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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 T. C. Maswanganyi, G. L. Smith, R. C. A. Minnitt

This paper identifies the strategic gaps and opportunities for the South African mining industry’s contribution towards advancing sustainable development. Mineral resources companies are confronted by a range of complex social performance challenges, which largely manifest in sporadic community and labour unrest, undermining the sustainability and profitability of these companies. Integrating supply chain management, strategic long-term planning and sustainability planning is identified as a strategic gap that can contribute towards the sustainability of mining companies, if effectively implemented. Contributing towards sustainable development by the South African mining industry is not merely a voluntary requirement on the industry but a legal requirement in terms of the Minerals and Petroleum Resources Development Act No. 28 of 2002. This Act is legislation aimed at advancing socioeconomic development in communities that host mining operations and in areas that provide labour to the South African mining industry. In contributing towards the advancement of sustainable development in mining host communities, not only will mining companies fulfil a legal requirement in terms of the Minerals and Petroleum Resources Development Act, but they will also prevent negative social and economic impacts in those communities. This paper identifies innovative and cost-effective ways of advancing sustainable development by integrating strategic supply chain management, strategic long-term planning, and sustainability planning.

Dec 15, 2025

By E. Kuipa, J. N. Lekunze

The selection of an underground mining method stems from a multivariate analysis that considers geomechanical, geological, economic, and operational parameters. Even after identifying the most compatible method, there is no assurance that the mining company will achieve the best performance. The geological complexity of some deposits requires adaptations of methods described in the literature to obtain more selectivity and reduce mining waste. There are some studies on geometry of underground structures, but a methodology that describes an adaptation of a room-and-pillar mining method for ore bodies with down-dip varying from 20° to 25° is novel. The present work aimed to reduce dilution by adapting the traditional room-and-pillar mining method (TRP) to inclined ore boLittle attention has been paid to the rehabilitation of derelict and ownerless mines in South Africa after their lifespan. This paper aims to explore management gaps in legislation that have resulted in the non-rehabilitation of derelict and ownerless mines in South Africa. There is growing evidence that supports the distressing effects of mining on people living around these mines in the North West Province. This paper was motivated by the current socio-economic status quo of old mining towns, the influx of illegal miners (Zama Zamas), severe environmental damages, and the violence associated with derelict mines. Underpinning this research was an ecosystem approach and integrated resources management principles, which formed the foundation for the decision-making process.The researcher used a mixed-method approach and employed convergent techniques. A semi-structured instrument was used to collect data from 200 respondents. The results indicated that there is a dire need for community-based consultative processes, and an absence of clear guidelines for derelict and ownerless mines to pressure mine management to adhere to rehabilitation standards. Moreover, the mining charter is ambiguous regarding policy implementation, budgetary allocation, and duration of the rehabilitation of these mines. The paper concluded that management challenges associated with derelict mines can be reduced if all stakeholders follow the guidelines as outlined in the environmental legislative framework (NEMA) of South Africa while being open to innovations in line with international best practices. It also contributes towards the development of guidelines for the management and implementation of legislation related to derelict and ownerless mines in South Africa from a philosophical, theoretical, and policy perspectivedies. This new method is entitled short-hole room-and-pillar (SHRP). The equations that measure the dilution are defined according to the geometry of stopes and openings. The results comprise comparative analyses of the operational and planned dilutions to measure the performance of the SHRP method. The average operating dilution of the SHRP method was more than five times lower than the planned dilution according to the TRP method. Low operational dilution indicates high selectivity of the method and its potential to reduce underground mining tailings.

Oct 9, 2024

By J. D. Swanepoel, S. Horn, C. J. Badenhorst

Diesel particulate matter (DPM) is the particulate component of diesel exhaust, which includes diesel soot and aerosols. When released into the atmosphere, DPM can take the form of individual particles or chain aggregates, with most in the invisible sub-micrometer range of 100 nanometres. The main particulate fraction of diesel exhaust consists of fine particles and because of their small size, inhaled particles may easily penetrate deep into the lungs. The rough surfaces of these particles make it easy for them to bind with other toxins in the environment, thus increasing the hazards of particle inhalation. DPM is a significant health hazard in underground mining operations, where the use of dieselpowered equipment in confined spaces can lead to high levels of exposure among people working in these environments. Classified as a carcinogen by the International Agency for Research on Cancer (IARC), DPM has been linked to severe health effects, including respiratory and cardiovascular diseases, as well as an increased risk of lung cancer. Effective management of DPM is essential not only for protecting people’s health but also for ensuring regulatory compliance, maintaining operational efficiency, and safeguarding the long-term viability of mining companies.

