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By G. A. Bezuidenhout

Lonmin Platinum installed a concentrated mode dual-alkali scrubber at the smelter in Marikana in 2002. The dual-alkali scrubber was the technology of choice at that time as a sulphur fixation plant, due to the perceived benefits of handling both the high SO2 concentrations of converter off-gas and the swings in SO2 concentration that are linked to Peirce-Smith operation. Owing to current and impending legislative requirements for air quality and waste, Lonmin is currently considering additions to the dual-alkali plant, but is also evaluating alternative technologies for sulphur fixation. This paper reviews the decision of Lonmin to install a concentrated mode dual-alkali scrubber and presents plant performance achieved. It also describes the important control variables and sensitivities of the plant, and the final product that is produced by the operation of the plant. The legislative requirement that drives the Lonmin technology evaluation is also discussed.

Jan 1, 2012

By G. A. Bezuidenhout

Lonmin Platinum installed a concentrated mode dual-alkali scrubber at the smelter in Marikana in 2002. The dual-alkali scrubber was the technology of choice at that time as a sulphur fixation plant, due to the perceived benefits of handling both the high SO2 concentrations of converter off-gas and the swings in SO2 concentration that are linked to Peirce-Smith operation. Owing to current and impending legislative requirements for air quality and waste, Lonmin is currently considering additions to the dual-alkali plant, but is also evaluating alternative technologies for sulphur fixation. This paper reviews the decision of Lonmin to install a concentrated mode dual-alkali scrubber and presents plant performance achieved. It also describes the important control variables and sensitivities of the plant, and the final product that is produced by the operation of the plant. The legislative requirement that drives the Lonmin technology evaluation is also discussed.

Jan 1, 2012

By S. Kirkpatrick, J. Mukendwa

"The mining operation at Namdeb’s Southern Coastal Mine (SCM) is unique. It targets gravel layers up to 30 m below sea level, which continue to dip deeper, further west, under the Atlantic Ocean. On this storm-dominated coastline, severe water seepage into mining areas, rugged orebody footwall characteristics, and highly variable resource grades all contribute to a challenging operational environment. Namdeb has a proud history of innovation, and as the mine progresses further westwards and associated technical and economic challenges increase, this innovative culture has become essential to the future of the mine. The Theory of Constraints (ToC) has been widely used at SCM, and across the mining discipline, to focus efforts on improving overall business profitability. Through analysis of the mining processes, opportunities were identified, solutions developed, and initiatives implemented with staggering results across all three mining disciplines, i.e. stripping, load and haul, and bedrock bulking and cleaning. This paper outlines the solutions adopted and the results of the ToC analysis. IntroductionSouthern Coastal Mine (SCM) is one of three Namdeb operations located in the southwestern corner of Namibia, between the Orange River in the south, the Namib Desert to the east and the Atlantic Ocean to the west (Figure 1). These three geographical features set the backdrop for the world’s greatest marine diamond mining placer (Badenhorst, 2003). SCM is situated along the coastline extending from the mouth of the Orange River to Chameis Bay approximately 120 km to the north. The active mining area, called Mining Area 1 (MA1) is, however, limited to very narrow strip, 30 km in length, in the south of the licence area, close to the town of Oranjemund.Namdeb, a wholly owned subsidiary of Namdeb Holdings, is a 50/50 joint venture between De Beers and the Government of Namibia. Diamonds were first discovered along the Namibian coastline in April 1908, close to the town of Luderitz, but mining operations started in the SCM mining area only in February 1929 (Schneider, 2009). Initially all Namdeb mining operations exploited massive land-based deposits, producing nearly 40 million carats from MA1 between 1920 and 1977 (Schneider, 2009) when mining targeted onshore raised beaches west of the high water line. Since 1977 however, SCM and Namdeb have developed a unique mining method to economically extract the resource which extends westward under the Atlantic Ocean."

Feb 1, 2019

By J. T. Collins, C. J. Cloete

Secunda Collieries forms part of Sasol Coal, the coal division of the Sasol Group of companies, and already produces 29 Mt of coal per annum from its four collieries: Twistdraai, Brandspruit, Bosjesspruit, and Middelbult. The successful establishment of this mining complex was achieved only through a unique team spirit in which the central services and the decentralized teams under the leadership of the mine management of each of the four mines played an important role. The Secunda mining complex has now reached the optimization phase, during which the mining cost, productivity, safety, and quality of work become as important as production. The setting of priorities and problem solving over the long, medium, and short term are essential for improving the performance of the four collieries. Management had to adapt to the fast-changing environment during the enormously fast build-up of production. The major challenges in the environment were posed by the frequent dolerite intrusions, the extremely hard cutting conditions caused by carbonated nodules and thin sandstone intrusions in the coal seam, and excessive roof and face pressure in some areas due to semi-massive sandstone formations in the rock strata.

