School of Mining Engineering (ETDs)

Permanent URI for this communityhttps://hdl.handle.net/10539/37974

Browse

Now showing 1 - 20 of 39

A Data Science Framework for Mineral Resource Exploration and Estimation Using Remote Sensing and Machine Learning
(University of the Witwatersrand, Johannesburg, 2023-08) Muhammad Ahsan, Mahboob; Celik, Turgay; Genc, Bekir
Exploring mineral resources and transforming them into ore reserves is imperative for sustainable economic growth, particularly in low income developing economy countries. Limited exploration budgets, inaccessible areas, and long data processing times necessitate the use of advanced multidisciplinary technologies for minerals exploration and resource estimation. The conventional methods used for mineral resources exploration require expertise, understanding and knowledge of the spatial statistics, resource modelling, geology, mining engineering and clean validated data to build accurate estimations. In the past few years, data science has become increasingly important in the field of minerals exploration and estimation. This study is a step forward in this field of data science and its integration with minerals exploration and estimation. The research has been conducted to develop a state-of-the-art data science framework that can effectively use limited field data with remotely sensed satellite data for efficient mineral exploration and estimation, which was validated through case studies. Satellite remote sensing has emerged as a powerful modern technology for mineral resources exploration and estimation. This technology has been used to map and identify minerals, geological features, and lithology. Using digital image processing techniques (band ratios, spectral band combinations, spectral angle mapper and principal component analysis), the hydrothermal alteration of potential mineralization was mapped and analysed. Advanced machine learning and geostatistical models have been used to evaluate and predict the mineralization using field based geochemical samples, drillholes samples, and multispectral satellite remote sensing based hydrothermal alteration information. Several machine learning models were applied including the Convolutional Neural Networks (CNN), Random Forest (RF), Support Vector Machine (SVM), Support Vector Regression (SVR), Generalized Linear Model (GLM), and Decision Tree (DT). The geostatistical models used include the Inverse Distance Weighting (IDW) and Kriging with different semivariogram models. IDW was used to interpolate data points to make a prediction on mineralization, while Kriging used the spatial autocorrelation to make predictions. In order to assess the performance of machine learning and geostatistical models, a variety of predictive accuracy metrics such as confusion matrix, a receiver operating characteristic (ROC) curve, and a success-rate curve were used. In addition, Mean Absolute Error, Mean Square Error, and root mean square prediction error were also used. The results obtained based on the 10 m spatial resolution show that Zn is best predicted with RF with significant R2 values of 0.74 (p < 0.01) and 0.7 (p < 0.01) during training and testing. However, for Pb, the best prediction is made by SVR with significant R2 values of 0.72 (p < 0.01) and 0.64 (p < 0.01) for training and testing, respectively. Overall, the performance of SVR and RF outperforms the other machine learning models with the highest testing R2 values. The experimental results also showed that there is no single method that can be used independently to predict the spatial distribution of geochemical elements in streams. Instead, a combinatory approach of IDW and kriging is advised to generate more accurate predictions. For the case study of copper prediction, the results showed that the RF model exhibited the highest predictive accuracy, consistency and interpretability among the three ML models evaluated in this study. RF model also achieved the highest predictive efficiency in capturing known copper (Cu) deposits within a small prospective area. In comparison to the SVM and CNN models, the RF model outperformed them in terms of predictive accuracy and interpretability. The evaluation results have showed that the data science framework is able to deliver highly accurate results in minerals exploration and estimation. The results of the research were published through several peer reviewed journal and conference articles. The innovative aspect of the research is the use of machine learning models to both satellite remote sensing and field data, which allows for the identification of highly prospective mineral deposits. The framework developed in this study is cost-effective and time-saving and can be applied to inaccessible and/or new areas with limited ground-based knowledge to obtain reliable and up- to-date mineral information.
A holistic approach to the design of two tonnes temporary support systems (nets, mechanical props, hooks and roof bolt face plates)
(University of the Witwatersrand, Johannesburg, 2024) Modika, Moses
In 2019, Thembelani Mine experienced a high number of injuries caused by Falls of Ground (FOGs) in the face area. To address this issue, safety nets with a capacity of two tonnes were urgently introduced. The two tonnes safety nets were intended to hold FOGs with a maximum mass of 1.78 tonnes, thereby providing a factor of safety of 1.1. However, in 2020 a FOG accident occurred during a drilling shift when a rock with a mass of 1.65 tonnes fell, leading to the death of an employee. The square headboard mechanical props with headboard dimensions of 130 mm x 130 mm, which were supposed to hold the safety net, were pulled out by the FOG, thereby allowing the safety net to collapse with the FOG. The slipping out of the square headboard mechanical props was due to a smaller headboard surface area of 130 mm x 130 mm in contact with hangingwall and a pretensioned load of 0.86 tonnes to 1.43 tonnes which could not sustain a falling rock with a mass of 1.65 tonnes. As a result, the square headboard props were immediately replaced with T-shaped Grease box mechanical props with average pretension load of 2.23 tonnes, larger and longer headboards of 370 mm x 100 mm to increase resistance to slipping out. The T-shaped