Search Documents

By M Jara, R Nuñez

As the global interest in sustainable energy sources has increased, lithium has emerged as a vital resource, playing a crucial role in the transition towards a cleaner and more efficient economy, but with this comes important challenges, especially associated to health, safety, and environmental matters. So, it is imperative for the lithium industry to prioritise HSE measures to protect workers, environment and surrounding communities. Implementing robust safety protocols and technology helps ensure the sustainability of mining operations and contributes to the overall responsible development of the industry. In this work we present how the Chilean lithium mining industry becomes a safer and more compliant industry using digital transformation (Cochilco, 2018; Bradley et al, 2013; Cabello, 2022).

Apr 16, 2024

By M Alston

Organisations’ incident classification processes are plagued by the overclassification of events, often leading to excessive workloads and suboptimal outcomes. This presentation addresses the pressing need to rethink how incidents are classified to maximise organisational learning and minimise systemic risk. A major issue in the current incident classification landscape is the tendency to classify events at high levels, overwhelming organisations with investigations they cannot efficiently handle. This results in inadequate risk reduction and learning opportunities. The link between injury classification and investigation methods further compounds these problems, creating unnecessary administrative clutter. Challenging the misconception that every event, no matter how minor, requires a comprehensive investigation, this presentation advocates for a shift in perspective. The key recommendation is to decouple injury classification and risk matrices from the decision-making process regarding what and how to investigate. Instead, the emphasis should be placed on identifying opportunities for organisational learning and risk reduction. Organisations can streamline their incident management processes by adopting a more pragmatic approach that aligns incident classification with the organisation’s investigation capacity. This transformation focuses on achieving meaningful outcomes, enhancing safety and improving performance. This presentation provides an innovative process for organisations to revamp their incident classification practices, enabling them to harness the full potential of incident data for learning and risk mitigation. It highlights the importance of aligning incident classification with the opportunity for organisational learning, ultimately leading to more effective incident management and enhanced safety outcomes.

Apr 16, 2024

By A. Chuma, K. J. Nyembwe, H. Simonsen, J. H. Potgieter

Different concentration techniques were evaluated for preconcentration of a mineral ore at a coarser size to avoid energy and resource wastage. Specifically, the aim was to reduce milling costs and energy required in the beneficiation of tin. In this study, cassiterite (0.17% Sn) was the mineral of interest in a pegmatite ore body associated with quartz (SiO₂ > 60%) and alumina (Al₂O3 > 20%). Three concentration techniques, namely dense media, shaking table, and flotation, coupled with characterization analysis, were used to assess the concentration response. The results confirmed that particle size and mineral liberation impact the separation process. High recovery and grade were obtained with gravity concentration methods (dense media and shaking table) for coarser (+300 to +212 μm) and intermediate (+150 to +53 μm) particle sizes. Lower recovery and grade were identified for much finer sizes (−53 to −38 μm). Flotation produced a high-grade product at a relatively low recovery and appeared to be only applicable to finer grains. Separation efficiency based on Schulz’s equation measured a segregation performance of 74.8% for dense medium separation and 60.7% for the shaking table for the coarse and intermediate particle sizes. Flotation only achieved a separation of 30%–40%. The results suggest that use of dense media separation as a rough preconcentration method prior to further grinding, and the utilization of a more advanced concentration technique for mineral recovery and upgrade, constitute a successful approach to improve process economics.

Apr 14, 2024

By G. Akdogan, M. Tadie, A. Tapfuma

The Southern African region contains abundant gold tailing heaps that are an environmental concern due to dust pollution and chemical contamination of nearby water bodies. Nevertheless, these heaps contain gold with potential to be extracted for financial gain. In this study, the feasibility of extraction of gold from a Witwatersrand gold tailings using glycine was investigated using a two-level full factorial design. Effects of variables such as glycine concentration at levels of 0.5–1.5 M with a solid–liquid ratio of 50–200 g/L were investigated. Although the solid–liquid ratio used in this study was below the industrial norm, it provides a starting point for investigating the applicability of this technology. To enhance the gold extraction, potassium permanganate pretreatment and copper ion addition were adopted. The results revealed that 91.4% gold extraction was achieved after 24 h pre-treatment of the tailings using 2 g/L potassium permanganate followed by subsequent leaching using 1.5 M glycine at pH 12, with 50 g/L solid–liquid ratio and 2 g/L copper ions. Statistically, the solid–liquid ratio and potassium permanganate pre-treatment of the tailings were found to be significant at 95% confidence interval, whilst interactions of copper ions and glycine concentration were significant factors. The work demonstrates that potassium permanganate pre-treatment prior to glycine leaching of low-grade secondary gold resources, such as tailings, can be beneficial. Furthermore, the methodology developed in this work provides an opportunity for further investigation of the recovery of gold hosted in complex mineralogical matrices.