Jan 1, 1986

"Chairman: Dr N. G. W. Cook Rapporteur: Mr M. P. RobertsPapers:Planning open pit mining operations using simulation by A. Bauer and P. N. Calder Simulation for control of underground liquid flow by G. N. Pitts and P. B. CrawfordEvaluation of production strategies in a group of copper mines by linear programming by P. H. Williams, J. N. Brooke and D. M. PoulterAn equipment maintenance system by D. W. Dean and J. A. RyderTaken as a whole, the difference between the four papers in this session were perhaps more illuminating than their similarities. The titles of the first and second papers contained the word 'simulation', and in both papers random number generation was relied upon in the selection of inputs from empirical distributions, but the nature of the models to which these values were inputs were quite different. The third paper displayed another method of uniting the empirical and the theoretical in a linear programming formulation whose matrix coefficients were measured empirically, and here some apt remarks on computer implementation were included. This paved the way for the last paper which abandoned all theoretical pretensions in favour of a detailed description of computer implementation and perhaps as a result gave rise to the most feeling audience participation.The systems mentioned were developed for the iron, petrol, copper and gold producing industries in the US, Canada, Zambia and South Africa..As with all the parallel sessions, contributions from the floor may have been limited by the shorter time available to delegates to acquaint themselves with the papers before the session. In spite of this, and due largely to the active chairman¬ship of Dr Cook, the discussion during the session which is summarized here contributed much to the information contained in the papers themselves.In his presentation, Dr Calder summarized his paper. He expected that simulation would be used in future on an almost universal basis in open pit mining. It could contribute new knowledge more cheaply than experimentation in the flea For example, this study had shown what was previously thought to be a matter of more shovels and trucks was really a blasting problem, and improving blasting had increased production to the desired level. The simulation had shown that uniformity of truck performance was a desirable factor. It had also been used to study the advisability of a dispatching system.Dr Ramani contended that where equipment characteristics were available, deterministic standard simulation could adequately simulate systems in which interference occurred. Operator performance could be measured against perfor¬mance curves predicted by standard simulation and poor operators spotted and retrained. The present system did not take into account variability in truck loading, for instance. Dr Calder replied that if the number of variables was large, the standard approach became too complicated for operating personnel to follow. He admitted he had not tried it. The variability of truck loading could be coped with easily using the Monte Carlo approach. Operator variability was already incorporated because the time studies are actual."

Jan 1, 2014

By M. Getz, G. Asbjörnsson, M. Evertsson, E. Clausen

The mining and minerals processing industry is gradually being digitalised to improve efficiency and reduce waste. One aspect of this transition is to ensure that relevant process-data in sufficient quality and quantity is given to the operator in the right format and at the right time to improve decision-making. Augmented reality (AR) can serve as a potential ICT-based support tool for human operators to achieve this goal. With AR, virtual information is combined with the real world in real-time. Therefore, AR technology has the potential to fulfil the need for improved data visualisation in Industry 4.0. This article is the result of a collaborative effort of Chalmers University of Technology and RWTH Aachen University to identify selected state-of-the-art applications of AR that are currently being applied in the mining and minerals industry or selected related industries. This paper aims to show opportunities for the application of AR in the mining and mineral processing industry with selected conceptual applications. This paper concludes with several requirements identified as necessary to implement the conceptual applications of AR in the mining and minerals industry. Keywords: Augmented reality, mining, mineral processing

Jan 1, 2020

By Jeremy Bosman, Johan de Korte

Traditionally the feed to coal preparation plants was de-slimed at 0,5 mm. The +0,5 mm size fraction was processed via dense-medium cyclones and the -0,5 mm size fraction was beneficiated with froth flotation, water-only cyclones or spirals. With the introduction of large diameter cyclones, the aperture sizes of de-sliming screens have progressively increased to about 3 mm in the belief that the larger cyclones are not able to effectively beneficiate coal which has a particle size below the ?breakaway? size. The efficiency of separation in the large dense-medium cyclones is improved by presenting a coarser feed to the units. At the same time, the capacity of the de-sliming screens is increased due to the larger screen apertures and in effect, the throughput capacity of the dense-medium section is increased. The 3 x 0,5 mm size fraction, which was previously processed in the dense-medium cyclones, is now added to the fine coal size fraction and processed by water-only methods such as Teetered Bed Separators (TBS) and spirals. Whether this practice is the most economical way to process the 3 x 0,5 mm size fraction requires further thought since the best processing route for the 3 x 0,5 mm size fraction will depend on a number of factors, amongst which are: o The washability of the coal and the amount of near-density material o Processing efficiency o Specification of the required product o The price paid by the customer for the product o The cost of processing the coal Breakaway size The ?breakaway? size is defined as the particle size below which the Epm of the smaller particles starts to decrease significantly. Bosman1 provides an approximate breakaway size versus cyclone diameter (Figure 1). It should be kept in mind though that the Epm of the small particles is a function not only of the cyclone diameter but also of feed pressure, medium density, medium viscosity, particle shape and density, top-size of particles in the feed, etc.

