important problem in mine operations is the classification of material as waste, low-grade stockpile, and ore. This classification must often be made with blasthole data that are widely spaced and that have sampling errors. Geo-statistical simulation techniques combined with basic economic principles allows a procedure for classification that maximizes expected profit. Geostatistical simulation methods (Gaussian, indicator, or annealing-based) allow the integration of hard and soft data in the creation of alternative, equally-probable, realizations of the mineral grade(s). At each location, for each realization, we calculate the "profit" if the block were to be classified as ore or waste The optimal classification is the one that maximizes expected profit (a Maximum Profit Se-lection (MPS) procedure). We discuss the theoretical justification of the method and implementation details. The use of blasthole data from different types of mineral deposits, that is, different levels of continuity, is considered. We also show the efficacy of the procedure with different levels of sampling error. The increased revenue due to the MPS procedure and improved sampling is shown. We show the geostatistical simulation procedure and the uncertainty in block grades that result from incomplete and imperfect sampling. The optimal classification is presented. Optimal block classifications are transferred to realizable dig-limits by hand-drawing polygonal boundaries. We compare the results of the proposed method to classification based on kriging. Limitations and areas of future work are identified.

Jan 1, 1999

By T Wambeke, J Benndorf

A risk-robust development of a heavy mineral resource requires an assessment of the geological uncertainty and spatial variability of the key factors impacting the mining and processing operation. Attributes of interest are the total heavy mineral grade, the slime content and the amount of oversized particles. The modelling of a mineral sand deposit presents two main challenges. Firstly, the exact location of the geological boundaries are obscure due to the complex interaction of the deposit formation processes. Secondly, the properties of interest exhibit a rather complex transitional behaviour across the so-called soft boundaries. Traditionally, the modelling exercise is restricted to a consecutive stochastic simulation of distinct geological facies and orebody properties. This results in different zones separated by hard boundaries, ignoring the typical transitional behaviour.This contribution presents an alternative approach which models the entire sand body as a single domain while accounting for the complex trends present. Error curves are used to infer covariance model parameters without the need of a prior removal of the trend. The principle is based on minimising the differences between empirical and theoretical errors resulting from two methods of prediction calculated for different rings of influence. The added value results from the unambiguous decomposition of the spatial variation into a deterministic trend and a stochastic residual. The trend model neither overfits nor underfits the data. The calculated residuals are thus unbiased and the uncertainty can be correctly assessed.The effort results in a characterisation of the resource uncertainty which provides a more realistic image of the spatial variability of the key properties in and across the geological domains of an existing heavy mineral sand deposit.CITATION:Wambeke, T and Benndorf, J, 2014. Optimal inference of modelling parameters to simulate complex trends across soft boundaries – a case study in heavy mineral sands, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 73–84 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By Jorgen Elbrond, Yve Lizotte

"A mathematical procedure for determining the underground mining level layout which minimizes the total costs of excavation and haulage is described. This procedure has the advantage over previous graphical procedures of being easily amenable to microcomputers. The paper demonstrates through examples how the procedure can be applied to minimizing discounted costs of level layout as well as providing the optimal location of a production shaft.IntroductionIn recent years there have been numerous publications in mining journals concerning the minimization of mine haulage costs. With the rapid escalation of energy costs during the last decade it is not surprising that several studies applying queuing theory, simulation and mathematical programming to mining related transportation problems have been successfully undertaken. Because of the increasing availability of various sizes of computers these techniques have gained considerable popularity as evidenced by the numerous commercial packages presently being marketed.The publications concerned with haulage cost minimization are generally concluded along the lines of ' ... haulage costs at production rate x will be minimized by assigning y units to location z...'. Details about the route followed and whether it guarantees a minimization of costs are seldom considered. Route data has to date been manually resolved and used for input to developed programs. It would appear that no program has been developed to date which simultaneously minimizes costs by both fleet assignment and routing network resolution.Another important factor in transportation problems is the investment cost associated with the routes; road construction costs or, in the case of underground levels, drift excavation costs. Except for special cases the transport network which minimizes haulage costs only will not provide a minimum excavation cost solution.Zarnbo(1) illustrates by graphical and mathematical procedures how central 'facilities' can be located to simultaneously minimize investment in the transport network and haulage costs. Unfortunately these procedures and others recently applied to mine haulage problems do not provide solutions to the generalized problem. Also because these procedures are geared to graphical solutions and hand computations whereby certain possibilities can be 'visually' eliminated, they can be tedious to program and present storage capacity constraints with current microcomputers."