Grease box mechanical props come with 16 mm flexible G-hooks attached to the headboards. The T-shaped Grease box mechanical props were tested at a drop test facility together with two tonnes Rock- stop safety nets and found to be able to hold two tonnes mass when installed at a standard spacing of 1.5 m x 1.5 m. This indicated that components of the temporary support systems other than the two tonnes Rock-stop safety net were not considered during the roll out. These components include 12 mm diameter flexible G-hooks, roof bolt face plates with a thickness of 4.5 mm, and square headboard mechanical props with welded 12 mm U-hooks and headboard dimensions of 130 mm x 130 mm. Therefore, it was decided to conduct a study to test the temporary support systems holistically using installation scenarios as practiced at Thembelani Mine as opposed to testing each of the constituents of the systems individually. The aim of the tests was to assess if all components fulfil the requirements of the two tonnes temporary support systems from system test point of view. iv While conducting the study, it was found that the safety nets were introduced without considering all aspects of the temporary support systems, such as safety net deflection parameters, hooks, mechanical props, and roof bolt face plates. Moreover, it is necessary to maintain a safe working height within a specific stoping width, which is the vertical distance between the footwall and the safety net in the hangingwall after holding a falling rock. This is to ensure that the employee underneath the net does not get struck by the FOG which deflected with the safety net. The study aimed to identify the items that did not meet the two tonnes systems' requirements and recommend improvements to ensure they function as expected. The study was conducted at available drop test facilities such as NCM and Videx, simulating the installation scenarios as practiced at Thembelani Mine. The study revealed that the two tonnes Rock-stop safety nets, along with 6 mm face plates, 14 mm Carbon steel S-hooks, or 14.5 mm Spring steel G-hooks, fulfilled the requirements for the two tonnes systems. The two tonnes Rock-stop safety nets and T-shaped Grease box mechanical props with flexible 16 mm G- hooks also fulfilled the two tonnes’ requirements. The study determined that the systems that fulfilled the two tonnes’ requirements were effective for all stopes at Thembelani Mine with heights of 1.2 m and 1.4 m and flat excavation ends with a height of 3.2 m, with deflection limits of 0.35 m, 0.55 m and 1.3 m respectively. In 2022, an alternative to the safety nets, the MINAX 80/3 Blast-on Mesh (BOM) with 8 mm blast-on cable, was introduced. The BOM underwent a similar study to the Rock-stop safety net, and the drop tests showed that the deflections obtained with the BOM in various scenarios as installed at Thembelani Mine were all above 0.35 m but less than 0.55 m. Hence, BOM can be used in stopes and flat excavations with heights of 1.4 m and 3.2 m, respectively.
An assessment of the Angolan mineral taxation regime: considerations for possible improvements on government´s revenue
(University of the Witwatersrand, Johannesburg, 2024) Africano, N´djamila Hilifavale Borges; Mtegha, Hudson
Angola is host to 36 of the 51 critical minerals in the world and ranks third in mineral exports, totalling over USD 1 billion in 2020, and third in diamond production; Botswana and South Africa hold the top two slots, respectively. These untapped opportunities make the Angolan mining industry an excellent place to invest despite the mining industry contributing less than 1% to GDP and has yet to become a driver of economic diversification. In June 2022, Angola joined the EITI, bringing a welcome improvement in the transparency of the sector´s governance and reform, intended to attract new investors. The study evaluates the effectiveness of the Angolan mineral fiscal system as a tool for maximising revenue for the benefit of its citizens and securing investment (local and foreign) to promote linkages and broad-based national growth and development. Four objectives were examined in this study: (i) Conduct a situational analysis of the current fiscal regime through a comparative analysis of headline rates in regional and international countries; (ii) Qualitative evaluation of the effectiveness and efficiency of the mineral fiscal regime; (iii) Analyse the tax revenues raised by the mining industry between 2011-2021; (iv) Make possible recommendations to improve the current mining tax regime. The study employed a descriptive survey design with a qualitative and quantitative approach for data collection and analysis. The main findings include: (i); Angola's political economy setting resembles that of a hegemonic government characterised by an institutionalised one-party regime whereby the implications on the mineral fiscal regime are multifaceted, affecting investment, regulation, revenue sharing, and sustainability; (ii) Both mineral royalty and corporate income tax rates, are within regional and international norms and have consistently contributed a significant share of the government's direct tax revenues over the last eleven years; (iii) Prevailing fiscal regime can be improved through a combination of tax instruments such as resource rent-tax or profit-based royalty with a basic ad valorem tax system; (iv) However, Angola’s primary challenges point to a possible absence of enforcement and compliance mechanisms for both the mining code iii and the sector fiscal framework, as well as the need to strengthen government agency capacity to oversee and gather fiscal contributions from the sector. In light of these findings, it is recommended to (i) Improve the sector's mining code and fiscal legislative framework and enforce it; (ii) Conduct a study to analyse the effects of all government taxes (direct tax, indirect tax and non-tax instruments and tax incentives) on both the industry and the government´s treasury; and (iii) Conduct further studies on the proposed optimal mineral fiscal regime. Finally, an effective, efficient, and transparent mineral fiscal system can only exist first and foremost through intentional collaboration and alignment of objectives among the sector’s stakeholders.