Mar 5, 2025

By O. A. Bascur

Ores are becoming extremely variable with mineralogy and hardness disturbing the grinding and flotation circuits. The current grinding and flotation sensors provide large amounts of data for process optimisation. Adding the right context and operational events augments operational knowledge for proactive actions to improve the performance of the grinding and flotation circuits. A data-driven strategy is needed to enable operations, maintenance, and business personnel to quickly and easily take corrective action when abnormal conditions occur. A digital plant template transforms data into operational insights in real-time. It uncovers the hidden, idle and downtime losses. By measuring and managing these unproductive times, people find new ways of avoiding them, improving the profitability of the plant. The information created by the real time analytics enables the calculation of recovery in real time and develops predictive analytics models to find the best operating condition based on the type of ore currently mined. The creation of new workflows and collaboration between mining and concentrator plant and the enterprise, including services providers, are enabled. A grade recovery model is used to identify the best operating conditions in real-time. An optimal Gaudin size distribution shape is used to find the grinding operating conditions that optimise the metal recovery in the rougher sections of the mineral processing plant. Sensors in the flotation circuits enable estimation of metal recovery and determine the optimal froth depth and aeration profiles, using an industrial air holdup flotation model. The implementation of a recovery/grind strategy with industrial examples in non-ferrous metal concentrator is presented in the paper. Keywords: Digital transformation, soft sensors, predictive analytics, grinding flotation optimisation, flotation bubbles, particle size, particle size distribution shape, froth aeration profiles, flotation air hold up model, recovery predictive analytics

Jan 1, 2020

By B. Emwanu, R. A. Raju

The implementation of new technology in mining can be likened to a paradoxical situation or dilemma, where, on one hand, major mining projects are not able to solicit investor funding unless it is proven that the business cases were developed using tried and tested mining methods. On the other hand, new and innovative mining technology and mining methods need first to demonstrate and prove themselves under real production conditions over a reasonable period before they can be considered bankable feasibility studies in the mining industry. This dilemma locks new mining technology investments in a continuous cycle of underinvestment. Technological innovations are particularly relevant to the mining industry, which deals with the challenges of depleting access to resources, requiring new solutions to remain sustainable and competitive. In the last decade, the mining industry has come to realise that technological innovations can directly contribute to its sustained competitive advantage (Sanchez, Hartlieb, 2020), helping to reduce costs, lessen environmental impact, increase production, and improve mineral recovery. While understanding barriers and drivers for technology adoption is important for the success of technology implementation efforts and the sustainability of the mining sector (Muduli et al., 2013), this paper suggests strategies to exit the dilemma, proposing a preliminary framework.

Oct 24, 2025

By H. P. Kritzinger, T. C. Kingsley

Rotary kilns are used for a variety of mineral processing operations. Hatch makes use of a kiln model developed from first principles to evaluate designs for its clients. This tool has been applied to a variety of pyrometallurgical applications. This paper illustrates the application of numerical optimization techniques in combination with the kiln model in the interrogation of a generic iron-ore reduction process. The fundamental modelling concepts are explained, followed by a description of the optimization approach. The results show how the combination of the two methods, with modern computing power, can generate a large number of viable design and operating candidates.

Jan 1, 2014

By M. I. Mabala, B. P. Watson, M. J. Kanda

A failed and stable Upper Group 2 chromitite pillar database was collected in 2007 as part of the PlatMine 1.2 pillar strength project. The database consisted of 177 pillars, of which 33 had failed. Most of the data were collected from various intermediate-depth mines near the town of Thabazimbi. Spans between rows of chain pillars were about 30 m. Pillar loads were estimated using pseudo-3D, elastic, boundary element modelling software. The pillar-load data were evaluated using a maximum likelihood regression analysis to determine strength parameters, following a similar approach to historically acceptable practice. The original formula was named the PlatMine Formula. This paper describes re-evaluations of the database, using a linear formula and several variations of the power formula. The formula providing the lowest standard deviation to the data in the database was considered the best representation of the pillars in the database. Through this rigorous process, a new formula for peak pillar strength was developed for Upper Group 2 chromitite pillars, which is unaffected by volume. The small standard deviation provided by this formula suggests a reliable relationship between strength and w/h ratio, in the w/h ratio range between 1.5 and 4.7. Accuracy, precision, and recall analysis confirmed the efficacy of this equation to the data in the database. Importantly, the new formula provided in the paper does not predict a significantly different strength to the current PlatMine formula, within the confines of the database.