Jan 1, 1985

By Felipe Costa Hashimoto Bertin, Jorge Alberto Soares Tenório, Rodrigo de Souza Dalti Pereira, Denise Crocce Romano Espinosa

"The increasing amount of portable devices and their fast obsolescence generates an increasing quantity of discarded batteries. The recycling process of discarded batteries allows the recovery of metals for further use and avoids the contamination of soil and water. Even though there are several researches on the topic, few papers focus on mixed batteries. The purpose of this work is to characterize a mass of collected mixed batteries and study the hydrometallurgical process of recycling. The specific leaching parameters studied were pH, temperature and reduction potential. The specific goal was testing the selectivity of pH for leaching each metal. The results show that the optimal leaching occurs in acid solutions with negative pH at IM of sulfuric acid and at room temperature (25°C).IntroductionThe increasing portability of electronic devices in the past century along with their fast obsolescence produce tons of discarded materials yearly that could be recycled generating new materials for the industry. For example, metals such as cobalt and nickel, that are worth respectively US$ 30.00 and US$ 16.10 per kilogram[l,2] are disposed in urban trash yearly, which means that millions of dollars are thrown away instead of being recovered and reused[3].Besides the obvious fact that the society is throwing money away, most of these metals are toxic for the environment and all mammals, so when badly stored after use they can be found contaminating ground water which will contaminate the entire lifecycle. Some of these metals can cause cancer, serious lung problems and have bioaccumulative properties [4] resulting in lower productions of natural products and maybe death for consumers.So in compliance to new regulations such as the National Solid Residue Politic (PNRS) and the CONAMA-Resolution N°401 from November of 2008[5]- (that follows similar restrictions and regulations as the European directives) all those urban and electronic wastes need to be correctly disposed and treated before being thrown away on local dump sites.In Brazil the national rate of garbage recovery is around 70%, which only 5% is properly recycled, accordingly to the research of the UFSC, also electronic waste grows at 5% per year [6]The present study was motivated by the fact that recycling processes for batteries are not spread through the country and by the fact that most papers do not try to recycle a mixed mass of batteries, but a specific mixture which does not represent the composition of traditional household wastes."

Jan 1, 2014

By Gergö Rimaszéki

Due the fast growing of pig iron and steel in the last years associate with some mineral resources changes (Hematite?Itabirite), has been checking the sinter feed degradation. The typical sinter feed (0.15;-6.3 mm) has become limited and the rapid growing production resulted in more and more fine ore (< 150 µm) availability in the market. The sinter plant operators are facing several new challenges since the mixing and granulation- and the sintering behavior of the fines containing mixtures often differs from the traditional sinter feed´s behavior. The utilization of fines in the sinter plants might increase the process water consumption required for the mixing and granulation process or even the solid fuel consumption, which effects the operational cost of the plant significantly. The current study presents an overview about Outotec´s laboratory facilities and competence regarding the mixing and granulation of fines in different equipments. The usage of high intensity mixers (HIM) – vertical and horizontal as well – showed to be the most effective, based in cold agglomeration tests in small scale, in case of fine ore handling. Permeability and particle size distribution curves are used to evaluate and demonstrate the efficiency of the different equipments. Outotec´s ”Know-How” with the different type of mixer and the modern laboratory facilities provide an excellent opportunities to optimize the mixing and granulation procedure and utilize up to 100 % pellet feed