Apr 14, 2024

By N. Coulson, P. F. Stewart

The Mine Health and Safety Act No. 29 of 1996, as amended, embeds an occupational health and safety management system that facilitates communication between representatives of the state, capital, and labour. In underground mines, two communication loops between these role players serve to separate the production chain of command from the political tripartite relations. Worker-elected health and safety representatives are involved in both communication loops, but are severely constrained in escalating their occupational health and safety concerns to the legalpolitical level. This has a direct bearing on the exercise of the Right to Refuse Dangerous Work (RRDW). As previously reported, health and safety representatives were found to primarily consult their production supervisors in preference to their trade-union representatives. This follow-up article presents production supervisor perspectives on the RRDW. The study demonstrates how, for mineworkers, the two distinct communication subsystems constrain, rather than facilitate, implementation of the RRDW.

Apr 14, 2024

By K. Barani, S. M. S. Ganji

Creatine was used as a lixiviant for gold dissolution from gold ore. The effects of creatine concentration, temperature, leach time, and pH were examined for their influence on extent of gold dissolution. The results show that at a temperature of 75°C and pH 11.5, gold dissolution increased from 51% to 88% on increasing creatine concentration from 25 to 50 g/t. Further increase in creatine concentration showed a negative effect on the gold dissolution. Gold dissolution increased from 47% to 87% by increasing the temperature from 25°C to 55°C, and from 61% to 89% by increasing pH from 10 to 11.5. Under the optimum conditions of solids’ content of 30%, pH 11.5, creatine concentration of 100 g/t, temperature of 75°C, and hydrogen peroxide addition of 2%, about 90% of the gold could be dissolved from the ore after 24 h. A comparison between creatine and cyanide leaching showed that 90% gold dissolution was achieved at a cyanide concentration of 300 g/t, which is three times higher than the creatine concentration under optimal conditions.

Apr 14, 2024

By Z. Zhang, J. Niu, H. Wang, Y. Xu, J. Shi

Tribo-electrostatic separation is a promising method for effectively utiliing low-grade magnesite resources by removing quartz and improving the grade of magnesite. To determine the chargeto- mass ratios of pure magnesite and quartz, a triboelectric measurement system was employed, and a laboratory tribo-electrostatic separation system was used to separate low-grade magnesite. The results showed that the maximum difference in charge-to-mass ratio between pure magnesite and quartz particles was observed after friction with polyvinyl chloride. The grade and recovery of magnesite increased with temperature and initially increased with increasing voltage, feed rate, and air flowrate before gradually decreasing. The optimal conditions resulted in a concentrate with 46.91% MgO content and 77.36% recovery, while the quartz content decreased from 7.02% to 1.95%. These experimental results demonstrate the effectiveness and potential of tribo-electrostatic separation in removing quartz and upgrading magnesite.

Apr 14, 2024

By V. W. Lumadi, S. Nyasha

The mining industry has yet to fully accept and embrace the strategic role of technology and innovation in successful business planning and execution. In this study, we empirically determine the factors that influence acceptance of technology solutions in the mining industry in South Africa, assess critical success factors influencing adoption of advanced technology in the South African mining industry, and explore challenges faced by the mining industry in South Africa in adopting advanced technology in its operations. Thematic content analysis is employed in the data analysis. Results show that critical success factors to the adoption of mining technology include learning culture, knowledge sharing, high labour costs, and behaviour of other firms in the industry; commonly identified challenges include inadequate engagement with external stakeholders, uncertainties, the cyclical nature of the sector, and high risk related to the adoption of unproven technology and performance systems focused on volumetric production. The study encourages mining companies to implement usage of technology. This can be properly done through regular engagement with the Minerals Council South Africa.

Apr 14, 2024

By K. Karaman

This study investigated the effect of surface roughness on Schmidt rebound hardness (RL). Four different test surfaces of rock samples were studied: natural, ground, cut surfaces, and core samples. There was significant variability of standard deviation based on the RL on the natural surface, which indicated high roughness of the rock surface, whereas surface polishing caused a significant decrease in standard deviation. ISRM and ASTM methods were compared to estimate unconfined compressive strength (UCS) for different testing surfaces. RL obtained from the cut surface was found to be more reliable than those obtained from other testing surfaces for the prediction of UCS; however, regression and ANOVA analyses revealed that the ISRM method gave a more accurate UCS estimation of rocks with highly rough surfaces. It was also shown that RL values obtained from a cut surface were significantly higher than those obtained from core samples. Therefore, a comparison between RL values obtained from core samples and cut surfaces was made based on previous studies. This study statistically showed that estimated UCS values are not statistically significant if Schmidt rebound tests are not performed on similar surfaces. In addition, the mineral grain sizes of the studied rocks, different testing surfaces compared with those in literature, and standard deviation from RL are evaluated and discussed. The Schmidt hammer technique is a rapid, inexpensive, and straightforward method for estimating UCS for preliminary assessment; however, roughness of the surface should be eliminated if variations are shown in the surface rebound hardness.