An investigation into equity market timing practices by South African mining companies
(University of the Witwatersrand, Johannesburg, 2024) Matumba, Lindelani
This research examines the practice of equity market timing among 30 Johannesburg Stock Exchange (JSE)-listed mining companies from 2006 to 2022. Mining companies, characterised by their capital-intensive nature, rely on management for optimal capital management, which includes both the acquisition of capital through debt or equity and its optimal allocation. The concept of equity market timing, introduced by Wurgler and Baker in the 1990s, suggests that company management may engage in timing the equity market when they perceive their stock to be mispriced. This study incorporated control variables such as market-to-book value (a relative valuation metric that investors use to assess a company's market value in relation to its book value), asset tangibility, degree of leverage, and profitability. Panel regression analysis, utilising both fixed effects and random effects, revealed that market-to-book value was not statistically significant at the 5% level. The overall R-squared value was 58.8%. Given the lack of significance for market-to- book value and asset tangibility, it is recommended to consider other capital structure theories, such as the pecking order or trade-off theory. Additionally, incorporating variables like interest rates and other macroeconomic factors could help address the potential for omitted variable bias.
Analysis of factors affecting rehabilitation of abandoned mines in South Africa: cases on asbestos projects
(University of the Witwatersrand, Johannesburg, 2024) Meyerowitz, Reuben Benjamin
Asbestos was once mined in South Africa using traditional methods. Unfortunately, the exploitation of asbestos severely impacted both workers and the surrounding communities. In 2008, the government stopped asbestos mining and designated the abandoned mines as Derelict and Ownerless (D&O) Mines. This was done to mitigate the serious health and safety risks associated with asbestos mining. The aim of the programme was also to address the negative environmental impacts caused by abandoned mines on local areas and social environments. Since 2009, the MINTEK’s D&O programme has rehabilitated 38 mines. However, the rehabilitation of these mines has been affected by various factors that have impacted the Derelict and Ownerless mining projects. This study aims to identify and understand the factors that affect abandoned mine projects in South Africa. The study also aims to provide a comprehensive analysis of the identified impacts and provide recommendations to ensure the successful implementation of the D&O projects. The study used a mixed-method approach to collect both quantitative and qualitative data. The methodology involved data collection from various sources such as recorded reports, financial statements, spreadsheets, engineer reports, project progress reports, construction programs, and document analysis. The study focused on 32 asbestos mining projects in four provinces, namely Northern Cape, Limpopo, KwaZulu Natal, and Mpumalanga, which were used as case studies. The rehabilitation of abandoned asbestos mines is a challenging task that requires collaboration, innovation, and concerted efforts. The factors affecting the implementation of the rehabilitation projects include slow decision-making by the contractors before and during construction, internal challenges faced by the contractors, time delays in material and stock deliveries, community resistance, specific project team experience, influence of external stakeholders and others. These can be categorized into six areas, namely, technical, economic, management, psychological, political and legislative. The study has revealed that all factors identified in the research have a direct impact on rehabilitation projects and contribute to failures in meeting targets in terms of costs and time. In conclusion, the analysis of technical, economic, psychological, and political factors in the rehabilitation of abandoned mines iv in South Africa also highlighted the interconnected nature of these considerations. As such, resolving these factors collectively will enhance the success and sustainability of mine rehabilitation projects. The recommendations from the study include improvements in contract management, ensuring project monitoring and evaluation that encompasses progress monitoring, data management and reporting, and the establishment of performance matrices. The other areas of intervention include policy and legal reforms to define the requirements and objectives of rehabilitation projects. Stakeholder engagement and capacity building are also key elements that have a major influence on the successful implementation of rehabilitation projects. By prioritizing factors and addressing these bottlenecks, the risks associated with asbestos rehabilitation can be mitigated to foster resilient and empowered communities that actively participate and benefit from the restoration processes.
Analysis of the developmental potential of artisanal and small-scale mining: a strategy for South Africa
(2024) Twala, Pontsho Francinah
The mining industry remains central to the socio-economic development of mineral economies. While this is the case, most African countries have been struggling to translate the benefits of mining into positive developmental outcomes. This has been attributed to several factors including the failure to leverage opportunities from the Artisanal and Small-Scale Mining (ASM) sector which has been growing in most countries. As is the case in other African countries, the mining industry continues to play a considerable role in South Africa’s economy. The industry is expected to contribute significantly to the country’s socio-economic agenda which aims to eradicate poverty and inequality by 2030. Despite the positive outlook, the performance of the industry has been declining resulting in the government identifying a series of interventions aimed at reviving the industry’s activities. Amongst these is the formalisation of the ASM which has been earmarked for job creation and poverty alleviation. The objectives of the Thesis were to establish the developmental potential of ASM in the country, and subsequently develop a strategy framework aimed at enabling the sector to contribute to the mining industry and national development plan. The study was conducted using multiple case studies with data collected and analysed using multiple methods. The major finding from the study is that the ASM sector has the potential to contribute towards the country’s development priorities. This is taken from the evidence that shows a direct link between the sector’s activities and the country’s socio-economic landscape. It was established that the main drivers of ASM are socio-economic challenges in the country, mainly growing unemployment and poverty levels. To this end, ASM is playing a role in providing livelihoods to country’s population is that most affected by poverty and unemployment. As a livelihood strategy, ASM has improved the poverty status as well as the living standards of those that participate in its activities. The evidence from the study revealed that most of the miners measure above the country’s subsistence level and can provide for themselves and their families. The benefits of the sector also extend to communities and overall, these can be linked to several objectives as captured in the country’s development plan. The conclusion from the study is that the developmental potential of ASM can only be leveraged if the challenges in the sector are addressed, and these encompass issues relating to the regulation of the sector, mining land and mineral resources; value chain constraints, and related support, responsible practices, institutional arrangements, and ASM stakeholder relationships.
