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By S. Adams, J. R. C. von Holdt, J. L. Broadhurst

Fugitive dust from mineral extraction and processing activities can significantly influence air quality, the environment, and the health and quality of life of workers and surrounding communities. Poor engagement and communication between experts and lay persons, disciplinary silos and polarised viewpoints have made it difficult to develop a holistic understanding of the complex health issues associated with environmental emissions of mine dusts, and consequently to design meaningful and integrated approaches to address such issues. The collaborative Global Challenges Research Fund (GCRF) Mine Dust and Health Network, hosted by Minerals to Metals at the University of Cape Town, serves as a collaborative think-tank to inform research directions within and across disciplines, government policy and regulations, health monitoring programmes at public clinics, industry best practice, community healthcare and impact prevention programmes. It focuses initially on the southern African region, but with the intention to expand to mining-intensive developing countries within the rest of Africa, South America and Asia. This paper outlines the approach and activities of this global transdisciplinary and intersectoral network and presents some of the key outputs and achievements to date. Keywords: Mine dust, Global Challenges Research Fund Mine Dust and Health Network

Jan 1, 2020

By T. P. Letsebe, L. Magwaza, T. A. Sethu, S. M. Rupprecht

"The authors were tasked with introducing safe and efficient drilling and blasting practices to a small artisanal mine located in the Eastern Province of Rwanda. The current mining methods employed at the mine are inefficient as rockbreaking is conducted utilizing hammer and chisel, or by drilling and blasting with no understanding of the rockbreaking process. The paper discusses the drill and blast cycle, as well as the associated activities necessary to support the mining cycle. The challenges and critical aspects in implementing drill and blast activities are discussed, as well as some of the technical aspects, i.e.drilling pattern, initiation and timing of the blast, and handling of misfires. Ancillary issues such as ventilation, training, communication, effective planning, logistics, and human relations are also examined. IntroductionRockbreaking accounts for 60% of the direct mining costs in small-scale mining. When drilling and blasting practices are poorly implemented the process becomes inefficient and dangerous. The introduction of a proven drill and blast system to artisanal mining offers a number of challenges, with safety being considered the backbone of any sustainable operation and a standard that cannot be compromised.The paper is based on a project at an artisanal cassiterite (tin) mining operation in a small village in the Kayonza District in the Eastern Province of Rwanda. A drill and blast programme utilizing industry best practice was introduced at an underground development end; a raise developed at an inclination of 23 degrees. The underground working is accessed via a 17 degree incline shaft with an operating length of 105 m and serviced by a single drum winder. The winder operates at a speed of about 3.5 m/min hoisting two 1 t wagons from the bottom of the incline to surface for tipping (Figure 1)."