Apr 14, 2024

By N. C. Steenkamp

Lightning has been observed in dust clouds following open-pit blasting. It is proposed that the occurrence of this phenomenon is related to the physical composition and characterization of the mineral fines that comprise the bulk of the dust cloud. Silicate minerals, which are susceptible to fine fracturing during blasting, generate the initial charge. This is further enhanced by collisions and friction during the turbulent upcast in the post-blast dust cloud. Varying size fractions result in different rates at which these particles drop out of suspension and create a secondary temperature gradient. This results in the creation of two charged zones and increases the potential of developing a discharge in the form of lightning. The ideal prevailing meteorological conditions need to be windless to minimize the effect of particle dissipation and have sufficient moisture toenhance the potential of generating lightning.

Apr 14, 2024

By Martin Langenderfer, Catherine Johnson, Alexander Douglas

Mine haul roads degrade rapidly due to extreme loads on suboptimal construction materials. Unmanned aerial vehicles (UAV) are suited to quantify large-area road-network conditions, such as surface roughness, defects and grade to optimize remediation of poor conditions and reduce overall costs. Mine haul roads present unique challenges, such as material type and edge characteristics, to automatic road detection that often fails, requiring manual road input. This research work proposes a new method using the road center determined by the principal curve of a haul truck’s path. Analysis grids were created from this center line. A dense point cloud from UAV photogrammetry was generated and multiple linear regression analysis was conducted on each individual grid. The root-mean-square error in each grid indicates the surface roughness, and the change of slope between grids indicates the road grade inconsistencies. This method was applied to 26 road sections, and the results were validated by images taken from the truck operator’s vantage point. Critical defects were identified including excessive pothole formation, corrugation, depressions retaining water, and narrowing of travel lane. The results demonstrate this is a valid method of road identification and quantification of road defects at a mine site.

Apr 1, 2024

By Philani Larrance Ngwenyama, Ronald CW Webber-Youngman

The survival chances of trapped miners in underground mines depend on how quickly they can be located and rescued post-accident. During entrapments, emergency rescue is highly desired but can be hindered by the lack of positioning information when a fit-for-purpose missing-person locator system is not available. Various types of missing-person locator systems are available to aid search-and-rescue operations. From the wide range of the available systems, selecting the most suitable one becomes the next challenge. The available systems have not been measured if they are fit-for-purpose or not, and to what situation. This study proposes user requirements that can be used as a guideline to facilitate the system selection process. These user requirements provide a framework for the design and development of a fit-for-purpose missing-person locator system. The user requirements can also be used for evaluating the performances of a particular system, predict its success, and also drive future research toward developing new technology to enhance the capabilities of the current systems.

Apr 1, 2024

By Xuebin Liu, Yi Shang, Can Zhou, Hongqiu Zhu, Junbo Du

In the neutral leaching process of zinc hydrometallurgy, the pH value directly affects the leaching rate of zinc calcine. However, due to the complex mechanism of the leaching process and frequent fluctuation of working conditions, it is difficult to control the pH value by manual control. Therefore, this study proposes a fuzzy control method based on rule extraction under multiple working conditions, and analyzes the pH control performance. Firstly, the different operating states are classified according to process mechanisms and the Pearson method. Secondly, under the framework of the active learning algorithm, the approximate linear dependence (ALD) method is introduced to iteratively select samples with rule information in the original sample set for manual annotation. Then, the support vector machine (SVM) method is used to extract fuzzy control rules in different working conditions. Finally, a fuzzy rule set is established according to the samples mapped by the support vector. The simulation results based on industrial data show that the proposed method has better control performance than conventional fuzzy control and proportional–integral–derivative (PID) control.

Apr 1, 2024

By Ricardo Oliveira Gallart de Menezes, Claudio Gerheim Porto, Reiner Neumann

The Jiboia heavy mineral sands deposit is a new discovery associated with the São Francisco River delta on the northern coast of Sergipe state. The identified resources are part of the much larger mineralized trend. Mineralization is hosted in paleodunes deposited on Holocene marine terraces (Fig. 1). The dunes are up to 30 m above sea level, and mineralization occur from 6 m above sea level upward. The main ore minerals constitute pseudorutile, ilmenite, zircon, rutile and monazite. This work presents a thorough characterization of the mineralogy and granulometric distribution of the Jiboia orebody.