Application of Data Analysis and Machine Learning to Develop a Maintenance Strategy for Load-Haul-Dump (LHD) Machines at Booysendal Mine
(University of the Witwatersrand, Johannesburg, 2024) Malambule, Thulani Mduduzi; Mabala, Mahlomola Isaac; Nwaila, Glen
This report focuses on applying data analysis and machine learning to develop a maintenance strategy for load-haul-dump (LHD) equipment at Northam Platinum’s Booysendal underground mine. This operation predominantly relies on trackless mobile machinery, with a significant emphasis on LHD machines. The mine maintains daily records of mechanical equipment breakdowns. However, Booysendal's reliance on a reactive “run-to-failure” maintenance system has led to operations outside a predefined maintenance plan. The objective of this research was to apply data analytics to understand trends in the dataset and extract meaningful insights regarding LHD breakdowns. It aimed to develop a predictive maintenance model for LHD machines using appropriate machine learning models. Lastly, to design a data-driven maintenance strategy based on insights from data analysis and machine learning (ML). The hydraulic system and transmission components were found to contribute 80% towards downtime. The K-Nearest Neighbours (KNN) regressor was chosen as the best regression model, achieving the lowest Root Mean Square Error (RMSE) of 2.02, while the Support Vector Machines (SVM) classifier was selected as the best classification model with the highest accuracy of 60%. Recommendations on how the predictive models could be improved were highlighted. Finally, a hybrid maintenance strategy is proposed for proactive optimisation. The strategy entails integrating predictive analytics, real time condition monitoring and threshold-based alerts to enable proactive maintenance actions. The proactive actions include ensuring availability of critical spares and conscientizing LHD operators on failures related to bad operating practises.
Application of derivative techniques to improve the forecasting of price volatility of copper, gold and platinum metals
(2024) Veriyadi, Veriyadi
This research investigates the forecasted price volatility of copper, gold and platinum metals based on the selected companies; Palabora Copper Mining Ltd, AngloGold Ashanti Ltd, Gold Fields Ltd, Sibanye-Stillwater, Anglo Platinum Ltd and Impala Platinum Ltd. In responding to the latter sentence, single price volatilities are dual volatilities, where dual volatilities comprise of financial and technical variables. The selected firms either have global operations or they are subsidiaries of global companies. Dual volatility is computed using a Sample Correlation Coefficient and in order to explore the dual volatility, this research introduces three hypotheses. The first hypothesis uses a Decision Tree Analysis to test dual volatility based on financial and technical variables (e.g., mineral commodity price, metal grade, operating cost and production rate) in improving the forecasting of price volatility of copper, gold and platinum metals. For validation, the first hypothesis uses the Markov-Regime Switching Model. The results of this hypothesis illustrate that dual volatilities are more accurate and robust than price only volatilities. Then, the second hypothesis examines dual volatility using a GBM model. This hypothesis tests dual volatility; which is computed based on financial and technical variables (e.g., oil price, copper price, oil production and consumption, copper production and consumption; and the exchange rate from U.S.$ to ZAR and gold and platinum price data). The chosen variables that affect the dual volatility are examined using a Multiple Regression Model and that model confirms that those variables are independent in principle. Finally, the third hypothesis estimates future profits based on a binomial tree, which has risk-neutral probabilities based on dual volatility using mineral commodity price, metal grade, operating cost and production rate. The results of risk-neutral probabilities using dual volatility are less optimal than a mineral commodity price volatility due to not accounting for the mean of logarithmic returns. The robustness test uses the VAR model, which indicates that the profits react differently to different shock stages from revenues, risk-free interest rates and profits. In conclusion, dual volatility can improve future price forecasting performance because duality is underpinned by different variables, which include independent variables from the global commodity markets. The forecasting performance improvement from dual volatility in predicting the future price can be shown by the lower value of the Root Mean Square Error and Mean Absolute Percentage Error results than a mineral commodity price volatility. The findings of this research apply to copper, gold and platinum metals for mining around the globe.
Assessing the Challlenges in the Valuation of Early-Stage Secondary Diamond Deposits
(University of the Witwatersrand, Johannesburg, 2024) Ganda, Nair da Conceição de Oliveira Gavião; Marshall, Tania R.
Diamond mining is a fundamentally important part of the economy in many countries. Globally, some of these countries are home to early-stage alluvial diamond projects that attract significant interest from investors. Often, these investors need to understand the project’s value to make informed decisions. However, valuing early-stage alluvial projects is a complex and challenging process. This research report identifies and assesses the challenges associated with the valuation of early-stage alluvial projects through a case study of a project in Angola. For the case study, a valuation exercise was conducted using both the Cost Approach and the Market Approach. The research identified challenges specific to the Cost Approach, such as data availability and compliance with internationally recognised Resources and Reserves reporting codes. Likewise, challenges specific to the Market Approach included estimating current commodity prices and checking the performance of alluvial diamond properties on an applicable stock exchange. Additionally, it became clear that complications related to both approaches, such as experience and resource estimation methodologies, need to be addressed before a final valuation range can be determined. Although there are several difficulties, the valuation of early-stage alluvial projects is still possible. Nonetheless, these challenges impact the accuracy, consistency, and interpretation of the valuation results. Therefore, becoming familiar with these challenges and the recommendations made in the report will help valuators avoid potential pitfalls and contribute significantly to the field by guiding more informed decision-making in the valuation of early-stage alluvial diamond projects.
