Mining

Drilling and blasting is the conventional method used for rock fragmentation in open pit mining. Blast-induced damage can reduce the level of stability of benches and pit slopes. To develop an optimal blast design, an adequate knowledge of the rock properties and in situ fractures is needed. Fractures are generally the paths of least resistance for explosive energy and can affect the intensity of blast-induced damage. Discrete Fracture Networks (DFNs) are 3D representations of joint systems used for estimating the distribution of in situ fractures in a rock mass. The combined finite/discrete element method (FDEM) can be used to simulate the complex rock breakage process during a blast. The objective of this paper is to develop a methodology for assessing the influence of in situ joints on post-blast fracturing and the associated wall damage in 2D bench blast scenarios. First, a simple one-blasthole scenario is analyzed with the FDEM software Irazu 2D and calibrated based on a laboratory-scale blasting experiment available from previous literature. Secondly, more complex scenarios consisting of one-blasthole models at the bench scale were simulated. A bench blast without DFN (base case) and one with DFN were numerically simulated. The model with DFN demonstrated that the growth path and intensity of blast-induced fractures were governed by pre-existing fractures, which led to a smaller wall damage area. The damage intensity for the base case scenario is about 82% higher than for the blast model with DFN included, which highlights the significance of in situ fractures in the resulting blast damage intensity. The methodology for developing the DFN-included blasting simulation provides a more realistic modeling process for blast-induced wall damage assessment. This results in a better characterization of the blast damage zone and can lead to improved slope stability analyses. Full article

The selection of an appropriate mining method, along with the corresponding machinery, is a crucial and highly strategic decision in the field of mining engineering. This decision directly influences the efficiency, safety, and economic viability of a mining operation. An optimal combination of mining techniques and equipment is essential to ensure the effective exploitation of the ore deposit while minimizing costs and maximizing productivity. This paper briefly overviews existing mechanized mining machines for narrow reef mining. The NRE fleet is presented in more detail, together with the results of trial tests conducted using the NRE Drill Rig in narrow reef platinum mines situated in the Great Dyke of Zimbabwe and the Bushveld Igneous Complex in South Africa. The trials were carried out using two distinct mining layouts: the bord and pillar layout and the breast mining layout. The test results clearly demonstrated that the Drill Rig is more effective in breast mining layout compared to the bord and pillar layout in narrow reef mining. The breast mining layout showed superior performance in terms of the number of drilled boreholes and overall efficiency despite the lower availability and utilization of the Drill Rig. Full article

Automation is increasingly gaining attention as the global industry moves toward intelligent, unmanned approaches to perform hazardous tasks. Although the integration of autonomous technologies has revolutionized various industries for decades, the mining sector has only recently started to harness the potential of autonomous technology. Lately, the mining industry has been transforming by implementing automated systems to shape the future of mining and minimize human involvement in the process. Automated systems such as robotics, artificial intelligence (AI), the Industrial Internet of Things (IIOT), and data analytics have contributed immensely towards ensuring improved productivity and safety and promoting sustainable mineral industry. Despite the substantial benefits and promising potential of automation in the mining sector, its adoption faces challenges due to concerns about human–machine interaction. This paper extensively reviews the current trends, attempts, and trials in converting traditional mining machines to automated systems with no or less human involvement. It also delves into the application of AI in mining operations from the exploration phase to the processing stage. To advance the knowledge base in this domain, the study describes the method used to develop the human–machine interface (HMI) that controls and monitors the activity of a six-degrees-of-freedom robotic arm, a roof bolter machine, and the status of the automated machine. The notable findings in this study draw attention to the critical roles of humans in automated mining operations. This study shows that human operators are still relevant and must control, operate, and maintain these innovative technologies in mining operations. Thus, establishing an effective interaction between human operators and machines can promote the acceptability and implementation of autonomous technologies in mineral extraction processes. Full article

The social acceptability (SA) of mining projects is a crucial issue for the sustainable development of territories and local communities. This article aims to identify the issues and examine the factors influencing the SA of exploration, exploitation and processing projects of critical and strategic minerals (CSMs) in Quebec. A systematic review guided by the PRISMA approach was conducted, selecting 57 relevant documents after excluding several others. The results reveal that between 2000 and 2024, the publication of studies on SA in the mining sector has increased significantly, particularly since 2013. Research is mainly concentrated in North America, with a predominance of case studies. Their critical analysis indicates that the SA of mining projects is based on various issues, including the need for greater consideration of the perspectives of local communities, as well as open and inclusive communication between all stakeholders. However, SA is affected by various factors, including demographic, economic, environmental and governance, which can have positive or negative effects depending on the context. Following this analysis, future research should explore the complex interactions between these factors, determining how some may act as mediators or moderators in various contexts through real case studies. Full article