Apr 1, 2024

By Arman Hazrathosseini, Ali Moradi Afrapoli

Fleet management systems (FMSs), as a pivotal part of any surface mining operation, need to evolve from conventional to intelligent systems because of both Mining 4.0 requirements and some shortcomings inherent in conventional methods. However, this novel transformation needs to be investigated technically and strategically. To this end, previously published research works on intelligent FMSs are explored to track the latest status of these third-generation frameworks within the surface mining context. Their underlying models are then compared in terms of five categories of allocation and dispatching features to pinpoint the technical gaps ignored. Having drawn the future lines of research, the present work then leverages the popular SWOT analysis method to outline the strengths, weaknesses, opportunities, and threats associated with the advent of these intelligent FMSs in mines of future. By and large, the analysis indicates that advantages outweigh disadvantages. Solutions are offered to address the existing weaknesses and threats.

Apr 1, 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 J. P. Gouvea

Back-analysis of two mining-induced tremors in 2011 was used to determine a modelling criterion for the entire Klerksdorp Goldfield (i.e., Vaal Reefs region). At that time, most mining operations in the region were owned by AngloGold Ashanti (AGA) and shared many geotechnical similarities. By 2018 AGA had sold off all its Klerksdorp operations to different mining companies, which continued applying the 2011 modelling criterion. As mining activities became more remote, scattered, and isolated, the extraction of isolated blocks of ground and remnants became increasingly necessary. However, the inherited criterion allowed only minimal or no mining activities at these areas. Keeping in mind that safety is the overriding consideration, an innovative numerical modelling approach, which includes the application of peak particle velocity designs, was developed to provide practitioners in the Klerksdorp Goldfield with a suitable criterion to justifiably and safely mine isolated blocks of ground and remnants. This would not always be possible if a conformist approach was used.

Mar 14, 2024

By W. Bendaikha, S. Larbi, A. Ramdane

An oolitic iron ore from Gara Djebilet, Algeria was characterized by X-ray diffraction, scanning electron microscopy, and energy dispersive spectrosopy and the phosphorus distribution between various phases studied. Two ore types were identified – a haematite-dominated, oolitic type and a more massive, magnetite-dominated type. The haematite-dominated ore had a higher phosphorus content, up to 0.6% in the iron oxide minerals, than the magnetite-dominated type (0.3% P). Owing to the very fine-grained texture of the gangue minerals, reducing the phosphorus content to levels suitable for steelmaking (below 0.05% P) by conventiobal means would entail an energyintensive process with a high carbon footprint. Preliminary leaching test work using a sulphurous geothermal water as lixiviant, assisted by solar thermal acceleration, gave very promising results, removing 0.13% of the residual P (or 21.7% removal of total P) from the high-phosphorus oolitic ore.

Mar 14, 2024

By S. Swanepoel, A. V. Cherkaev, Q. G. Reynolds, M. Erwee

Ferrochrome (FeCr) is a vital ingredient in stainless steel production and is commonly produced by smelting chromite ores in submerged arc furnaces. Silicon (Si) is a componrnt of the FeCr alloy from the smelting process. Being both a contaminant and an indicator of the state of the process, its content needs to be kept within a narrow range. The complex chemistry of the smelting process and interactions between various factors make Si prediction by fundamental models infeasible. A data-driven approach offers an alternative by formulating the model based on historical data. This paper presents a systematic development of a data-driven model for predicting Si content. The model includes dimensionality reduction, regularized linear regression, and a boosting method to reduce the variability of the linear model residuals. It shows a good performance on testing data (R2 = 0.63). The most significant predictors, as determined by linear model analysis and permutation testing, are previous Si content, carbon and titanium in the alloy, calcium oxide in the slag, resistance between electrodes, and electrode slips. Further analysis using thermodynamic data and models, links these predictors to electrode control and slag chemistry. This analysis lays the foundation for implementing Si content control on a ferrochrome smelter.

Mar 14, 2024

By I. Ince, S. Kahraman, M. Rostami, B. Dibavar

The density, porosity, and strength of rocks are fundamental in the design of geo-engineering projects. Determining these properties requires the preparation of smooth core samples, which is usually impossible for soft rocks. Besides, only fragmented samples may be available in some projects. A method for predicting rock properties from rock particles such as drilling debris would therefore be useful. This study was undertaken to develop prediction equations for compressive strength (UCS), tensile strength (BTS), density, and porosity values from the crushability index (CI) obtained from rock fragments. The results showed that UCS, BTS, density, and porosity were strongly correlated with the CI. The physical characteristics and strength of rocks may be predicted with the help of the derived equations. The CI test is a valuable tool for estimating rock properties in drilling projects and in situations where core specimens are not available.

Mar 14, 2024