Assessing the policies for legalising artisanal and small-scale mining in south africa
(University of the Witwatersrand, Johannesburg, 2024) Komape, Ledile Jane; Marshall, T. R.
This research examines the regulatory framework of artisanal and small-scale mining in South Africa, discussing issues around whether the current policies are up to the challenge of managing the realities and expectations of artisanal and small-scale miners. The research was conducted through a survey of three focus groups across four areas in South Africa using structured questionnaires and interviews. Data collection involved contacting individuals at the Department of Mineral Resources and Energy, Mine Health and Safety Council, and Mining Qualifications Authority, as well as Artisanal and Small-Scale Miners and mine representatives, and conducting interviews at their offices, homes, or workplaces based on their preferences. Data collected from the three focus groups reveal a disconnect between the goals of the policies and how the artisanal and small miners’ communities experience them, emphasising the need for effective policy implementation, comprehensive education initiatives, and avoidance of unrealistic expectations. Key recommendations of the research include the adoption of digital technologies for monitoring, fostering cooperative models, and encouraging international collaboration between local and foreign operators. It underscores the importance of creating and applying inclusive, equitable and sustainable policies to improve the socio-economic and environmental conditions of artisanal and small-scale miners in South Africa.
Back analysis of previously stooped Panels to improve the safety and productivity of future stooping operations at new Denmark colliery
(University of the Witwatersrand, Johannesburg, 2024) Gonsalves, Ricardo
New Denmark Colliery (NDC) is a Seriti-owned underground coal mine in the Mpumalanga Province. It started stooping operations towards the end of 2018 and has since stooped 50 panels safely across all three of its shafts. NDC selected the NEVID method, which is known for its safety and success in neighbouring mines. Initially stooping panels in the 1100 block, NDC encountered challenges due to narrow panel spans, leading to limited goafing and heightened abutment stresses on surrounding pillars and infrastructure. This necessitated additional support for strategic pillars to ensure long-term stability. To address these challenges, comprehensive research was conducted, which included back-analysis of stooped panels and numerical modelling. Findings revealed that goafing was influenced more by horizontal stress concentrators, such as geological structures than panel spans. Goafing at NDC has primarily been defined by low-angle shear failures, which only extend a couple of metres into the immediate sandstone roof. This is known as partial goafing, which typically results in high abutment stresses. Since complete goafing is unlikely due to the depth below surface and the competent roof material, the high abutment stresses needed to be managed by increasing the width of the barrier pillars between panels and leaving a sufficient number of stopper pillars at the end of a stooped panel. Numerical modelling was used to validate NDC's current design strategy of stooping panels and to determine the width of new barrier pillars. The derived strategy includes an increase in barrier pillar width and stand-off distances, to ensure the long-term stability of main developments. iv The current stooping strategy which was informed by comprehensive research and modelling, has proven effective in both safety and stability.
Benefits of using Internet of Things technology for fuel management at a mechanised underground platinum bord and pillar mine: A Bathopele mine case study
(University of the Witwatersrand, Johannesburg, 2024-01) Thema, Sephela Makete; Cawood, Frederick; Feroze, Tariq
The advent of the fourth industrial revolution, Environmental Social and Governance (ESG), and push for green energy transition has propelled mining companies to reconsider their strategies. Over the past two decades, mining companies along the Bushveld Igneous complex in South Africa have been shifting towards mechanized mining methods which are generally safer and provide for the generation of greater volumes of output. Sibanye Stillwater’s Bathopele mine, which has a fleet of over two hundred and fifty (250) trackless mobile machinery (TMM) and a daily fuel consumption of approximately ten thousand (10 000) liters per day. The introduction of Internet of Things (IOT) technology in the fuel management system at Bathopele mine achieved benefits such as fuel consumption tracking, effective inventory management, prevention of fuel theft, detection of fuel leaks, determination of maintenance requirements and readily available access to fuel use data. This access to data enabled the mine to effectively apply for fuel use rebates from the South African Revenue Services (SARS) with ease. To determine the impact of the increased distance to underground working places on the refueling of TMM, the Theory of Constraints (TOC) method, qualitative and quantitative techniques were applied. A bivariate analysis conducted indicated a linear relationship between fuel consumption and production output at Bathopele mine, which suggests that an effective fuel management system had a positive impact on production output at the mine. A real-time or near real time model for fuel management in underground trackless bord and pillar mines in proposed.