Jan 1, 2017

By S. Sinha, S. Ganguly

"In an opencast mine explosives are used for fragmentation of rock. Inefficient use of explosive energy in an opencast operation produces excessive ground vibration, which is measured by peak particle velocity (PPV). To mitigate ground vibration, it is essential to develop a model to predict PPV. At present empirical models are used. These models are based on only a few input variables, hence they fail to take into account the effects of the myriad factors that cause ground vibration. Due to lack of explicit knowledge about the complex mine blasting system the scope of application of mathematical and statistical modeling techniques is limited. The artificial neural network (ANN) technique is a learning algorithm that can remove some of these limitations and can be applied to predict PPV. In this paper an ANN model is developed for prediction of blast vibration using 248 data records collected from three coal mines with diverse geomining conditions. The correlation coefficient between measured PPV and model output was found to be 0.96 and the average error percentage 11.85. The ANN model output was compared with the output of three empirical models that are widely used for prediction of PPV. The correlation coefficient between the PPV predicted by an empirical model and measured PPV data was 0.63 and the relative error percentage 38.47. This result demonstrates the superiority of the ANN model compared to empirical blast models. By using site-specific structural discontinuities as input the model performance can be further improved. Sensitivity analysis and 3D plotting were used to gain further knowledge about blast-induced ground vibration. IntroductionIn an opencast coal mine explosives are used for fragmentation of coal and overburden. If the explosive energy is not fully utilized it causes blast-induced ground vibration, which may damage nearby structures. Ground vibration is expressed as peak particle velocity (PPV). During different stages of mine planning and operation, it is necessary to use a ground vibration prediction model for blasthole design. Selection of the modelling technique is crucial. Mathematical and statistical modelling techniques have limited application because of the lack of explicit knowledge about the complex mine blasting system. Vogiatzi (2002) highlighted the problem of multicollinearity in case of statistical modeling techniques. Mutalib et al. (2013) stated that mathematical models are unable to capture the nonlinear relationship between several blasting-related parameters due to the complexity of the model input data. However, the difficulty involved in modelling complex blast vibration problems can be removed by adopting an alternative soft computing modelling approach. One of the soft computing techniques is the artificial neural network (ANN). Ragam and Nimaje (2018) developed an ANN model for predicting PPV using six input variables. Kosti et al. (2013) stated that the conventional predictors fail to provide acceptable prediction accuracy. They showed that a neural network model with four mine blast parameters as input could make significantly more accurate on-site predictions. Sayadi et al., (2013), using a database from Teheran Cement Company limestone mines, found that a neural network resulted in maximum accuracy and minimum error. Khandelwal and Singh (2009) developed an ANN model using 150 data records from an Indian coal mine with site-specific rock characteristics and geomining setting. Khandewal and Singh (2007) built a ground vibration prediction model for a magnesite mine using four prediction variables with 20 data records. Kamali and Ataei (2010) predicted PPV in the structure of the Karoun III power plant and dam using an ANN. El Hafiz et al. (2010) evaluated ground vibration predictors using data from a single-station seismograph at a limestone quarry in Egypt."

Feb 1, 2019

By S. T. L. Harrison, M. A. Fagan-Endres, M. D. Odidi

This paper investigated the ability of eight common hydrodynamic models – tanks in series (TIS); three compartmental model configurations (Comp-1, Comp-2 and Comp-3); advection dispersion (AD); piston exchange (PE); piston exchange-diffusion variant (PE-D) and piston dispersion exchange (PDE) – to simulate residence time distribution (RTD) data generated from tracer tests conducted on a packed bed composed of different size fractions of malachite ore. The chosen materials were packed into 0.1 m internal diameter columns to a depth of 0.155 m and drip irrigated at 5.11 L/ m2.h. The four size fractions tested were: 1 – 2 mm, 2 – 2.8 mm, 4.75 – 5.6 mm and 13.6 – 16 mm. Step-up tracer tests were conducted using potassium chloride. The results showed that an increase in the particle size of the malachite ore had little effect on overall bed porosity but resulted in significantly lower values of liquid holdup. Two of the monoporosity models tested, TIS and Comp-2, were the most affected by the changes in bed size fraction due to their inherent inability to cope with high degrees of non-ideal flow present in the larger particle systems. The dual porosity models performed relatively better with the dominant trend being a reduction in dynamic to total liquid holdup as particle size increased. Of all the models tested, the PDE and TIS models were the best and worst performers respectively, with R2 values averaging at 0.997 and 0.679 across all experiments respectively. Though the Comp-1, Comp-3 and PE-D models also performed well, the addition of the dispersion coefficient to take the axial spread of fluid molecules into account added a layer of complexity that allowed the PDE model to perform relatively better than the other dual porosity models. Keywords: Heap leaching, packing material, hydrodynamics, malachite, PSD, modelling

Jan 1, 2020

By Pieter de Waal

The beneficiation equipment under the control of plant metallurgists exploits the differences in the physical properties between valuable and waste mineral components. In many cases, laboratory results are too late for process control and can only serve the purpose of "post" reports, the calculation of a mass balance and the issue of a quality certificate. As a result, experienced operators regularly adjust separation equipment based on the colour and texture of the various product streams in the beneficiation plant. Metallurgists quickly learn to recognise the different minerals in their ore body. The stereo microscope has been a valuable tool used by operators to quantify known mineral species. For many years it was the only practical method available for the purpose of process control and even for quality contro1. The modem spectroscope is far superior to the human eye and can rapidly detect a change in mineral composition. New generation optical scanners and digital signal processors can provide useful signals, related to mineral composition that can readily be applied for the purpose of process control. Successful case studies, covering dry in-line and slurry applications as well as in-plant fast spot analysers are presented.

