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By M. Louarrat, G. Enaime, A. Yaacoubi, A. Baçaoui, J. Blin

"The purpose of this study is to prepare a new activated carbon from olive stones for use in gold recovery by carbon-in-leach (CIL) and carbon-inpulp (CIP). The preparation method chosen was physical activation using steam. The effect of four process parameters: the residence time for carbonization, the activation temperature, the residence time for activation, and steam flow, were studied by the mean of response surface method (RSM) in order to optimize the yield, iodine index, and attrition characteristics. These two last responses were used as primary indicators of gold recovery capacity and mechanical strength. The results obtained show that optimal activated carbon can be prepared under the following conditions: a carbonization time of 157 minutes, activation at 921°C for 53 minutes, and a water vapour flow of 0.18 mL/min. This optimum carbon has an iodine value greater than 1100 mg/g and an attrition index in the order of 0.74%. These values reflect the quality of the precursor (olive stones) as a raw material for the development of an effective new activated carbon for the gold mining industry. IntroductionActivated carbon is an effective adsorbent widely used in industry due to its high surface area, well-developed reproducible microporous structure, and high degree of surface reactivity and adsorption capacity. World consumption of activated carbon is steadily increasing. It is primarily used in industrial wastewater and gas treatment and also for silver and gold recovery from cyanide solutions (Syna and Valix, 2003; Soleimani and Kaghazchi, 2008; Buah and Williams, 2010; Eddy et al., 2011). However, activated carbon is expensive and it needs to be regenerated after each adsorption cycle. In order to decrease the cost of manufacturing activated carbon, low-cost forest and agricultural wastes are considered promising new materials. In recent years considerable research has been reported on activated carbon from agricultural wastes, such as olive stones (Yavu et al., 2010), acorn shells (Sahin and Saka, 2013), peanut shells (Wu, Guo, and Fu, 2013), grape seeds (Jimenez-Cordero, 2014), coconut shells (Yalcin and Arol, 2002; Gratuito, 2008), palm shells (Sumathi, 2009), cherry stones (Jaramilloa, Gomez-Serrano, and A´lvareza, 2009), macadamia nut shells (Eddy, 2011), apricot stones (Soleimani and Kaghazchi, 2008), and bagass (Syna and Valix, 2003)."

Mar 1, 2019

By B. F. Giyani, A. Salama

Tanzania is a country with a variety of mineral deposits, including metallic minerals, gemstones, mineral fuels, industrial minerals, and critical minerals. This study provides an overview of mining legal framework, mineral occurrence and production, challenges in the mining sector, and government initiatives. The aim is to demonstrate the development of the mining sector in Tanzania and explore the potential for further mining investment in the country. The mineral production data showed generally increasing trends over the years, for example, gold production increased from 42 tonnes in 2018/2019 to around 50 tonnes in 2023/2024. Despite the growth, the mining sector encounters several challenges, including a lack of detailed geological information on mineral deposits, inadequate infrastructures in some remote mining sites, the existence of informal artisanal miners, and mineral smuggling. The Tanzanian government has introduced several initiatives to address these challenges, including carrying out the highresolution airborne geophysical survey to increase geological information in some areas, the formalisation of artisanal and small-scale mining, establishing mineral markets to combat mineral smuggling, and encouraging mineral value addition within the country.

Oct 24, 2025

By C. Banff, E. C. F. Hamman, J. Venter

Open pit slope stability analyses for large scale instabilities are often carried out using limit equilibrium, finite element or finite difference computer programs. All of these require empirical estimates of rock mass shear strength when calibrated values are not available, which is a common occurrence. A common method of estimating rock mass shear strength is the Hoek-Brown failure criterion, which often over- or underestimates rock mass shear strength when used in limit equilibrium or elastic linearly plastic slope stability analyses, resulting in published alternative estimates for the coefficients of the Hoek-Brown failure criterion. This paper investigates the differences between limit equilibrium and elastic linearly plastic slope stability analysis based on the Hoek-Brown failure criterion. The investigation consisted of a comparison of 3840 RS2 finite element analysis models completed with strain softening, and 216 Slide2 limit equilibrium models. The models were used to evaluate a methodology to determine equivalent limit equilibrium and elastic linearly plastic shear strength parameters that provide the same stable slope angles and instability back break distances as the more representative strain softening stress analysis methods. This paper presents the methodology and compiles the results into design charts and equations for equivalent limit equilibrium Mohr-Coulomb shear strength parameters, that simplify calibration against actual case studies. The results compare well with older empirical shear strength estimates, however, a detailed calibration of the results against case studies will need to be carried out. The analysis also did not consider pore pressure effects; this is left for future publication.