Jan 1, 2006

By J. Abdollahisharif

Optimal cut-off grade is one of the most critical parameters in open-pit mine design because it defines the ore and waste and thus determines the maximum net present value possible from the mining operation. Although the algorithm presented by Lane (Choosing the optimum cut-off grade. Colorado school of Mines Quarterly, vol. 59, no. 4, 1964. pp. 811-829) is the most common one in the literature, it does assume constant capacities of the mine, processing, and refinery. In this paper, Lane's original algorithm has been modified to consider variable processing capacities in order to determine the optimal cut-off grade in open-pit mines. The new algorithm proposed here is compared to both Lane's original algorithm and to a previous modification that incorporated rehabilitation costs into the cut-off grade estimation. The algorithm proposed here that permits variable processing capacities is shown to be superior for the determination of optimal cut-off grade to both these previous versions. In addition, a computer-based program was developed in Microsoft Office Excel© to calculate the optimal cut-off grade as proposed here.

Jan 1, 2012

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

[Consider a square block W in an ore body S2, to be valued from one centre sample w, and one corner sample w2 (Fig. 9.1). The sample set is ws = Iw,;w21. We can estimate the block average µw by the average of the sample values x, and x2: µw = 'z (x, + xz). (9.1) The error made is measured by the estimation variance: o' (ws to W) = 2 - (ws; W) - - (ws;ws) - - (W; W). (9.2) However, we know that the centre sample w, gives more information about the block value than the corner sample w2. In the example studied in § 8.4, where w, and w2 were considered to be points, we found that of (w, to W) was nearly one third smaller than o2E (w2 to W), therefore when estimating W one should give more weight to w, than to w2. In general, when evaluating a block W from a set of n samples ws, where WS = l w;w2; ... wn1, a better estimator of µw can be obtained if we give different weights to the sample values, depending on the size and the positions of the samples. Some desirable properties of such an estimator µw are: ? It should be a linear function of the sample values xi: n µw = bi xi (9.3) =t where bi = weight given to sample x . ? It should be unbiased, i.e. its expected value should be equal to the true block value: E [µw - µw] = 0. (9.4) ? The mean squared error of estimation of µw should be a minimum E [(µw - µw)2] = a minimum. (9.5) The estimator which satisfies these properties is a minimum variance, linear and unbiased estimator, and is known as the kriging estimator. The corresponding error of estimation is the kriging error. This estimator is also known as the BLUE (for Best Linear Unbiased Estimator) estimator. This was named by Matheron in acknowledgement of the early work of Krige's in the optimization of the evaluation of the South African gold mines. The following notations will be used: µK kriging estimator. o2k = o2K (w,, to W) kriging error.]

Jan 1, 1978

In many practical situations, calculation of the point semivariogram is not necessary. Such a case is analysed in this chapter. The purpose of this analysis is to give a better understanding of the meaning of the mathematical formulae developed in the previous chapters. A similar problem will be studied in Chapter 11, using the point semivariogram.

Jan 1, 1978

By T. Puhakka

Simulation is a way to obtain quickly today future information on how planned systems will most likely behave in various selected situations. This information may then be used to optimize the system and its components and maximize the performance and output. Simulation is a way to fine-tune the layout, match the mobile fleet and optimize the schedule and the way of working to meet the desired production requirements. Simulation provides a glimpse of the upcoming operation, ‘future today’ and helps to predict its restrictions and sensitivity to various aspects. OptiMine™, the Sandvik Tamrock Corp. and CyberCube Oy developed simulation tool is designed to simulate underground rock flow and match suitable technology with various layout options. This tool can be used to view what-if situations and determine what kind of impact mastered changes have to production. The findings of critical points in the layout and working procedures at an early stage of a new mine can help to optimize the layout and material flow. OptiMine™is modular based simulation tool that combines the supplier machine knowledge and traffic guidance with mine operational know-how and mine environment. It is developed to work in a way that an effect of an individual incident, such as the effect of one additional turn in a continuous loading cycle to the daily capacity can be identified. The reported output can be used for economical impact evaluation of selected options. This paper discusses the use of simulation in general and the way the OptiMine™ simulation tool operates and how it may be used for operation, technology and material flow optimization.