A comparison of various modelling techniques to optimise production rate on a platinum mining project
(2021) Dreyer, Jaco
Every business aims to create an optimal economic value for its shareholders. The production rate is one of the critical drivers of value in the mining business. Several approaches have been developed to determine the production rate for mining operations. This study applied three approaches for determining production rate, namely the tonnage-based, microeconomic and marginal-analysis modelling methods. These methods were applied on a platinum project, and the production rate results from the three methods were used to determine the life of mine (LOM) production profiles, capital expenditure (CAPEX) and operational expenditure (OPEX). These results were then used as inputs into a discounted cash flow (DCF) model. The DCF model results were compared and analysed to determine a production rate determination method that results in an optimum production output rate for the project. The study revealed that the tonnage-based modelling technique resulted in the highest production rate of 410-kilo tonnes per month (ktpm), the highest CAPEX of USD957.24 million, the lowest OPEX of USD75.37 per mined tonne, the highest net present value (NPV) of USD63.12 million and the highest internal rate of return (IRR) of 12.85% over a 40-year LOM. The microeconomic modelling technique ranked second with a production rate of 270 ktpm, CAPEX of USD 726.24 million, OPEX of USD 76.68 per mined tonne, NPV of USD 3.46 million and IRR of 10.17%. The marginal-analysis modelling technique ranked last with a production rate of 230 ktpm, CAPEX of USD 658.76 million, OPEX of USD 77.83 per mined tonne, NPV of USD -10.69 million and the lowest IRR of 9.47%. Mineral Resource tonnage-based modelling may be further investigated in other commodities other than platinum or other multi-element/polymetallic mineral deposits in line with the South African mining industry. This will result in the formulation of industry-specific calibration in the South African mining industry
Developing a work management system to create an integrated and optimal short-term planning process at South Deep Mine
(University of the Witwatersrand, Johannesburg, 2024) Maleka, Manuel
This research was conducted at South Deep Mine, an underground trackless gold mine located within the Modderfontein Farm in the Westonaria District, Southwest of Johannesburg. The aim of this study was to develop a work management system to create an integrated and optimal short-term planning process at South Deep Mine. The study employed both quantitative and qualitative research methods to achieve its objectives. Most of the data was obtained through an online survey which targeted individuals employed within the mine technical services department. The problem being addressed in this research is the challenge associated with manual data capturing during planning sessions. This research is driven by a desire to improve work efficiency and mine productivity at South Deep Mine through the application of innovative planning and reporting tools. Literature review presented the importance of innovation and effective planning in mining operations, indicating the role of integrated work management systems in modernized underground mining environments. Work Management Systems investigated were Deswik and MineRP software and Syncromine reporting system. The results reflected that Deswik and Syncromine are used throughout the industry with some benefits such as the ability to produce integrated production reports and the reliability in data handling. However, data analysis revealed shortcomings in existing work management systems, particularly in addressing real-time data and promoting automation. The aims of this research were achieved through the development of a systemized planning protocol. The study highlighted the need for an iv integrated approach to address short-term planning challenges. Future studies include the adoption of user-friendly software tailored with site specific requirements and the development of models covering all aspects of the mining value chain.
Evaluating the economics of constructing mine haul roads using Portland cement stabilization- a case study at Lumwana Mine
(University of the Witwatersrand, Johannesburg, 2024) Katukula, Brian; Birch, Clinton
Surface mine operations engage in various strategies to optimise efficiency and productivity. The efficiency and productivity aspect of such operations aims to deliver the maximum amount of mined tonnes out of the open-pit using minimum resources. Efficiency and productivity entail that the means of conveying the material mined out of the open-pit must be at their best. In turn, equipment used in mining must be available in a good state. Furthermore, the road network and the bench conditions where such equipment operates in must offer minimum resistance for efficient utilisation. In this study, a means of improving the mine haul road condition was examined in which a ramp section at Barrick’s Lumwana Mine in North Western Zambia was stabilised with Portland cement to make it competent with an extended life span. The 300 m of Portland cement stabilised ramp section provided a common overlap of information before and after stabilisation. The information was then used as input for this study. The ramp was observed for data collection over six months, from June 2020 to December 2020. MaxMine, an independent fleet management and optimisation system, was used to collect truck-related information such as speed, time through the section, distance travelled, entry speed, the payload in tonnes, fuel consumption, and surface smoothness of the haul road section. An analysis of this information was able to deduce gains made in fuel usage, truck loaded haul and empty speeds, payload, and haul road smoothness. Information on the construction costs and other input parameters related to haul road maintenance was consolidated from the mine’s project office and used as input data. The research study deduced that cement stabilisation delivered value in the productivity and efficiency of the mine operation as there was a 12% increase in the haulage speed of loaded trucks and a 45% increase in the empty return leg. iv Even though the maximum allowable empty truck speed is 50 km/h on the mine haul roads, going down the ramp is restricted to 30 km/h and the recorded speed in the study of 34 km/h showed that a smooth ramp can be a source of safety violations. The mine has since installed a fleet management system to monitor and manage speed violations and invested in simulator training for its operators to ensure they drive the trucks within safe allowable speed limits using installed systems on the haul trucks such as the speed retarder and cruise controls. There was a 10% reduction in fuel consumption on the loaded haul and 14% on the empty return. There was also a corresponding payload increase of 5% from 243 tonnes to 255 tonnes for the review period. The increase in payload was within the capacity of the tyres to handle and had no negative impact on tyre life as the 53/80R63 tyres fitted on these trucks can handle more than 255 tonnes of payload. It is the same tyre specification used on a Hitachi 5000AC-3 dump truck that carries a nominal payload of 296 tonnes The ramp section in the research study delivered an overall value gain of over $306,000 despite incurring additional road construction costs of 13% above the normal. The additional construction costs were offset by the gains made on reduced haul road maintenance costs, which were reduced by 99.5%. Other gains made were on fuel consumption and truck maintenance through hours saved from truck speeds/cycle time gains.