Sep 1, 2025

By T. Dlokweni, M. Bester, C. Koegelenberg, I. Basson

Certain degrees of safety, economic, and financial risk are implicit in any mining operation. At Thabazimbi Mine, slope stability was one of the major sources of risk, largely due to data uncertainties. Consequently, a risk-based approach in slope design was followed. On 6 June 2015, a slope failure occurred in Thabazimbi Mine’s Kumba pit, involving approximately 65 million tonnes of rock failing into the pit and the valley below. Although the failed mass moved rapidly and resulted in a run-out distance of approximately 900 m, controls had been put in place to successfully evacuate all personnel. Risk assessment during the onset of failure supported the decision to not compromise the safety of personnel in any way, leading to unavoidable equipment loss. This contribution presents the failure as a case study in the context of a risk-based approach to slope design as well as the importance of implementing geotechnical controls to effectively manage slope instability risk. Furthermore, a comprehensive back-analysis was performed, on a fully constrained 3D model, utilising 3DEC software, to gain insights into the failure mechanism. In conclusion, lessons from the Thabazimbi slope failure are valuable as they demonstrate the importance of following a risk-based approach in slope design to effectively manage safety and financial risk in open pit mines.

Sep 1, 2025

By U. König, N. Norberg

Ore mineralogy defines the properties during processing and metal extraction. Fast and frequent monitoring of the mineral content and related process parameters brings value to the mining operation and material processing. Decreasing ore qualities and increasing prices for raw materials require a better control of processed ore and a more efficient use of energy. Traditionally quality control in mining industries has relied on time consuming wet chemistry or the analysis of the elemental composition. The mineralogy that defines the physical properties is often monitored infrequently, if at all. The use of highspeed detectors has turned X-ray diffraction (XRD) into an important tool for fast and accurate process control. XRD data and their interpretation make the difference in the identification of minerals, in describing their distribution in ore bodies and in their beneficiation during processing. The use of statistical techniques such as Partial Least-Squares Regression (PLSR) or Principal Component Analysis (PCA) on XRD raw data has been successfully trialled to determine raw materials and processed ores, in addition to well established methods for mineral identification and quantification. PLSR can be used to correlate process parameters directly from the XRD pattern without investigating the mineral content. Hidden information present in the XRD pattern but not determined with traditional methods can be used to improve the characterisation of the analysed materials. The practical use for the direct determination of process relevant parameters during exploration and ore beneficiation will be illustrated in several case studies from mining and ore processing. Keywords: Geometallurgy, mineral monitoring, X-ray diffraction, process efficiency

Jan 1, 2020

By H. Dudycz, A. Skoczylas, P. Stefaniak, P. Pyda

In the era of Industry 4.0, technologies such as Big Data (BD) and the Internet of Things (IoT) play a key role, especially for multi-site manufacturing companies. In such companies, the challenge is to collect and process massive amounts of data from industrial devices and extract key information from this data in real-time for ad hoc decision-making. The ability to analyse data from industrial devices translates directly into streamlined production processes, cost optimisation, prevention of unplanned events, and safety during operation. In this context, particular attention should be paid to Big Data Analytics (BDA), whose main source is the Industrial Internet of Things (IIoT). The purpose of this paper is to propose an IT system architecture incorporating BD and the IoT for a mining company. The paper presents results from a literature review focusing on available BD and the IoT solutions for industry (mining in particular) for the purposes of the acquisition, integration, and advanced analysis of data. The advantages and disadvantages of the different solutions were indicated and gaps in the accessibility to dedicated functionality are identified. Based on the analysis of a multi-site mining company, the main challenges faced by such companies planning to implement BD and IoT solutions are identified. Also, a proposal for an IT system architecture incorporating BD and IoT for a mining company is described in the paper. The contribution of the article consists of the identification of the challenges faced by mining companies planning to implement BD and the IoT solutions, and the proposal of an IT system architecture that allows BDA whose main source is the IIoT.