This study presents a gravity survey conducted for mineral exploration in the Gerolekas overthrust area at a bauxite mining site in Central Greece. In the summer of 2018, a gravity survey, covering 28 km², was conducted, including confirmed and unexplored zones. By utilizing gravity data, we investigated the shallow subsurface geology and structural sequences, resulting in a high-resolution 3D density model. This model is generated through constrained gravity inversion by the exploitation of the boreholes available at mining sites, and the geological survey fills the areas with boreholes, which provides the stratigraphy to some depth. The suggested data-processing techniques provide information for the tectonism of the area, which is also important for mineral exploration, as well as mining design. The interface with density contrast between the flysch and the underlying limestone in the high-resolution 3D density model provides useful information on the geological status, but also, the slight density difference in limestone provides an interface where bauxite deposits can be. The inversion, conducted with EMIGMA software, incorporated high-resolution topography data and density constraints to produce a reliable 3D density model. The findings highlight the gravity method’s potential to enhance mineral exploration efficiency, offering a robust tool for further geological and mining considerations. Full article

To enhance the efficiency of mine planning, mining companies wish to understand the structure and extent of ore-bearing rocks as well as possible. Conventional seismic reflection surveys are not well suited for this purpose as they provide an image containing only the location of reflectors, and do not provide physical property information to discriminate between ore and gangue material. Full-waveform inversion (FWI) is a powerful inversion technique, which is able to recover the physical properties of the subsurface at a far greater spatial resolution and accuracy than conventional seismic methods. In this study, we synthetically examined the feasibility of using FWI to image quartz vein-hosted gold deposits. We utilised the Curraghinalt gold deposit in Northern Ireland to parameterise our models, where mineralisation is bound entirely to thin (1–3 m) and steeply dipping (>45°) quartz sulphide veins. Firstly, we demonstrated that a conventional surface seismic reflection survey geometry alongside FWI is infeasible for imaging quartz vein-hosted gold deposits. Secondly, we explored a cross-hole seismic survey geometry consisting of sources and receivers placed down vertical boreholes. This cross-hole survey geometry is capable of generating synthetic datasets such that FWI can recover the position of the veins in space accurate to within 0.5 m relative to their true positions, and recover their physical properties with an accuracy greater than $90\%$, beginning from an entirely homogeneous starting model. We conclude it is essential the source and receiver boreholes be positioned such that both transmitted and reflected arrivals are present in the datasets, otherwise FWI will fail to accurately recover the position and physical properties of the veins. This opens a new avenue for FWI to play a major role in the planning stages and development of gold mines around the world. Full article

The use of pumpable emulsion explosives in the stopes of narrow-reef gold mines is an emerging practice. This is due to recent developments in the delivery and placement mechanisms of emulsion and gassing agents through portable charging units into small-diameter blastholes. With these developments, this paper outlines the performance of pumpable emulsion explosives in a non-trial basis at two underground gold mines in South Africa, where a combined 33 underground drilling and blasting outcomes were observed in two shafts, where three key performance indicators—namely face advance, powder factor, and fragmentation size distribution—were evaluated. The results indicated that the use of emulsion explosives can enhance the probability of achieving the target face advance, whereas the results of the powder factor are mixed. In one shaft, the actual powder factor of the observed blasts mostly exceeded the planned powder factor, whereas in the other shaft, the latter was largely achieved. Lastly, the results of the fragmentation size distribution analyses are inconclusive; that is, it cannot be conclusively pointed out whether the use of pumpable emulsion explosives can achieve a mean particle fragmentation range of 11.5 cm to 13.5 cm at Shafts A and B. Full article