Sep 1, 2001

By B. Mbuya, A. F. Mulaba-Bafubianda, J. M. Mvita

The paper explains the main effects of input leaching parameters, such as addition of a reducing agent, acidity, agitation, temperature, and leaching system potential, in relation to observed and predicted yields of sought-after cobalt. An artificial neural network coupled with graphical probability networks was developed wherein the abovementioned input parameters were used to predict the percentage of dissolved cobalt. Furthermore, similarities and differences between the Bayesian and neural network approaches in terms of their key outcomes are compared with respect to study of the dissolution of cobalt in sulfuric acid. Key results indicate that there is a need to use neural network results to predict conditions for dissolution of cobalt, while using Bayesian network to explain inferences about conditions of the input parameters, thereby achieving realistic predictions.

Jan 1, 2023

By M. K. Sichone

Anglo Platinum?s Waterval smelting complex based in South Africa operates the Anglo Converting Process (ACP) that produces SO2 offgas. This SO2 offgas is treated in a double-contact, double-absorption acid plant allowing for conversion efficiencies higher than 99.90 %. The catalytic converter used in the acid plant to convert the SO2 to SO3 is a 4-bed reactor loaded with a combination of cesium-promoted and conventional vanadium pentoxide catalysts. In June 2008 there was a shutdown, in which one of the main activities was to screen the catalyst. Before this shutdown, the operator would control the converter pass temperatures manually, via the SCADA, especially during plant start-ups after which some of the automatic temperature controllers were used. After the shutdown, the control philosophy was revisited and all temperature controllers were put on auto mode during plant start up. Furthermore the set points of the pass inlet temperatures were reduced to maximize conversion in the first two passes. The result has been a reduction of SO2 emissions, from a daily average of 50 ? 70 ppm to as low as 20 ppm for similar sulphur dioxide and oxygen concentrations. Further work has been done to maintain high bed temperatures in the third and fourth passes at low SO2 strengths by splitting the gas stream between pass 1 and 2 thus increasing the SO2 content in the gas to pass 2. This increases the temperature of the gas exiting the second pass, which results in higher temperatures in passes 3 and 4. Comparison of the converter performance prior to and after the changes is made. The benefits of partially bypassing the first pass to increase the SO2 content in the gas to the second pass are shown. Conclusions and scope for further work have been drawn from the comparisons.

Jan 1, 2009

By Fadeela Saloojee, Frank K. Crundwell

"Pressure leaching is an option for copper recovery from chalcopyrite. Leaching takes place at high temperatures and pressures in the presence of an oxidising agent. This work shows how the performance of pressure leaching circuits may be improved by optimising the configuration of autoclaves and the heat-removal method. The objective was achieved by creating an autoclave model by combining mass balances, energy balances and population balances. A base-case circuit consisting of a single autoclave was chosen, and this base case was compared with options for increasing capacity by adding more autoclaves to the circuit. These capacity–increase options include circuits in which the additional autoclave is added in parallel, in series and in series with thickening between the two autoclaves. The copper extraction, productivity and cooling requirements for these options are compared. The series circuit with inter-stage thickening has the highest extraction and productivity, however, the cooling duty in the first autoclave is high. In addition to comparing circuit options, three options for heat removal were investigated: cooling coils, quench water and flash recycling. The flash-recycle option results in the highest copper extraction, and the quench-water option gives the lowest copper extraction. INTRODUCTION Background Copper sulfide ores and concentrates containing chalcopyrite are typically hard to leach under atmospheric conditions. Smelting of these ores may also be a challenge, due to the inability of smelting processes to handle low-grade ores, as well as impurities such as arsenic and antimony. Alternative hydrometallurgical routes to treating chalcopyrite are therefore required. One option is pressure leaching, which is the focus of this work. In the pressure leaching process, sulfide ores and concentrates are leached in autoclaves at temperatures of 200 to 220°C and a pressure of about 3000 kPa (Schlesinger et al., 2011). An oxidising agent, usually oxygen, is required to oxidise sulfide ions to sulfate ions. The oxidation of sulfur to sulfate is exothermic; consequently, a method of heat removal is necessary in order to maintain the temperature in the autoclave."