Sep 1, 2021

By J. D. T. Steyl, G. B. Grobbelaar

Two examples are presented to show how first-principles – physical-dynamic, here termed behavioural modelling, is used to build digital twins of unit processes or plant sections. A digital twin equips the metallurgist, engineer, or manager with a powerful tool to conduct model-based design, solve process problems and improve operations. It is particularly relevant in the metallurgical industry where plant behaviour is highly integrated, rates respond to particle dynamics in complicated ways and mineral flows across flowsheet boundaries are variable. The two examples used to illustrate the behavioural modelling methodology are 1) a flotation column unit block and 2) a multi-compartment pressure oxidation (POX) autoclave. It simultaneously accounts for the causality of material and heat flow, takes care of mineral particle dynamics, physical and chemical reaction rates, the plant control system behaviour and operating heuristics. The basic modelling building blocks are briefly reviewed to show how the behavioural modelling attributes constrain the mass and heat flow dynamics to physically realistic values. This is the key aspect that allows project value to be created with minimal input data. Behavioural modelling is especially valuable where the process dynamics are poorly understood or controlled, where data-driven models fail to cope with complex and highly integrated plant behaviour, where quality data is lacking or limited funds are available to generate the data required to fill all the knowledge gaps. The paper uses the flotation column example to show how behavioural modelling and simulation can be used to optimise plant performance, while the multi-compartment POX autoclave model shows how it can be used to diagnose process problems. It also provides a solid basis to add a data-driven component – in other words, it makes a strong case for a hybrid first-principle– data-driven approach to solve process problems, especially where microscopic-level understanding is poor. Keywords: Digital twin, behavioural modelling, simulation, flotation column, pressure oxidation

Jan 1, 2020

By J. Pelders, F. Magweregwede, S. M. Rupprecht

Increased depths of conventional gold and platinum mines, longer travelling times as working places move further from the shaft, and ancillary activities taking place in the mining cycle reduce the useable time spent at them workface. Current shift lengths of 8 hours 20 minutes may no longer be adequate ton complete required mining activities.The impact of mineworker commuting times on shift work is also not well understood. The aim of this research was to draft a framework to optimize shift cycles in order to maximize productivity, health, safety, and wellness in the South African mining sector. The framework was informed by a review of the literature, case studies at a local gold mine and platinum mine, and a workshop with industry experts. The findings indicate potential advantages of extended shift lengths and continuous operations, such as improved productivity, asset utilization, and employee morale. However, concerns included fatigue and the associated safety hazards, particularly when working longer shifts, night shifts, and numerous consecutive shifts. Job demands, personal factors, and commuting times are further considerations when scheduling shifts. The ideal shift system for the mining sector should holistically consider and balance operational requirements, health and safety, and employees’ and their families’ requirements, and suit the unique needs of each operation. Changes in shift cycles will require a structured change management process, which involves all stakeholders, and could help to enhance the viability of the South African mining sector.

Aug 1, 2021

By Z. Ruetz

Portable X-ray fluorescence (pXRF) analysis has been widely adopted in the geochemical and environmental field as a cost-saving alternative to standard analyses. This paper outlines the efficacy of a method for indirectly quantifying organic copper content in solvent extraction circuits via stripping of the chelated metal with concentrated sulfuric acid in a single contact and subsequent pXRF aqueous analysis. pXRF analysis is common within the mining industry but presents unique challenges with liquid analysis, the most prevalent of which are briefly discussed. This method was developed specifically for mining operations with regional constraints and limited resources. Providing an in-field alternative to flame atomic absorption spectrophotometry and inductively coupled plasma optical emission spectroscopy, this entirely mobile XRF analysis method produces consistent and accurate results within minutes and at a fraction of the cost.