Jan 1, 2014

By R. D. Alorro, B. Tadesse, E. Aghaei

Cinnabar (HgS) and native mercury (Hg) are the most common naturally occurring forms of mercury found in most gold ores subsequently released into the environment during processing. Mercury and its compounds are extremely toxic and recognised as serious health and environmental hazards. This research investigates the possibility of mercury (Hg) removal from waste solutions from gold processing using iron-aluminium (Fe-Al) bimetallic particles. The synthesis of Fe-Al bimetallic particles using zero-valent aluminium and ferric chloride as precursors were performed following the optimisation of influencing factors. The presence of both metals in the prepared bimetals was confirmed by XRD analysis. The experiments for mercury removal by bimetals were designed using the central composite design and Minitab software based on two variables including contact time and adsorbent dosage. The best result of Hg(II) removal (>90%) was achieved using 4 g/L bimetals and contact time of 75 min. However, the statistical analysis of results indicated that these parameters have only a minor contribution to the removal of Hg(II) by Fe-Al bimetals. Higher bimetal dosage and contact time resulted in a higher Fe dissolution from the Al surface which can be attributed to the presence of nitrate (# $) ions in the solution. However, adding 0.1 M NaCl to the Hg solution had a positive impact on Hg removal by improving the conductivity and electron transfer within the solution. The Fe-Al bimetallic particles are promising substances for further testing of Hg removal from gold processing waste solutions with different conditions and constituents. Keywords: Mercury removal, gold processing, Fe-Al bimetals, optimisation

Jan 1, 2020

By D White, L. Lorenzen

Sampling and metallurgical testwork during various phases of engineering studies is of paramount importance for a robust processing plant design. When developing a process flowsheet, risks in achieving desirable financial outcomes are minimised by ensuring that appropriate sampling and adequate metallurgical testwork support the engineering and cost estimation at each phase of project development. The quality and type of samples used for metallurgical testwork are just as important as the metallurgical testwork itself. The key characteristic required of any sample is that it represents some defined portion of a mineral deposit. Representivity should consider the spatial orientation, lithology, alteration, degree of oxidation, mineralogy, and competency of the ore such as hardness and abrasiveness. Statistically representative sampling procedures and an appropriate metallurgical testwork program should be designed to bring metallurgical understanding up to feasibility study standard and to give a basis for process plant design. The authors have observed that the quality of sampling and quantity of metallurgical testwork carried out during the various phases of engineering studies are often insufficient to truly support a robust plant design. Some designs are based on benchmarks of apparently similar ore bodies or rely on buoyant metal prices supporting cash flows until rectifications can be implemented. The paper will discuss important aspects of sampling and testwork required for engineering studies in designing process plants. Keywords: Sampling, metallurgical testwork, studies, design