Where mining activities cause disturbance in catchments, streams are often impacted by heavy loads of fine eroded material. Since geomorphological processes are very slow, it is expected that during rehabilitation, typically hundreds of years are required for a mine landform to return to stability. A sensitive approach to analyzing post-mining landform stability in tropical regions is to assess the quantity of fine suspended sediments (FSS = silt + clay (0.45 µm < diameter < 63 µm)) leaving the catchment where the mine resides and entering the receiving streams in response to storm events. Continuous stream discharge and FSS quantities upstream and downstream of the catchment where the mine resides were modeled using the HEC-HMS (Hydrologic Engineering Centre–Hydrologic Modeling System). Once calibrated, the model was run for a thousand years to predict continuous stream discharge and FSS quantities for various predicted rainfall scenarios. Short-term erosion and deposition across the mine catchment were also evaluated using a calibrated landform evolution model, CAESAR-Lisflood. This paper reviews watershed soil erosion measurements and modeling research leading to the abovementioned approach. This approach assesses mine landform erosion and stability in terms of fine suspended sediments. It can be used to determine mine landform erosion dynamics, predict the achievement of landform stability equilibrium, and as a post-mining rehabilitation assessment tool. Full article

The thermal regime of underground mines, shaped by air temperature, velocity, and relative humidity, is a crucial factor for production and the health and safety of miners. While many aspects of this thermal regime have been thoroughly studied in the literature, local heat sources from mechanized equipment, such as load–haul–dump machines, conveyors, and auxiliary fans, have received comparatively little attention despite their significant impact on the thermal environment in mining development areas and stopes. This paper presents findings from a comprehensive study of the microclimatic air parameters in several nickel–copper and potash mines. We focus specifically on variations in air temperature in areas where mining equipment is operational. The heat output from different types of equipment, including load–haul–dump units, cutter–loaders, drilling rigs, conveyors, and auxiliary fans, has been quantified. We established empirical relationships for heat emissions from these machines and conducted a comparative analysis of their heat outputs. The main advantage of these relationships is their simplicity and the minimal number of input parameters required, making them practical for use in the field. Full article

Decreasing the rockburst potential in longwall mining of burst-prone coal seams has been a longstanding challenge for geotechnical engineering worldwide. One of the effective approaches is drilling of relief boreholes in front of the coal seam face from the airways. This work presents a novel approach based on the integral rockburst factor ($K_{Irb}$) taking account of the length of the dynamic abutment stress influence zone and the ratio of the vertical stress to the remote field virgin stress. The geotechnical conditions of seam 3 of the Alardinskaya mine (Kuznetsky basin, Russia) are taken as a study site. An approach of the finite-difference continuum damage mechanics is employed to describe the processes of deformation and fracture of coal and host rocks using an in-house software. The results indicate that the abutment stress maximum shifts deep into the seam after drilling and that the stress distribution along the coal seam horizon is a superposition of the solutions similar to those of the elastoplastic Kirsch problem. The results also indicate that the curves of $K_{Irb}$ dependence on spacing between the boreholes and their diameter are nonlinear and non-monotonic functions, which allows for optimizing of the drilling technology. Full article

Hyperspectral imaging technology holds great potential for various stages of the mining life cycle, both in active and abandoned mines, from exploration to reclamation. The technology, however, has yet to achieve large-scale industrial implementation and acceptance. While hyperspectral satellite imagery yields high spectral resolution, a high signal-to-noise ratio (SNR), and global availability with breakthrough systems like EnMAP, EMIT, GaoFen-5, PRISMA, and Tanager-1, limited spatial and temporal resolution poses challenges for the mining sectors, which require decimetre-to-centimetre-scale spatial resolution for applications such as reconciliation and environmental monitoring and daily temporal revisit times, such as for ore/waste estimates and geotechnical assessments. Hyperspectral imaging from drones (Uncrewed Aerial Systems; UASs) offers high-spatial-resolution data relevant to the pit/mine scale, with the capability for frequent, user-defined re-visit times for areas of limited extent. Areas of interest can be defined by the user and targeted explicitly. Collecting data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions offers the detection of different minerals and surface alteration patterns, potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. This is related to but not exclusive to detecting deleterious minerals for different processes (e.g., clays, iron oxides, talc), secondary iron oxides indicating the leakage of acid mine drainage for rehabilitation efforts, swelling clays potentially affecting rock integrity and stability, and alteration minerals used to vector toward economic mineralisation (e.g., dickite, jarosite, alunite). In this paper, we review applicable instrumentation, software components, and relevant studies deploying hyperspectral imaging datasets in or appropriate to the mining sector, with a particular focus on hyperspectral VNIR-SWIR UASs. Complementarily, we draw on previous insights from airborne, satellite, and ground-based imaging systems. We also discuss common practises for UAS survey planning and ground sampling considerations to aid in data interpretation. Full article