Jan 1, 2023

By T. Bui, T. Wallmach, S. B. Blancher, A. Back, M. Pierre, V. Delarue, A. Kanzari

This study investigates nickel laterite porosity and its impact on geometallurgical modelling. We performed a detailed mineralogical study on a set of Ni-laterite samples originating from New Caledonia. Samples were analysed after heavy liquid separation by automated SEM (QEMSCAN®). Laboratory and QEMSCAN® modelling results do not correlate well. Ideal physical mineral properties such as mineral densities used in QEMSCAN® modelling do not match the actual physical densities of minerals. The presence of empty or water-filled pores can represent important amounts in minerals and change the overall density of a particle. An adequate modelling of real density separation of minerals and particles should consider the water-filled pores. The first step towards a better simulation was to integrate pores larger than 10 μm in diameter filled with water (density of 1 g/cm3) in the QEMSCAN® database. The results approached, but did not match the physical laboratory results. The second step was to identify nanometer to micrometer sized pores, which could not be identified by QEMSCAN®. It was possible to identify nanometric pores in enstatite, Fe-oxides, serpentine, talc and quartz, and radial aggregates of fibrous Fe-oxyhydroxides with high resolution SEM (HR-SEM). The quantification of those micro-sized pores was performed on 2D HR-SEM images using image-processing techniques developed in Python to calculate the nanometer to micrometer scale pores in each mineral. Despite the limitation of converting 2D imaging into 3D objects, in our case pore sizes and porosities, we were able to calculate a mean value of porosity for each mineral. The integration of this porosity in the calculation of particle densities yielded a good match between the QEMSCAN® model and the laboratory experiment results. Despite the complexity of a strongly weathered material, such as Ni-laterites, a good knowledge of the ore makes it possible to build reliable processing models. Keywords: Mineralogy, geometallurgy, nickel laterites, SEM, QEMSCAN®, porosity, density

Jan 1, 2020

By C. Swart

Automation technologies are increasingly adopted in different mines world-wide. This paper presents the technical aspects of vehicle automation applications at two Noranda operating mines. Teleoperation of 5 LHDs at Noranda?s Bell Allard mine is used in order to meet aggressive mining requirements under difficult conditions. The equipment is performing under high demand for reliability and performance. In order to further increase performance, automated loading has been commissioned on one of the LHDs and is being tested. Results to date indicate improved performance with respect to an operator through better filling of the bucket, fewer passes at the muck pile and shorter cycles. Noranda?s Brunswick mine is currently commissioning an automated haulage zone where two optically guided trucks transport ore from a remotely operated chute to two ore passes. Expected operational advantages include increased system capacity and enhanced safety and comfort for the operator. Monitoring to date indicates that the trucks can operate reliably under the conditions imposed by mine production.

Jan 1, 2002

By K. Isaac, S. O. Bada

This research focuses on the co-firing of discard coal with refuse-derived fuel (RDF) to utilize this abundant resource in South Africa for energy generation and reduce the volume of waste disposed of at landfills. The potential of a coal with a high ash content (> 40%), which is a grade used in some power stations in South Africa, and its combustion compatibility with two different RDFs in terms of emission reductions has been established. Gaseous emissions and ash residues from the combustion and cocombustion of the coal, two different RDFs and coal/RDF blends of different proportion were analysed. One of the RDF samples contained mostly paper (PB) and the other mostly plastic (PL). Co-combustion ash from the discard coal and RDFs showed a decrease in chloride and alkali metal contents as the coal ratio in the blend increased. The slagging propensity of the co-fired blends was found to be very low, while the propensity for fouling decreased from high to medium for all the blends with < 75% RDF. Cocombustion of RDF with coal showed a decrease in SO2 emissions from 387 ppm (discard coal) to 50 ppm for the sample containing 25% coal discard plus 75% PL. A 15% PL to 85% coal blend also reduced NOx emissions from 145 ppm (100% PL) to 88 ppm. The lowest CO2 emission observed was 6000 ppm for the blend of 85% discard coal plus 15% PB. It was established that the most favourable fuel blend that can produce the lowest sulphur emissions if used for power generation is the 25% coal discard plus 75% PL sample.

Aug 2, 2022

By D. V. J. W. Groenewald, T. M. Louw, L. Auret, S. M. Bradshaw, A. V. Cherkaev

Unexpected equipment failures lead to financial losses due to production disruption. Time-based maintenance, based on checks over regular time periods, has been employed to minimise disruption. However, the improvements it can offer are limited as it may lead to unnecessary service of healthy equipment or missed failures occurring between service intervals. Condition-based maintenance (CBM) provides a further improvement to equipment reliability by detecting faults and predicting remaining useful life (RUL) based on equipment health monitoring. Its application in the mineral processing industry is hindered due to the high cost of health monitoring equipment. In this study, two stochastic process models, the adaptive auto-regressive model and the gamma process, are compared in their ability to forecast the degradation state and to provide RUL prediction. The gamma process model was found to be effective in both tasks. Due to its simplicity and minimum hyperparameters requirements, it is proposed to use the gamma process as a baseline for comparison with other models. Keywords: Condition-based maintenance, remaining useful life, slurry pump, adaptive autoregressive mode, gamma process