Geometallurgical influence of clays on the Jwaneng kimberlite value chain
(2024) Nkgakile, Naomi
Geometallurgy is a cross- disciplinary function that provides a better understanding of the ore characteristics impacting the treatability of the material. Optimal treatment of the material is enabled by understanding variability in the ore body. Having this understanding leads to flexibility when planning mining mixes. The present investigation of the Jwaneng DK2 deposit’s geometallurgical responses demonstrate that various rock lithologies impact the treatability of the Jwaneng kimberlites. The plan t is therefore hindered from achieving design capacity as a result of its treatability constraints. The volcaniclastic kimberlite, which is a majority- treated lithology at Jwaneng Mine, contains the highest volumes of smectite clays. These clays cause settling challenges resulting in higher consumption of processing materials. To allow for informed strategic planning, all vital treatability information on the clayrich kimberlites needs to be collected. The clay occurrence can then be incorporated into the creation of the geometallurgy model. Then the completed geometallurgical model can be utilised as a predictive tool for planning
Impact of secondary rock-breaking equipment availability on mining plan in block cave mining
(University of the Witwatersrand, Johannesburg, 2024) Pedro, Martina
In 2018, the Angolan economy was ranked the third largest in sub-Saharan Africa, behind Nigeria and South Africa. This performance is mainly driven by oil production, which represents 50% of the country’s Gross Domestic Product, 95% of its exports, and more than 70% of government revenue, while diamonds represent only 5% of Angola’s exports. The Angolan Government has already invested US$ 260 million into the National Geology Plan (PLANAGEO), which concluded the geophysical aerial survey of the country’s mineral and geological potential in October 2023, putting the country in a better position for future investment. According to the African Diamond Council, it was reported in the Kimberley Process Certification System Statistics in 2021 that the diamond industry in Angola represented almost 1.2 billion Euros, with the contribution to the Gross Domestic Products at 1.6%, making Angolan diamonds the second most important export commodity. The socio-economic impact of the diamond sector has improved from 2016 to 2022, of which a value of US$ 29.58 million was contributed to the areas of education, health, sport, environment, culture, et cetera in local and surrounding communities through the Brilhante Foundation. The diamond mining industry in Angola was regulated by the Diamond Law enacted in 1994. Presently, Angola’s mining industry is subject to state regulation stipulated in the Angolan constitution—Law No. 31/11 of September 2011 (the Mining Code)—and various additional statutory and regulatory acts. In the past five years, under the newly appointed government of 2017, the 2018 Mining Code was amended. This report aimed to investigate whether Angola had fully developed its diamond mining sector to maximise revenue from the industry while also iv attracting more investors and generating socio-economic benefits for everyone, including its citizens. The methodology used in this research was a qualitative research approach. This involved the collection of primary data by interviewing experts in the diamond mining industry, and secondary data that relied on desktop studies of published and unpublished data from books, journals, abstracts, statistical data, and reports from the government gazette. The research findings unequivocally affirmed a positive response to this inquiry. The construction of the Saurimo Diamond Pole in the Lunda Sul Province—featuring seven fully operational polishing factories including Kothari, Stardiam, Kapu Gems, and the KGK factory—has generated employment opportunities and had a positive socio-economic impact within the region. The CEFOLAD Diamond training centre is currently equipping Angolan citizens with the necessary skills and tools to make meaningful contributions to the growth and sustainability of future generations. Angola is the sixth-largest diamond producer globally and is known for its high-quality gemstones. The annual production of rough diamond exports in Angola was 9.396 million carats, with an average of US$ 163 per carat and a gross revenue of US$ 1.56 billion in 2023. The Angola diamond industry employed 200 000 individuals in 2020. The Luele mine was inaugurated on November 10, 2023, in Lunda Sul Province, Angola, and it is expected to contribute an additional 5–7 million carats to the annual diamond sector. The mine currently employs 1 300 Angolan nationals. Based on the findings of this report, it is recommended that more geological investigation needs to be done in areas with visible geological potential in order to enhance and find new deposits which will eventually increase diamond production.
Impact of secondary rock-breaking equipment availability on mining plan in block cave mining
(University of the Witwatersrand, Johannesburg, 2024) Nyarela, Martin Sphiwe
Block caving is one of the massive mining methods that has become increasingly popular due to its low operating cost, improved safety, and high production output. The low operational cost is attributable to minimal blasting, which is only focused on secondary rock-breaking activities. Once caved, the material flows continually and is loaded from the drawpoint to the tipping areas using LHDs and other means, such as scraper winches. Different rock fragmentations register in the drawpoint as loading continues. The sizes range from fine to medium fragmentation and the undesirable oversized rocks that cause hang-ups and blockages. Blockages and hang-ups disturb the flow of material, which negatively impacts compliance with the mining plan and draw control schedule. The hang-ups are treated with secondary rock-breaking equipment to make drawpoints available for loading. However, if the mechanical availability of rock-breaking equipment is low, drawpoints remain idle beyond acceptable limits. Additionally, factors such as the availability of experienced miners to address challenging hang-ups, in instances where treated hang- ups remain unresolved as a result of treatment failure, and the prioritisation of adjacent draw points for loading to restore macro material flow, especially in cases of high hang- ups, can significantly contribute to longer idle periods as well. In this regard, this research aimed to understand the impact that secondary rock-breaking equipment has on the mining plan at the PMC block cave. The research conducted an empirical study of the Secondary Breaking Unit, which forms part of the Mining Operations responsible for all secondary rock-breaking activities at the Palabora Mining Company (PMC). The secondary rock-breaking equipment types that this study investigated include the Medium Reach Rigs, Water Cannons, and Mobile Rock-Breakers. A 52-week data obtained from PMC was used for this study, covering iv the period from January to December 2021. The data pertain to secondary rock- breaking equipment availability and utilisation, cave availability, loading compliance, downtime contribution factors, and in-situ grade. The correlation and regression analysis methods were used for the analyses of data to answer the research questions. In this study, the copper content derived from the mined tonnes and in-situ grade was used as a proxy for the mining plan and it excludes uncontrollable factors such as recovery, pricing, and exchange rates. Firstly, the study sought to determine whether the PMC’s Lift 1 block cave is behaving as predicted and it was concluded that it is. Secondly, the study sought to determine if there is a relationship between the mining plan, using the deviation from the mining plan, and cave availability and loading compliance respectively. It was established that the correlation between the deviation from the mining plan and cave availability was not strong enough whereas the correlation between the deviation from the mining plan and loading compliance was strong enough to derive a predictive equation which was validated. Thirdly, the research sought to establish the minimum acceptable rock-breaking equipment availability at PMC. It was found that the minimum acceptable availability was cautiously 60% based on the historical data. Fourthly, the research sought to determine the research strategy that can improve the rock-breaking equipment availability from the low of 42% in 2021 to at least 60%. The mine’s target availability is 65%. To achieve this, categories of downtime for MRR, MBR and WC with high impact were identified using the Pareto principle. The maintenance overrun downtime category which was one of those with a high-impact downtime was found to be common in all three equipment types with a combined duration of 10 695 hours or 44.4 days per operational equipment per year. In this regard, the Schedule Maintenance strategy was suggested.