The study evaluates the socioeconomic dynamics and their impact on life expectancy in coal mining communities in Colombia, aligning with the Sustainable Development Goals (SDGs), assessing the relationship between production, occupation, accident rates, mortality and royalties. Univariate, bivariate, path analysis and ARIMA models were used to identify patterns and projections. The results show a positive constraint between coal production and royalties, which is negative with the occupation, accident, and mortality rates. Despite the revenues generated, no improvements in the quality of life of mining communities are observed; the poor use of royalties reflects a lack of effective strategies to convert mining revenues into sustainable enhancements for local communities. It highlights the rush for more effective public policies to ensure that economic benefits are aligned with improvements in communities’ health, safety and quality of life. In the future, greater alignment with the SDGs, particularly SDG 3 (Health and Well-being) and SDG 8 (Decent Work and Economic Growth), will depend on a sustainable approach that prioritises investment in social infrastructure and the equitable distribution of resources derived from mining, thereby addressing current disparities. Full article

Amazon rainforests have many hidden treasures; thus, a balance between mine activities and the environment must be maintained. In the northern region of Brazil, there is a large diversity of metal ore deposits, the exploitation of which requires innovative and sustainable mining operations. Historically, mining operations have caused various environmental issues, such as landscape deterioration, damage to natural structures due to detonations, and soil and water pollution, and have also contributed to CO₂ emissions from diesel trucks. Here, to estimate and minimize the operating expenses of a large-scale open-pit iron mine, a mine-to-crusher model was developed. The calibration of the mine-to-crusher model was based on rock fragmentation from the blasting phase through the primary crushing phase from an analysis of pictures of the fragmented pile. A reduction in cost was determined for an optimum 90% passing size (P90). The calibration was performed with technical and economic parameters from 2 years before. For the studied iron ore mine site, an optimum P90 value between 0.29 and 0.31 m was determined. Full article

Mineral processing is a crucial stage in the mining process, involving comminution and concentration stages. Comminution is modeled using various ore variables and operational parameters, representing a complex system. An alternative to simplifying the complexity of these stages is adopting machine learning (ML) techniques; however, ML often requires a substantial amount of data for effective training and validation. The conjoint analysis methodology was used to develop a procedure for discretizing input variables and reducing the data needed for training neural networks, requiring only 77 different scenarios. Using the results from a comminution plant simulator built in Matlab Simulink, neural networks were trained to predict the key output parameters, such as the water consumption, energy consumption, operational parameters, and particle size generated by the plant. The predictive capability of the neural networks was excellent, achieving R² > 0.99 in all cases. The networks were tested with a new set of scenarios to assess their response to values not categorized in the discretization process, achieving R² > 0.98. However, the prediction capability was lost for out-of-range input variables. This approach is attractive for developing easy-to-implement ML tools capable of representing complex systems without needing large amounts of input data, thereby simplifying the modeling process in mineral processing. Full article

The South African gold mining industry requires complex water reticulation systems to deliver chilled water to underground production areas. However, chilled- and service-water wastage, including leaks and misuse, contribute to approximately 50% of the total chilled-water demand. The current inefficiency detection methods rely on broad, infrequent, and labour-intensive work, focusing only on identifying and quantifying wastages without comprehensive mitigation strategies. This study aimed to develop a novel accountability framework employing dynamic zero-waste baselines to identify and address inefficiencies closer to active working areas. The proposed method incorporates four key components—define, assess, execute, and communicate—into an accountability system to monitor performance and ensure sustainable improvements. The integration of dynamic zero-waste baselines within this accountability framework will ensure faster and more accurate inefficiency detection and, more importantly, the mitigation thereof, significantly reducing water wastage. This study successfully reduced the daily water wastage, with an annual energy cost benefit of approximately USD 1.6 million (ZAR 28.7 million). The successful implementation of this method met all the research objectives, confirming its effectiveness. Full article