Jan 1, 2020

By J. de V. Lambrechts

A critical comparison of specific cooling power and the wet kata thermometer in hot mining environments By J. de V. Lambreehts. D.Sc. (Eng.) (Rand) A new formula for the wet kata thermometer has been established in place of the currently used one which is believed to be fundamentally wrong and the new formula is compared with the recently proposed specific cooling power concept. Apart from a constant multiplier, it is concluded that the difference between. the two concepts lies solely in the value of &apos;n&apos; in the function vn and that this value for the cooling power of air on the sweating human body remains to be established reliably. The kata thermometer might yet be found to be a reliable predictor of heat stress in hot environments.

By S. Durapraj, R. T. Masethe, U. Maqina, A. C. Adoko

This study investigates seismicity and rockburst control within the Merensky Reef and UG2 orebody of an intermediate-depth platinum mine located in South Africa's Bushveld Complex. Utilising a mine-wide seismic monitoring system, over 1,900 seismic events were recorded between April 2023 and May 2024, revealing complex seismic patterns driven by mining-induced stress changes. The largest event, with a magnitude of ML 2.0, underscores the seismic risks associated with mining at increasing depths. Key findings include the spatial and temporal variability of seismic events, with high seismic activity observed near pillars and geological structures. A significant portion of events correlated with pillar and foundation failures. Moment tensor analysis identified dominant failure modes, such as stress-driven fracture closures and dynamic pillar failures. To mitigate risks, the study emphasises advanced support system redesign and rockburst risk assessment using the rockburst damage potential (RDP) method. The research highlights the importance of monitoring, geotechnical compliance, and adaptive designs in enhancing safety and reducing seismic hazards in underground mining operations. The study applied the RDP framework, classifying damage across R1 to R5 scales, where most instances fell into low-risk categories (R1 and R3), indicating minor to moderate damage. However, data limitations and the tabular stoping method's complexity led to inconclusive results, highlighting the need for more robust data and customised risk assessment tools. Despite these challenges, the RDP approach provided valuable insights into rockburst mechanisms and the effectiveness of existing support systems.

Jan 12, 2025

The excavation of ramps and tunnels often requires high-speed development with (or without) the use of high-energy mining equipment such as loaders, dump trucks, TBMs and roadheaders. This high-speed development creates a challenge in terms of providing a safe and productive working environment. For example, heat from continuously exposed surrounding rock, heat from broken rock, heat generated by mining equipment, potential in flows of hot ground water, pollution from associated diesel equipment and the distance of the advancing face from fresh through-ventilation all have to be taken into account when designing ventilation systems for high-speed ramp and tunnel developments. This paper discusses methods of achieving acceptable environments at the face and along the length of the tunnel. The methodology has been successfully implemented in the development of long (up to 20 km) TBM drives in the Lesotho Highlands Project and in mining projects in hot rock using drill and blast methods as well as mechanized methods using continuous miners and roadheaders. The determination of heat loads includes calculation of the heat flow within the surrounding rock, evaluation of the operating cycle of the equipment and the contribution to the overall heat load of the broken rock as it travels out of the tunnel. The determination of heat loads from surrounding rock in new tunnels required a modification of the algorithms generally used for established excavations. The paper also examines the use of, for example, mobile duct and fan systems to ensure that fresh air is delivered to the specific areas where workers are located.

Jan 1, 2000

By S. Gan, E. van Niekerk, L. Birrell, D. Robbertze, L. Ncubi, B. Zhao

Quality assurance and quality control (or QAQC) plays a key role in safeguarding the level of confidence of the data generated during mineral exploration and mine development, and is also part of the reporting code requirements for resource estimation and reporting, as well as mining investment. Implementation of good policies and working protocols in quality management will result in the generation of reliable information, which is critical for decision-making on the future of the mining project. The use of certified reference materials, i.e., standard, blank, and duplicate samples, proves effective and efficient for ensuring the level of data confidence in terms of precision, accuracy, and sample contamination. This is well demonstrated by the practice of QC in the exploration programme for the chrysotile tailings storage facilities of Havelock Mine, using 1254 samples from 53 drill-holes. Different statistical tools were applied to analyse the assay results from these samples. The outcome substantiates that the QC practice established during the Havelock exploration project is aligned to best practice guidelines in the industry. The resource delineated indicates that the tailings material at Havelock could potentially become a significant source of supply to the global magnesium market.