Nov 27, 2024

By I. Cerny, M. Vanek, J. Hubácek

"SWOT analyses and the closely related TOWS matrix are frequent starting points for an organization to develop its strategy. The paper deals with the evaluation of the TOWS matrix and presents three novel approaches to evaluate the different factors of the TOWS matrix, namely (1) approach to evaluate the factors with identical weights; (2) approach to evaluate factors with their weights determined within the different quadrants of the TOWS matrix; and (3) approach to evaluate factors with weights determined within the whole TOWS matrix. The third approach has two variants. The proposed approaches to evaluate the TOWS matrix were tested on a SWOT analysis of a significant mining company in the Czech Republic. The results imply that the strategy W-T (weaknesses-threats) is recommended in three cases, while the strategy S-T (strengths-threats) is recommended once. The paper may be valuable for managers responsible for strategic planning.IntroductionThe process of human needs gratification has been closely connected with raw material resources of the planet. In the contemporary socio-economic conditions, the task of the mining company managers, apart from extracting mineral resources, is to meet the owners' intents.The managerial work itself becomes very complex. In mining companies in particular, the complexity is augmented by the characteristics of the business. Undoubtedly, the key factor is that mineral resources cannot be renewed or relocated. Stojanovi (2013) characterizes mining projects as involving great investments in finance and time, as well as consecutive decisions and a 'complex mosaic of numerous unknown factors that affect the value of the project'. He adds that mining projects are typified by a 'number of geological, technological, technical, economic, environmental, social, and financial risks' (Stojanovi , 2013).Inter alia, the managerial work may also be intese due to the dynamic internal and external conditions for the existence of any company (Vane? k, 2014). This tallies with Peter Drucker’s prediction in 1969; that the times at the turn of the millennium could be expected to be turbulent (Drucker, 1969)."

Dec 1, 2018

By A. N. Clay, N. N. Moeketsi, S. Joubert

For many years, mine-impacted water has been regarded as a problem and linked to long-term environmental liabilities. However, this water can be a renewable and a sustainable resource, provided that it is managed in a responsible and sensible manner. South Africa’s National Water Resource Strategy (NWRS, 2013) considers water that can be used to contribute to economic activity to be a water resource. Although all water resources are considered as belonging to the State, government does not appear to have meaningfully explored the use of mineimpacted water to contribute to the country’s economic activity. Africa is blessed with more sunshine than anywhere else, apart from Australia, yet we see no rollout of vast quantities of solar panels to ensure every African family has access to affordable power. This suggests that governments are incapable of managing such a free resource. At the same time, apart from the equatorial areas, water is a seriously constrained resource and yet we expect the same entities to manage a commodity none of us can live without. This paper explores the conversion of mine-impacted water from waste to a resource and how the inclusion of other stakeholders (such as water users, landowners, and ordinary South Africans) could benefit the process.

Jan 2, 2022

By T. P. Chidakwa, T. R. Stacey

This study investigated the corrosion rates of various steel types and coatings used for friction rock stabilisers in a deep-level gold mine under diverse underground environmental conditions. Testing was conducted in situ within ramps, intake airways, and exhaust airways, and through simulated laboratory experiments. Results revealed that environmental variations significantly influence the corrosion performance of different materials and coatings. Duplex coatings, made up of galvanised steel with an organic paint layer, demonstrated the highest corrosion resistance. Zinc-based coatings provided moderate protection, while 3CR12 stainless steel and uncoated S420 carbon steel exhibited comparatively poor resistance under both aqueous and atmospheric conditions.

Mar 4, 2025

By S. Schutte, J. Pelders

Worker participation in equipment development can result in improved user acceptance and product quality. This paper focuses on worker engagement in equipment development processes in the South African minerals sector. Qualitative data was gathered during interviews with original equipment manufacturers (OEMs) and industry experts. A lack of inclusion in equipment design from workers from all organizational levels in mines was reported. Meanwhile, the historical context and workplace culture of the mining industry (including leadership, trust, training, performance, and remuneration factors) were evident barriers to the implementation of new technology. Worker engagement processes should include securing management commitment, creating multidisciplinary teams, effective facilitation, shared understanding of needs, training and development, and iterative design. Human-centred design approaches and independent platforms for engagement on equipment design requirements are recommended.