Aug 17, 2017

By M Forbes, R Jeuken

Brownfields geoscience measurement such as drilling and surface geophysics can be costly and it is often difficult to weigh the cost of data collection and processing against the value it unlocks at the time of extraction. This makes it difficult to prioritise geoscience expenditure and find the optimum intensity of geoscience activity across competing assets. There are multiple options for managing resource uncertainty and spatial variability through mine planning and resource engineering such as varying marketing strategy, adjusting stockpile or other infrastructure design and product blending. Consideration of these alongside increased data collection further complicates finding a comparable value of geoscience programs to determine the right blend of geoscience measurement and engineering controls. Concepts similar to Value of Information (VOI) analysis which is applied to strategic planning can be used to estimate the value of geoscience measurement and pit sequencing at tactical planning and operational timescales. This involves the quantification of resource uncertainty and prediction of how it will affect resource extraction. This paper outlines this process and demonstrates its use to prioritise geoscience at BHP Coal Assets. The value of infill drill programs in enabling operational stability is quantified and compared the value of engineering controls like increased stockpile capacity. This study supports that idea that the application of VOI methods to bulk mining at tactical time horizons has potential to inform geoscience planning and resource engineering not just separately, but as part of a unified strategy for managing resource uncertainty.

Mar 22, 2022

The authors summarise the development and recent advances in the reconstruction and visualisation of three-dimensional objects from point data and describe applications to the reconstruction of orebody shapes from drill-hole and other data. In particular, Dijkstra's algorithm is proposed and implemented as a means of optimal reconstruction of complex orebody and topographical shapes from irregularly located sample data. The surfaces of the shapes are constructed from triangular tiles and the algorithms proposed by the authors are guaranteed to find the optimal set of tiles that "best" construct the surfaces on the basis of specified objective criteria. The algorithms are illustrated by applications to a complex silver/gold/zinc/lead deposit.

Jan 1, 2002

By Alessandro Navarra, Roberto Parra, Boyd Davis, Frank Mucciardi

A smelter scheduling algorithm has been developed, which allocates the oxygen production between the smelting furnace and the converter aisle, so as to maximize copper throughput. The algorithm is intended for daily operation planning, controlling the sequencing of the converter cycles, and the oxygen drawn by these cycles. In some cases, it may be worthwhile to decrease converter oxygen allocation in favour of the smelting furnaces. Thus, a better utilization of the oxygen plant can increase primary copper throughput by several percentage points. This principle is demonstrated through sample computations. The approach presented in this paper can be incorporated into smelter management software.

Jan 1, 2015

By G. ALBORNOZ, S. Utili, A. AGOSTI, C. VALDERRAMA, R. PELL, N. Morales

The steepness of the slopes of an open pit mine has a substantial influence on the financial return of the mine. The paper proposes a novel design methodology where overall steeper pitwalls are employed without compromising the safety of the mine. In current design practice, pitwall profiles are often planar in cross-section within each rock layer; i.e., the profile inclination across each layer tends to be constant. Here instead, a new geotechnical software, OptimalSlope, is employed to determine optimal pitwall profiles of depth varying inclination. OptimalSlope seeks the solution of a mathematical optimization problem where the overall steepness of the pitwall, from crest to toe, is maximized for an assigned lithology, geotechnical properties, and factor of safety (FoS). Bench geometries (bench height, face inclination, minimum berm width) are imposed in the optimization as constraints which bind the maximum local inclination of the sought optimal profile together with any other constraints such as geological discontinuities that may influence slope failure. The obtained optimal profiles are always steeper than their planar counterparts (i.e., the planar profiles exhibiting the same FoS) up to 8° depending on rock type and severity of constraints on local inclinations. The design of a copper mine is first carried out employing planar pitwalls, secondly adopting the optimal pitwall profiles determined by OptimalSlope. The adoption of optimal slope profiles leads to a 34% higher net present value and reductions of carbon footprint and energy consumption of 0.17 Mt CO2 eq and 82.5 million MJ respectively due to a 15% reduction of rockwaste volume.