Impact of the mining charter on socio-economic development and mining investment attractiveness in South Africa
(University of the Witwatersrand, Johannesburg, 2024) Meela, Princess Makone; Mutemeri, Nellia
The purpose of this study was to review the impact of the Mining Charter on socio- economic development and mining investment attractiveness in South Africa. The impact on socio-economic development was assessed by reviewing government compliance reports and Minerals Council of South Africa publications. The analysis of exploration budgets as a percentage of country Gross Domestic Product (GDP) was used to gauge the investment attractiveness of South Africa’s mining industry. A qualitative description was also conducted on mining codes and mineral policies of Canada, Australia, Brazil, Chile and five African countries (Ghana, Botswana, Tanzania, DRC, Zambia) to understand how these countries utilise natural resources to advance socio-economic developments. The study concluded that the Mining Charter has a positive impact on socio-economic development in South Africa. The research further revealed that globally, South Africa ranks relatively low in its exploration expenditure in terms of both absolute exploration budget and percentage of exploration budget to GDP. Findings of the international benchmarking study are that the requirements of elements of the Mining Charter are similar to other socio- economic development interventions observed in the assessed mining jurisdictions. The requirement of ownership of mining companies by local people is restricted to South Africa and the DRC. In Canada there is limited sharing-holding/profit-sharing for the benefit of the community where there is an agreement in place between the mining company and such community. These agreements are not imposed by law or mining policy. The research finding regarding the ownership element is significant in that it links to the problem statement of the research study wherein the requirement of ownership of mining companies by citizens (“black people”) is reportedly one of the main hindrances of mining investments in South Africa, as singled out by some of the iii mining executives. The recommendation from the study is that the South African Government should enforce empowerment deals where all shareholders are treated equally in terms of contributions and participation in the managing of a mining company. In line with other mining jurisdictions particularly in Africa, direct state participation could be considered as an option for meaningful economic participation of the South African Government, for the benefit of all South Africans.
Improving grade estimation using machine learning: a comparative study of ordinary kriging against machine learning algorithms
(University of the Witwatersrand, Johannesburg, 2024) Akpabio, Aniekan
This study investigated the efficiency of machine learning (ML) methods in the accurate prediction of ore grades, placing them in direct comparison with the established Ordinary Kriging (OK) methodology, a mainstay in geostatistical analysis. Utilising a dataset from a complex platinum group elements (PGE) deposit, the research assessed a suite of ML algorithms—namely, Random Forest (RF), Decision Trees (DT), Support Vector Regression (SVR), and particularly 𝑘- Nearest Neighbours (𝑘NN). The latter is highlighted for its adeptness in assimilating spatial data correlations intrinsically, echoing the insights from Nwalia's analytical explorations. The research engages with detailed swath plot analyses, comparative metric evaluations, and a nuanced understanding of spatial continuity, to illustrate the distinct advantages and operational competencies of the models. 𝑘NN, with its reliance on local data proximities and non-parametric nature, alongside RF, with its ensemble-based approach, emerged as capable in point estimate predictions. These models adeptly delineated local grade variations, demonstrating a high degree of reliability to the observed data and outperforming the OK model in both precision and accuracy. Further, the study examined block estimate predictions, a cornerstone in practical mining and resource estimation, where both 𝑘NN and RF demonstrated a commendable ability to generalise predictions over larger spatial extents. This translates into significant potential for enhancing mineral resource estimation processes, tailoring them to the granular specifics of a given ore body, and refining block model accuracy to inform more strategic mining operations. While the results endorse the ML methodologies as robust alternatives to traditional geostatistical techniques, the research also highlights the nuanced nature of these predictions. Factors such as the ore body's heterogeneity, the appropriateness of the variogram model, and the interplay between prediction scale and algorithmic performance are examined, offering a critical lens through which the suitability of each method is assessed. iv The research suggests that while some models like LR and SVR are bounded by linear assumptions and hyperparameter sensitivities, non-linear models such as DT and RF can innately navigate the complex, multifaceted layers of geological data. The comprehensive evaluation extends to propose a novel set of performance metrics designed to capture the intricacies of grade prediction, thereby aligning closely with the operational demands and decision-making processes in the mining industry.