Feb 2, 2021

By L. Diko-Makia, N. Rembuluwani

Artisanal and small-scale mining is crucial for the mineral sector in South Africa, but it also presents both opportunities and challenges. This paper presents an overview of the South African artisanal and small-scale mining sector, the socio-economic significance of artisanal and smallscale mining, the regulatory environment, and the environmental impacts, which are currently the status quo of this sector in South Africa. The paper identified ways in which artisanal and small-scale mining can support local development, create employment opportunities, and reduce poverty. The case of informatisation, ecological damage, and social insecurity has shown social conflicts, potential land degradation, and criminal behaviour. Finally, the paper discusses the future of artisanal and small-scale mining in South Africa, which will largely depend on improved legislation, enhanced personnel capacity, and more sustainable practices to ensure that the positive outcomes of the industry outweigh the negative ones. These propositions include recommendations to all stakeholders, including the government, industry, and civil society, such as stricter environmental regulations, improved working conditions for miners, and the promotion of responsible mining practices.

Dec 15, 2025

By R. B. Khumalo, T. Chauke, T. Mtshali, F. K. Mulenga, B. Makgate, N. M. Chiloane, T. Moyane, V. C. Madanda

While high production rates are important for the profitability of a mine, the influence of geotechnical engineering cannot be ignored. In block caving, a high-stress level is required for cave propagation; this is one of the core elements for ore recovery. Therefore, stress distribution and geological structures play a major role in the planning and layout design of the mine. This paper explores the influence of stress and geological features on the design of the mine from the feasibility study phase. The geology and stress measurement of the mine were determined through logging and overcoring, respectively. This study found that while production rate is the primary operational consideration, the long-term layout design of the undercut face advance, face angle, drawpoint spacing, and undercutting sequence is mainly governed by the stress orientation and major geological structures. Moreover, widely spaced drawpoints result in isolated draw zones, consequently, resulting in ore loss and early dilution whereas closely spaced drawpoints affect the stability of the major apex pillar. This paper also provides insight into how operations can leverage stress distribution to optimise mine layout and safety in massive mining methods.

Nov 24, 2025

By R. Nyirenda, B. Besa, N. Dzimunya

The accurate estimation of peak particle velocity (PPV) is crucial during the design of bench blasting operations in open pit mines, since the vibrations caused by blasting can significantly affect the integrity of nearby buildings and other structures. Conventional models used to predict blast-induced vibrations are not capable of capturing nonlinear relationships between the different blasting-related parameters. Soft computing techniques, i.e., techniques that are founded on the principles of artificial intelligence, effectively model these complexities. In this paper, we use the random forest (RF) algorithm to develop a model to predict blast-induced ground vibrations from bench blasting using 48 data records. The model was trained and tested using WEKA datamining software. To build this model, a feature selection process using several combinations of Attribute Evaluators and Search Methods under the WEKA Select Attributes tab was performed. The correlation coefficient of the actual data and RF model-predicted data was 0.95, and the weighted average of the relative absolute error (RAE) was 10.9%. The RF model performance was also compared to the equivalent-path-based (EPB) equation on the testing data-set, and it was seen that the RF model can effectively be used to predict PPV. The study also demonstrates that the EPB equation is a suitable empirical method for predicting PPV.

Mar 30, 2023

By A. Navarra, A. Quelopana

The mine production scheduling problem (MPSP) has been studied since the 1960s, and remains an active area of computational research. In extending the concepts of the MPSP, the automated mine may now be regarded as a hierarchical intelligent agent in which the bottom layer consists of distributed robotic equipment, while strategic functionality occupies the higher layers. Here we present a disambiguation of artificial intelligence, machine learning, computational optimization, and automation within the mining context. Specifically, the Q-learning algorithm has been adapted to generate the initial solutions for a high-performing strategic mine planning algorithm, originally developed by Lamghari, Dimitrakopoulos and Ferland, based on the variable neighbourhood descent (VND) metaheuristic. The hierarchical intelligent agent is presented as an integrative conceptual platform, defining the interaction between our new Q-learning adaptation and Lamghari’s VND, and potentially other hierarchically controlled components of an artificially intelligent mine, having various degrees of automation. Sample computations involving Q-learning and VND are presented.