Jan 1, 2020

By R. McGregor

You wouldn't start excavating before testing core samples, so why would you approve a project plan before all factors have been identified, reviewed and addressed? Even a champion sports team made up of the best players can't produce optimal results without a well understood and agreed game plan. Could an F1 racing team produce their outstanding performance without rigorous evaluation and testing of the factors for successful performance? Why would we expect a capital works project team to be able to get it right without an understanding and an involvement in setting and implementing the overall game plan and without an understanding of all stakeholder requirements? For International Power's Hazelwood (IPRH) mine in Victoria, the challenge was development and delivery of a 40 year mine plan, ultimately involving relocation of existing mine operations into an adjacent new coal field, land acquisitions and major environmental and other approvals to allow diversion of three streams, a highway, an Over Dimension route and other infrastructure in a political and environmentally sensitive atmosphere. The lessons from International Power Hazelwood's (IPRH) experience are: ? that the clear set of project principles and guiding values ensured delivery of a robust plan; ? a robust plan can withstand significant change; and ? value management (VM) played an important role in providing assurance, to all, that the plan was sound at both the strategic and micro levels. This Hazelwood mine project included five major VM workshops. The first was a critical review process in addition to design and cost reviews. This VM workshop was used to analyse, at a high level, the preferred coal mining sequence and design concepts, together with the interaction between design elements, risks and costs. In addition to this, the workshop provided an agreed common pathway for all downstream decisions. A second VM study was conducted to ensure that the proposed plan and design for relocation of the conveying systems from the existing mine into the new field were planned for optimum achievement from a whole of life cost, time, operational and maintenance perspective, plus the logistics of continuing operations while relocating assets. A third study followed to review the Conveyor Transfer Alliance and review functional design. A fourth VM study workshop was formed at the start of Phase 2 Alliance to ensure that the best value for money was being achieved through the current design, schedule and project arrangements and that all interfaces between parties had been reviewed and responsibilities were clear and understood. Other studies are outlined later in this paper. This paper details the evaluation criteria and processes used in the project evaluation that led to the WestField Mine Development.

Jan 1, 2007

By R. G. Coyle

"In an earlier paper the author explored the consequences of price-stabilizing effects, on an industry-wide basis, of various production strategies. These ideas have now been applied to an illustrative case of an individual mine. It is shown that the turning of production and financial policies can affect financial performance over a five-year period by as much as 22 per cent.No generality is claimed for the results and they would differ from mine to mine. It is, however, asserted that the results show that the proper turning of production, reserves and financial policies are more critical determinants of mine performance than has been realised. It is also asserted that the methods of dynamic analysis are the most appropriate means for studying this policy-design problem."

Jan 1, 2014

"Chairman: Professor J. Elbrond Rapporteur: Miss V. E. MartingPapers.Aids to planning production in coal mines by F. H. Deist and M. P. RobertsCapacity calculations, investment allocation and long-range production scheduling in German coal mines by F. L. WilkeOre reserve evaluation and open pit planning by J. M. Marino and J. P. SlamaThis session was devoted to the economic aspects of planning and scheduling. After Dr F. H. Deist had introduced the paper Aids to planning production in coal mines, Dr T. V. Falkie summarized the following formal contribution prepared jointly with Dr R. V. Ramani, describing the work that has been done at the Pennsylvania State University in the development of simulation programs for mine planning over the past 15 years:During the late 50's and early 60's, Monte Carlo simulators were developed to model continuous miner-shuttle car transport systems, track haulage systems, belt conveyor networks, etc. In the mid-60's attention was directed towards deterministic simulation of equipment performance, given the equipment characteristics and the system profile. In the late (10's all these systems (miners, shuttle cars, belts and trains) were integrated together to form a complete coal mine simulator and the program could predict the output potential of the system, given the mining dimensions, method and equipment employed. The actual sequence of coal-cutting operations is entered into the computer through the use of a special programming language which permits any type of mining configuration to be simulated. The simulator is hybrid in nature in that the shuttle cars, trains and belts are simulated deterministically, whereas rate functions with delay frequencies are entered for the continuous mining operations of sumping, shearing, fleeting, cleaning, etc. With suitable manipulation of the data, the program may be applied to all belt or conventional mining sections. Most of these simulators were developed through the assistance of grants from the Department of Mines and Mineral Industries of the Commonwealth of Pennsylvania and are available from the Coal Research Board of the Commonwealth,"