Jan 1, 2015

Two column flotation cells have been installed as single-stage rougher cleaners at Batu Hijau. The objective was to provide additional residence time in the cleaner circuit to maintain maximum recovery during high mill throughput and high feed grade periods. Installation of the columns has allowed the relatively coarse, well-liberated rougher concentrate and the relatively fine, low-grade scavenger concentrate to be treated separately, improving metallurgical performance in the cleaner circuit. Plant results show that the columns produce a high-grade concentrate at an average stage copper recovery of approximately 80 per cent. There is also indication of increases in both overall plant copper recovery and final concentrate copper grade. In addition, the operability and stability of the cleaner circuit has greatly improved.

Jan 1, 2007

By Z. Saw, C. Poveda, N. L. Mai

Optimising the throughput of a mining network comprising all equipment from shovels to semi-autogenous grinding (SAG) mills is a complicated task, yet the potential benefits can be significant. Key modelling challenges stem from the sheer number of possible routes which material can travel, different equipment operating under different constraints, and the rate of SAG mills being calculated through a nonlinear function of the blended materials’ rock attributes. Nevertheless, this is an ideal onapplication area of mathematical programming, a branch of operations research. This paper describes an application of mixed integer linear programming (MILP) to optimise the mining equipment network of one of the world’s largest copper mines.The model takes as input a year-long monthly mine schedule of shovels in different pits, pushbacks, sequences and faces which produce material to be moved through a network of crushers, conveyors, silos, distributors, stockpiles and SAG mills, ultimately outputting a daily operational plan for all equipment that maximises the throughput of the network. All operational constraints and business rules are considered, including three quality attributes of copper ore. Comparing model results with actual data shows an improvement of 4.47% in network throughput tonnage. Additionally, although the model is solved using a free, open-source solver, optimal solutions are still achieved within a practical timeframe.

Sep 1, 2021

By J. Griesel, P. H. F. Bouwer, K. Bisaka

Transalloys produces 160 000 tons of SiMn per annum from five AC submerged-arc furnaces. The lime-ore melt from two AC open-arc furnaces is contacted with SiMn to produce 50 000 tons of medium carbon FeMn per annum. Metallics in the slag are reclaimed in a jigging plant, which has been in operation since 1999. The flow of materials between the jigging plant and furnaces has been optimised. The amount of recycle slag in the feed of the SiMn furnaces has been decreased by more than 30% which still provides satisfactory stability of the furnace operation. The jigging plant has absorbed all the additional slag generated, to recover SiMn metal. A review of the raw materials used and operating parameters for SiMn production was also undertaken. Slag to metal ratios were decreased by more than 30% by reducing the slag recycle, removing magnesite from the recipe and introducing high-grade ore. Electrode penetration was improved by reducing coke levels and by utilising more reactive coal. The pitch circle diameter (PCD) was reduced to get a better operating stability on furnace no 5 using the MINSTRAL Control System. Energy consumption on the furnaces improved by more than 15% while SiMn production increased as a result by more than 18%.

Jan 1, 2004

By S. Ranganathan

Production of ferro-chromium in the submerged-arc furnace is highly energy-intensive. Several process rates have been attempted to reduce the specific energy consumption in the production of this alloy. An exhaustive understanding of the thermo-chemical features of the production process can be used to reduce the specific power consumption significantly. The knowledge can be used to reduce the energy drain through undesired reactions in the process can be minimised. Plant trials have shown that specific energy consumption up to 100kWh/tonne of hot metal can be obtained by adopting this strategy. The process requires modification in operation practice and does not require any capital investment unlike other processes adopted for reducing power consumption. The principle of thermo-chemistry involved in this process development and results of plant trials are discussed in detail.

Jan 1, 2007

By P. Ramsaywok, S Ndanduleni, G. Legodi

The objective of this paper is to share the optimisation journey of a pilot Reflux classifier (RC) circuit in the Exxaro GG1 plant, at Grootegeluk beneficiation complex in Lephalale, South Africa. The RC circuit was commissioned in 2016 to produce semi-soft coking coal at its fines circuit; however the stability of operation as well as the quality control of the coal product was not fully achieved. Various test campaigns and optimisation studies were conducted to understand and optimise the RC circuit at GG1. The studies revealed circuit design inefficiencies; provided an improved technical understanding of the current pilot circuit and the parameters required for the circuit to reach a stable operation. The operation was stabilised with its current inefficiencies to produce an average 12.5% ash semi-soft coking coal product for sustained periods, above the initial target of 10.3% ash. Keywords: Reflux classifier, coal

Jan 1, 2020