Jul 2, 2022

By T. Khumalo, L. Musenwa, S. Masemola, M. Kgaphola

"In 2017, Petra Diamonds completed the construction and commissioning of a modern, fit-for-purpose diamond processing plant at Cullinan Diamond Mine (CDM). The design of CDM’s milling circuit is unconventional in that it comprises an autogenous (AG) mill with a grate discharge with large ports, low-revolution jaw crushers, and high-pressure grinding roll crushers with large operating gaps. In this paper we review the design to provide guidance on what is expected from the milling circuit and to demonstrate how the design aims to address challenges experienced in the old plant, which was based on staged crushing technology. We assessed the performance of the CDM AG milling circuit from commissioning and early production stages to examine its impact along multiple dimensions. In the assessment we sought to understand the lessons from our milling circuit regarding diamond liberation, energy consumption, and the future of diamond processing as a whole. IntroductionCullinan Diamond Mine (CDM), previously known as Premier Mine, is an underground diamond mine owned by Petra Diamonds. Petra Diamonds is a leading independent diamond mining group and a growing supplier of rough diamonds to the international market. Petra Diamonds is listed on the Main Market of the London Stock Exchange under the ticker ‘PDL’. Petra’s total resource of 305 million carats ranks third by size after De Beers and ALROSA (Petra Diamonds, 2018).CDM was established in 1902. The mine rose to prominence in 1905, when the 3106 carat Cullinan Diamond — the largest rough diamond of gem quality ever found — was discovered there. The mine has produced over 750 stones that are larger than 100 carats and more than a quarter of all the world's diamonds that are larger than 400 carats. Cullinan is renowned as a source of large, high-quality gem diamonds, including Type II stones, as well as being the world’s most important source of very rare blue diamonds (Petra Diamonds, 2018)."

Feb 1, 2019

By M. Grozdanovic, D. Marjanovic, M. Ilic

We present a framework for solving the problem of functional compatibility between process control equipment in control centres at underground mines and operator capabilities. The equipment incorporates displays of current ventilation, gas, and fire hazard data, status of alarm and early warning systems, a voice communication subsystem, and facilities for recording and printing ofdata and reports. The layout of the existing control panel is compared with a recommended design. The basic principles of ergonomic design and arrangement of the controls and indicators, as well as ease of use, type of operations carried out with these controls, and operators’ viewing angles are discussed. The objective is to improve the usability of control panels, display boards, and graphic screens so as to enhance the functioning of control centres and optimize control of technological processes in coal mines.

Jun 10, 2024

By R. J. Quevedo, Y. A. Sari, S. D. McKinnon

The large scale of cave mines leads to many challenges, including operational logistics and geomechanics design. In current practice, pillar stability assessment relies almost exclusively on stress analysis. However, stability is also affected by other factors including those related to operational aspects of the mining method, the effects of which are difficult to account for during the design stages. In this paper we present a case study of the application of a machine learning approach to evaluate the influence of these operational factors on pillar stability at the Chuquicamata underground cave mine in northern Chile. Due to the likely multi-factorial damage process leading to collapses and considering the different pillar conditions, a tree-based machine learning method was used and analysed to improve the understanding of the relative importance of the various contributing factors. Unlike stress analysis methods, it does not require any a priori knowledge of failure mechanisms, nor the calibration of associated controlling parameters. The proposed random forest model predicted pillar collapses with 80% accuracy despite limited samples to model from. The main contributing factors to collapses were found to be related to available pillar volume, cave front geometry, and time under abutment stress conditions. The effects and interactions of such factors were also studied, showing that careful and improved control over operational conditions can significantly reduce the likelihood of pillar collapses. These conclusions could not have been obtained from stress analysis alone, illustrating the complementary nature of conventional stress analysis and machine learning approaches.

Mar 14, 2024