Jan 1, 2014

"Chairman: Professor J. C. Griffiths Rapporteur: Mr J. P. G. PRETORIUSPapers:Mine-mill production scheduling by dynamic programming by R. J. Roman Optimization of a large mining venture by J. C. Paynter, B. K. Loveday and C. G. Robinson Economic surface mining of multiple seams by T. V. Falkie and W. E. PorterIn introducing his paper, Mr Roman said that whereas in manufacturing plants the yearly production levels were usually chosen to produce the largest annual cash flow, in a mining operation, the raw materials (ore) were exhaustible so that the production had to be scheduled to maximize the total net present worth of the operation. This optimum production schedule could be determined by using dynamic programming. The required information was readily available to management at most mines. The 'possible operating range' of production rates lay between the rate with the highest profit per ton. and that with the highest profit per year. The optimum production rate started typically at the top of this range and decreased slowly as the deposit was depleted.Dynamic programming was used to determine several production schedules for a hypothetical mine-mill complex. The effects of changes in the ore grade estimates, size of deposit and acceptable rate of interest on the production schedule were taken into account. Apart from the fact that the net present worth of the overall profits was larger than that obtained by conventional methods, it appeared from the cases studied that the amount of metal recovered was also greater.Dr it P. King commented that this was a very interesting application of dynamic programming. He pointed out, however, that the market price of the metal was likely to vary significantly and randomly during the life of the mine, and he suggested that the problem should, therefore, be reformulated as a stochastic dynamic programming problem.If the price of the metal rose to abnormally high levels, a much higher than normal production rate could be expected. The results of analyses given in Table 5 showed that the production rate was a function of market price. In his view the stochastic problem could be solved just as easily as the deterministic problem.In reply to a question by Dr King as to whether the function relating recovery to production rate (Table I) was based on real data, the author replied that it was based on the results of an analysis conducted at the Union Carbide Corporation's Pine Creek tungsten mine in California.Dr D. M. Hawkins stated that costs were incurred when the production rate was altered, for example, in appointing or laying off staff, and that in practice it may be necessary to take these costs into account in finding the optimum production rate. Mr Roman replied that, while normal administrative costs were accounted for, the additional costs incurred in appointing and laying off staff were not taken into account."

Jan 1, 2014

By P. Pięta, A. Surowiak, T. Niedoba

In a flotation process of copper ore three factors were measured: copper grade in concentrate (β), copper grade in tailings (J) and recovery of copper in concentrate (e). The experiment was conducted by means of the Jameson cell. The factors influencing the quality of the process were particle size (d), time of separation (t), type of the collector (k) and dosage of the collector (s). The considered vector function was then [β(d, t, k, s), J(d, t, k, s), e(d, t, k, s)]. Optimisation achieved was based on determining the values of the adjustable factors (d, t, k, s). The goal was to obtain the highest possible values of functions β and e (maximum) and the lowest possible values of function J (minimum). To this purpose the taxonomic methods were applied. Keywords: Flotation, copper ore, lithology, flotation agents, particle size distribution, taxonomic methods

Jan 1, 2020

By M. Mpofu, B. Maphalala, S. Khan, S. Ngobese, D. Roberts

This paper details an assessment of stemming practices at a South African opencast coal mine and their influence on ground vibration and air blast. Quantitative and qualitative analysis methods were used for the study. The parameters assessed for the quantitative analyses included stemming length, stemming material type, blast-hole depth, burden, and spacing. Pre-blast data from the mine was analysed to determine the deviation between actual and mine design stemming parameters. Mine design stemming length was also compared to the rule-of-thumb stemming lengths. Peak particle velocity (ground vibration) and air blast data from seismograph stations around the mine was analysed to determine the correlation between stemming length and excessive ground vibration and air blast. The qualitative analysis involved observations of blasting procedures at the mine to determine compliance with mine procedures. Some level of non-compliance of actual stemming parameters to design stemming parameters was found, which initially suggested that non-compliance may have contributed to excessive air blast. However, further analysis of the seismograph results indicated no direct correlation between stemming length and excessive air blast and ground vibration. Since stemming parameters are interrelated, it is crucial that all blasting procedures, including stemming, are executed in accordance with best practice, and recorded accurately. There is a need for digital systems for capturing on-bench blasting parameters, as the currently used manual data recording and reporting systems are inefficient and prone to error. Improvements to blast designs are possible through efficient and accurate data recording and reporting systems.