Dec 1, 2021

By B. Genc, P. Malepfane

This study proposes a new approach to reduce the environmental impact during surface mining by improving environmental factors through the incorporation of carbon footprint into strategic mine planning. Two key variables were analysed by contrasting and comparing the baseline and optimised models generated. These variables include net present value, which helps determine the financial feasibility of the mining models and their carbon emissions. The variables were analysed by using linear regression, Spearman’s correlation, a P-value hypothesis, and an exponential decay test. Results show that at Mine A the projected net present value was 62% higher than when running a baseline model. Furthermore, the net present value from the baseline model portrayed a high rate of decay at 0.667 versus 0.118 from the optimised model. This indicates the baseline model’s sensitivity to long-term project timelines and fluctuating markets. The optimised method presents an opportunity to manage emissions during the high operational costs phases. It is represented by a 31% improvement in carbon emissions during the periods of high operational costs, whilst maintaining a positive net present value when compared with the baseline model. It was shown that the optimised model presents a better chance of achieving financial feasibility and balancing environmental impact, thereby ensuring that Mine A can align with the environmental aspect of economic, social, and governance principles through lowering the carbon footprint resulting from its hauling operations.

Jan 30, 2026

By N. J. Wagner, D. G. Modiba

There is currently limited knowledge concerning South African coal deposits as hosts for rare earth elements (REE). This project aims to determine the concentration of REE, including yttrium and scandium (REY+Sc) in various coal seams and adjacent sediments in borehole cores from the Ermelo, Witbank, and Waterberg coalfields in South Africa. Coal petrography (maceral count and vitrinite reflectance), XRD, XRF, sequential chemical extraction procedure (SCEP) before ICPMS, and mineral liberation analysis (MLA) were conducted on the coal and associated sediment samples. The coals were inertinite-rich, medium-rank bituminous coal, with moderate to high ash content. The two dominant minerals in all the coalfields are kaolinite and quartz, except for sample ZBS2M, where dolomite was dominant. The dominant major oxides are Al2O3, SiO2, Fe2O3, and CaO, which concur with the XRD results. The ICP-MS results following SCEP indicated that both coal and the associated sediments were light REY+Sc dominant. There was also an elevation of medium REY+Sc in the Witbank coal’s associated sediment samples. Notably, the samples with the highest REY+Sc results were the sediment samples. The Waterberg samples had the lowest REY+Sc from both the coal (less than 2 μg/g to 7 μg/g) and associated sediments (2 μg/g to 15 μg/g). While the highest REY+Sc was yielded from the Witbank-associated sediments (500 μg/g to 2,500 μg/g). The carbonate fraction step proved to be the most successful leaching step, as most REY+Sc was recovered in that step for all coalfields. In addition to the carbonate fraction, the silicates and sulfide fraction in the Witbank samples, and the ion-exchangeable fraction for the Waterbergassociated sediments samples proved successful in leaching out the REY+Sc. MLA determined that monazite and xenotime in all the coal samples were the REY+Sc-bearing minerals.

Nov 6, 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

By W. C. Joughin

The science of soil mechanics is 100 years old, and rock mechanics is about 80 years old. While methods of analysis and design have been developed and have evolved over time, these are relatively young sciences. The rapid increases in computing power and new technologies have enabled more sophisticated modelling and monitoring. However, there are still many aspects of soil and rock mechanics that are not well understood. Geotechnical failures, which have major consequences, still occur. These consequences may include environmental damage, major production holdups and associated loss of revenue, damage to infrastructure, and loss of life. High-consequence events, which are rare, are more difficult to anticipate and to design for, because by their nature they involve extraordinary circumstances or conditions, often geological in nature. The risks are usually mitigated by conservative designs and monitoring. Detailed geotechnical investigations help us to understand the natural variability of soil and rock masses and identify unusual or unexpected conditions. Investigating and researching major geotechnical failures is essential to enable these unusual circumstances to be anticipated. In the past, severe unanticipated events may have been treated as natural events or ‘acts of God’. However, society now has much greater expectations and it is essential to have policies and procedures in place that enable appropriate management of these rare, high-consequence risks. A good example is the Global Industry Standard on Tailings Management (GISTM), which was introduced after the catastrophic dam collapse at Vale’s Corrego de Feijao mine in Brumadinho, Brazil. The address will explain the concepts of uncertainty and variability, and how they should be taken into account in geotechnical design. The challenges facing geotechnical engineers, mine owners, and managers will be discussed. referencing a number of real case studies.

Sep 6, 2023