Feb 9, 2022

By G. ALBORNOZ, S. Utili, A. AGOSTI, C. VALDERRAMA, R. PELL, N. Morales

The steepness of the slopes of an open pit mine has a substantial influence on the financial return of the mine. The paper proposes a novel design methodology where overall steeper pitwalls are employed without compromising the safety of the mine. In current design practice pitwall profiles are often planar in crosssection and the profile in between ramps especially tend to be planar and defined by a constant inter-ramp angle. Sometimes rock layers exhibiting different strengths require the inclination of the profile to vary with depth, but the inclination across each layer is usually constant. Here instead, a new geotechnical software, OptimalSlope, is employed to determine optimal pitwall profiles of depth varying inclination. OptimalSlope seeks the solution of a mathematical optimization problem where the overall steepness of the pitwall, from crest to toe, is maximized for an assigned lithology, geotechnical properties and Factor of Safety (FoS). Bench geometries (bench height, face inclination, minimum berm width) are imposed in the optimization as constraints which bind the maximum local inclination of the sought optimal profile together with any other constraints such as geological discontinuities that may influence slope failure. The obtained optimal profiles are always steeper than their planar counterparts (i.e. the planar profiles exhibiting the same FoS) up to 8 degrees depending on rock type and severity of constraints on local inclinations. The design of a copper mine is first carried out employing planar pitwalls, secondly adopting the optimal pitwall profiles determined by OptimalSlope. The adoption of optimal slope profiles leads to a 34% higher net present value and reductions of carbon footprint and energy consumption of 0.17 Mt CO2 eq and 82.5 million MJ respectively due to a 15% reduction of rockwaste volume.

Mar 2, 2022

By G. ALBORNOZ, S. Utili, A. AGOSTI, C. VALDERRAMA, R. PELL

The steepness of an openpit mine’s slopes has a substantial influence on the mine’s financial return. This paper proposes a novel design methodology where overall steeper pitwalls are employed without compromising the safety of the mine. In current design practice, pitwall profiles are often planar in cross section within each rock layer: that is, the profile inclination across each layer tends to be constant. Here, instead, a new geotechnical software, OptimalSlope, is used to determine optimal pitwall profiles of depth-varying inclination. OptimalSlope seeks the solution of a mathematical optimization problem where the overall steepness of the pitwall, from crest to toe, is maximized for an assigned lithology, geotechnical properties and factor of safety (FoS).

By I. V. Lunkin, E. B. Muhamedzhanov, A. B. Begalinov, B. R. Rakishev

Almost all the ore deposits of ferrous, non-ferrous and rare metals of Kazakstan, are exploiting by the open-cast method, are the complex-structural, multi-component ones. Their rational working requires precise organization of extracting works. In this connection it is necessary to set up the best intercommunications between drilling-blasting, excavating-loading and transport works. This requires the stable functioning of the quarry for dispatch of ore raw material of required quality with minimum of corresponding expenses. For this purpose, proceeding from the quarry’s ore output and the assumed parameters of the exploitation system, the first problem about rational arrangement of excavating-loading equipment in extracting faces is solved. By solving the problem the model with dynamic, adapting properties had been used. It was solved numerically by the method of statistical tests. By setting up the necessary link between type-sizes of excavating-loading and transport equipment, the minimum prime cost of loading and transportation of 1 ton of mining mass from the face to the receiving station was adopted as the criterion of optimality. Depending on the type of excavating-loading equipment, the efficiency function may be different. By using wheel loaders, their displacement between the faces is possible, therefore, the efficiency function of the problem may include expenses for their displacement. By using excavators like power shovel, the problem’s restrictions must exclude its displacement between the faces. The efficiency function consists of minimum expenses for loading, proceeding from set of volumes of extraction from the faces, satisfying required quality. The volumes of extraction from the faces, satisfying required quality of ore in output stream, are determined by the method of statistical tests. Sample range is given, proceeding from the restrictions for maximum productivity of the excavating-loading equipment. Volumes of extraction, not satisfying required quality, are cut off. The efficiency function meaning is then determined and minimized. Keywords: Excavating-loading equipment, its placing in extracting faces, optimal load-carrying capacity, specific expenses for loading and transportation of mining mass.

Jan 1, 2003