Jan 1, 2021

By P. van der Steen

This paper examines the historical developments in diamond beneficiation technology and the impacts on the industry. The art of diamond beneficiation has given way to the application of scientific process, but at considerable capital expenditure. The shift in beneficiation methodologies has been disruptive to the traditional skills set of the industry, but evolutionary change continues and has been beneficial to the quality of the final product.

Jan 1, 2010

By K. Duffy, W. Valery, L. Pyle, P. Holtham

A conceptual scoping study was conducted to investigate pre-concentration options for upgrading ore from an Ag-Pb-Zn deposit. The low grade of the ore would result in only modest economic returns, given current market conditions. Several pre-concentration options were considered. These included: selective mining, crushing and pre-screening (following either standard or high intensity selective blasting), bulk ore sorting, particle sorting, jigging, dense medium separation, or combinations of these approaches. Flowsheets were developed for each option, and the upgrade performance was modelled using Limn to determine mass balances and stream tables. Due to the limited availability of test work data, the models were based not only on what test data was available but also on case study data found in the literature. The Bazin technique was used to derive assay by size data for different streams following crushing. Equipment lists and preliminary layouts were established based on the stream tables, and capital and operating costs were estimated for each flowsheet. This information was used to carry out a preliminary economic evaluation using net present value and sensitivity analysis. In this case, the most economically attractive process was found to be particle sorting; although further benefits may be realised by combining with bulk sorting. This paper describes the methodology used and the key findings of the study. Keywords: Pre-concentration, pre-screening, ore sorting, jigging, Ag-Pb-Zn, particle sorting, bulk ore sorting

Jan 1, 2020

By M. Khodadazadeh, K. G. van den Boogaart, T. Leißner, L. Tusa, J. Gutzmer, R. Gloaguen, M. Kern

Ore sorting is a technology that is increasingly used to process primary raw materials. Timeconsuming and expensive empirical state-of-the-art test work is carried out to assess whether the use of ore sorting for the enrichment of a particular ore makes technical and economic sense. With the innovative simulation-based approach presented here, it is possible to direct the selection of a suitable sensor based on quantitative mineralogical and textural data, thus avoiding much of the empirical studies. Required data can be collected quickly and cost-effectively using available methods of automated mineralogy. The obtained parameters such as mineral grain size distribution, modal mineralogy, mineral area and mineral density distribution have been utilised in this study to simulate the prospects of success of ore sorting, applying different types of sensors. Empirical tests with commercially available sensor systems have been conducted to experimentally validate the predictions of the simulations. The estimation of the target mineral grade can be further optimised by the use of machine learning algorithms for the integration of automated mineralogy data and sensor data. The approach can easily be adapted to other types of raw materials and thus has great potential to become a key technology for the optimisation of processing experiments. Keywords: Automated mineralogy, hyperspectral imaging, machine learning, ore sorting

Jan 1, 2020

By E. Emami, J. Valencia, J. Sattarvand

The knowledge of the final location of a drillhole is critical in obtaining the expected blasting results. This paper proposes a new methodology to control the drilling accuracy in open-pit mines using aerial images and machine learning. Specifically, it investigates how support vector machines (SVM) and convolutional neural networks (CNN) are useful for automatically detecting blastholes over drone images captured in blasting patterns. Several datasets were obtained from different mines in Nevada (USA) and were used to train and test models. We then processed those images to create orthomosaic and digital elevation representations of the patterns. Thousands of patches were then extracted and augmented to develop SVM and CNN models. The results demonstrate that machine learning is useful for drillhole detection and, in this way, to control the drilling accuracy and use the explosive energy more efficiently.