To ensure the safe repurposing of post-mining landscapes, understanding and managing geotechnical risks, particularly ground movements such as settlements on opencast mining dump surfaces, is critical. Satellite-based radar interferometry (InSAR) technology offers highly detailed data on vertical ground movements with a high spatial and temporal resolution. By combining a data-driven approach, using InSAR-generated high-resolution datasets, with model-driven methods such as inverse modeling and classic time–settlement models, the efficient monitoring and prediction of opencast mine dump settlements can be achieved. This dual approach—leveraging advanced data analysis tools and precise modeling—yields valuable insights into spatial settlement behavior. In particular, classic time–settlement models are applied to the InSAR data through least square regression and Taylor approximation. The integration of both approaches enables the more robust, data-validated forecasts of key geotechnical indicators, such as the time to settlement stabilization and the expected maximum settlement over large areas. An application at a mine in central Germany illustrates the method by generating spatial predictions of the settlement behavior over more than 200 ha. In general, the results provide a comprehensive dataset for investigating other factors influencing the settlement behavior of opencast mine dumps. Full article

Industry 4.0 represents a crucial technological revolution for the modernization and competitiveness of companies, offering tools that enhance the efficiency, productivity, and sustainability of industrial processes. Adopting these technologies is essential, especially in crucial sectors such as mining, where their implementation can radically transform operations. This study investigates the adoption of Industry 4.0 technologies among mining and non-mining companies in Chile, using data from the Survey of Access and Use of Information and Communication Technology in Companies. A Principal Component Analysis (PCA) identified the main variables influencing technological adoption. The results indicate that mining companies are significantly more advanced in integrating technologies such as ERP, SCM, and Big Data, which optimize their operational processes and strengthen their competitiveness. In contrast, non-mining companies show a more dispersed adoption, which could limit their capacity for innovation. These findings underscore the importance of developing differentiated public policies that promote technological adoption in SMEs and less advanced sectors, also encouraging the development of internal capacities and collaboration between businesses and government to accelerate digital transformation. Full article

The mining industry is undergoing a transformation driven by the adoption of Industry 4.0 technologies, implementing autonomous trucks, drones, positions systems, and similar technologies. This article, drawing on experiences and observations from several studies conducted in the mining industry, explores the impact of these technologies on mining work. It identifies eight key potential changes in working conditions. Firstly, routine and dangerous tasks are increasingly automated, reducing physical strain but potentially leading to job displacement and increased maintenance demands. Secondly, operators and managers are shifting toward handling disturbances and training algorithms, as AI takes over decision-making processes. Thirdly, managers are responsible for more capital with fewer people, potentially altering managerial roles and spans of control. Fourthly, the global connectivity of operations makes the world both larger and smaller, with a universal language blurring boundaries. Fifthly, work becomes location-independent, allowing for remote operation and management. Sixthly, the distinction between work and private life blurs, with increased availability expected from operators and managers. Seventhly, technology expands human senses, providing real-time data and situational awareness. Eighthly and lastly, the pervasive collection and retention of data create a scenario where one’s history is inescapable, raising concerns about data ownership and privacy. These changes necessitate a strategic response from the mining industry to ensure socially sustainable technology development and to attract a future workforce. Full article

Mineral extraction is an important operation for the economy of different countries and generates millions of tons of mining waste. In this context, and in association with the high demand for paving aggregates and the lack of raw materials for this purpose, the feasibility of using iron ore processing waste has emerged as a promising alternative. This study evaluates the physical and mechanical behavior of asphalt mixtures incorporating waste from the company Samarco S.A., collected in Mariana-MG, to replace the fine aggregate in asphalt concrete mixtures, with a view to applications in the bearing layer of local traffic roads. Two mixtures, M2 and M3, containing 20% and 17% waste, respectively, were formulated and analyzed, compared to a reference mixture, M1. Evaluations were carried out using the Marshall method parameters, mechanical tests of resilience modulus, and fatigue life under controlled tension, as well as mechanistic analysis. Brazilian mechanistic–empirical design software (MeDiNa—v 1.5.0) contributed to this analysis. This analysis revealed that, for a traffic level of N = 5 × ${10}^6$ (average traffic) on a local road, pavements containing the M1 and M3 mixtures had the same layer thicknesses (6.9 cm), as well as the same fatigue class, equal to 1. The pavement with the M2 mixture had the thickest asphalt layer (8.2 cm) and a lower fatigue class equal to 0. But if compared in terms of the percentage of cracked area over 10 years, it still offers ideal performance conditions compared to the M1 and M3 mixes. Thus, it can be considered feasible to replace fine aggregate with iron ore waste in asphalt concrete for use on local roads in the region without altering the bearing capacity of the pavement. Full article