Sep 1, 2021

By N. Tatalias, P. Ilunga, M. Lampi, J. Edwards, K. Valkama, M. Nicolle, D. Samal

"Developing a greenfield mining project is a complex exercise: doing so in an increasingly volatile, uncertain, and ambiguous global economy adds significantly to this complexity. In the context of an elevated cobalt price, this paper outlines the metallurgical and process development of the Mutoshi copper–cobalt project for copper cathode and cobalt hydroxide production in the Democratic Republic of Congo. Chemaf has a long production history on the Copperbelt, a region widely perceived to be tough to operate in. This history stretches back to 2001, during which time the company has developed two copper–cobalt processing facilities. The experience gained in the development and operation of these two facilities has been used extensively in the Mutoshi copper–cobalt project. The metallurgical test work, process design, and project delivery approach are presented. Additionally, the decisions taken to minimize risk and maximize upside to the project are discussed. IntroductionChemaf (Chemicals of Africa), a mining company located in Katanga province of the Democratic Republic of Congo (DRC), has been operating since 2001 with two major copper– cobalt processing facilities: the Usoke and Etoile plants. In 2016, Chemaf acquired the Mutoshi mine, which belonged to Gecamines and had been explored by Anvil Mining since 2004 under a joint venture with Gecamines. Chemaf appointed African Mining Consultants Ltd (AMC) to undertake a preliminary economical assessment, then develop a JORCcompliant Mineral Resource estimate and finally a full life-of mine feasibility study. Both a Mineral Reserve and Mineral Resource were developed and the final life-of-mine feasibility study is to be published shortly. A metallurgical test work programme was initiated and carried out by Chemaf’s research and development laboratory with assistance from the Chemaf process team. After completion of the initial test work, Chemaf developed a process design criteria document for a 20 kt/a copper cathode and 8 kt/a cobalt in hydroxide production plant, followed by a flow sheet and supporting METSIM mass balance. As the drilling progressed, the plant design capacity was revised to 16 kt/a cobalt production. The life of the mine at this production rate is over 40 years."

Nov 1, 2018

By C. Musingwini, M. Mohutsiwa

"SynopsisCapital cost estimates are important in decisions on whether a project will be approved, mothballed, or abandoned. In South Africa, junior coal miners do not have extensive databases of historical projects from which to estimate capital costs. The purpose of this paper is to establish formulae that can be used for estimating capital costs of developing coal mines in a coal-producing country, using South Africa as a case study. The costs are estimated to an error of magnitude level of -30% to +50%, which is suitable for a concept study level, using a parametric estimation technique. The study uses data from completed coal mining projects from selected coal-producing countries. Three formulae are developed and presented for estimating capital costs of underground bord and pillar, surface shovel and truck, and dragline operations.IntroductionCapital cost estimates play a critical role in deciding whether projects will proceed, be delayed, or abandoned. It is therefore important that capital cost estimates are carried out accurately as determined by the estimation guidelines based on the level of estimation conducted (Shafiee and Topal, 2012). The lack of literature on estimation of capital costs in many coal mining countries is adversely affecting junior coal miners, since they do not have an extensive database of historical projects on which to base estimations. In South Africa, the difficulty in estimating capital costs is attributable to lack of publicly available data on completed South African mining projects (Hall, 2013)."

Jan 1, 2015

By R. B. Khumalo, F. K. Mulenga

Sampling in a continuous flotation plant is always a challenge as these plants are meant for production and not research work. The continuous flotation operation used in this work produced three sets of data: the first was based on overall plant performance, done by sampling the feed, concentrate, and tails; the second was based on the roughers row cell-by-cell; the third set of results came from the cleaners/recleaners row cell-by-cell. The highest recovery results in all sets of data obtained lie in the particle size ranges of 40 μm and 100 μm, which is in agreement with results by other researchers in the same field. King’s theoretical (model) recovery proved to be able to fit the experimental data but there is still room for improvement as the sum of squared error ranged between 400– 1200. Data obtained in continuous flotation operation could be used with batch flotation test-work to characterize scale-up of flotation cells.

Jan 1, 2023