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By M Pyle, R Ch, G Lane, ramhan

Data is the most valuable commodity in the information age. The use of data enables productivity, opportunity, and safety in various sectors and industries. In the late 1950s, Alan Turing coined the term artificial intelligence (AI) to describe the ability of computing machines to think and behave like humans through simplified reasoning and logic (Turing, 1950). This concept of mimicking human behaviour is the building block of machine learning algorithms used in most AI software. The ‘learning’ aspect in machine learning requires data, that is, information on the environment or the objective, to be modelled or predicted using AI. An AI-enabled system aims to predict the unknown faster and intuitively. Intuition in software algorithms can be described as probabilistic, learned through the data that the AI system is trained on; indeed, the AI software cannot predict the future, but it can provide the likelihood of an event/action occurring, thereby enabling decisions or responses to prevent it or take action. Just as various industries have adopted AI as the tool of choice to seek new opportunities (examples: medical research, self-driving cars, financial modelling), the mining industry, too, has been receptive to embracing AI for problem-solving and maximising the value of its business.

Sep 1, 2024

By B P. Banerjee. S Raval, P M. Ranasinghe

Simultaneous Localisation and Mapping (SLAM) is an important technology that enables autonomous robots to navigate independently and create detailed, real-time maps of their surroundings. This capability is crucial in underground mining settings, where it enhances operational efficiency and significantly strengthens safety in these subterranean environments. SLAM algorithms typically rely on identifying and using distinct geometric features, such as plane and edge features, to understand the spatial layout of the environment and to track how it evolves as the sensor moves through it. In underground roadways, the scarcity of noticeable edge features, coupled with the repetitive nature of walls and corridors, poses a significant challenge, making it difficult for these systems to distinguish one area from another. Furthermore, the absence of global navigation satellite system (GNSS) signals in underground adds more challenges, leading to the accumulation of errors in both the mapping and localisation.

Sep 1, 2024

By B P. Banerjee, D Patra, S Raval

Roof bolts are an essential component of roof support systems in underground mines. They are used to provide structural support to the roof of the mine and prevent it from collapsing. Therefore, it is imperative to perform regular assessments of these roof bolts to avert any hazards. Manual investigations of roof bolts are done by surveyors in underground mines, which is extremely timeconsuming and challenging due to the low-light conditions in underground mines accompanied by stringent mine access rules. To this end, automated recognition of roof bolts in 3D point cloud data obtained through laser scanning in underground mines serves as a potential solution to aid roof bolt monitoring. With the continuous advancements in laser scanning-based 3D data acquisition systems, the feasibility of making such surface estimations from 3D point cloud data has increased severalfold.

Sep 1, 2024

By S J. Schafrik, M Long

There are several factors that are increasing the need for new graduates to be ready to design and manage more autonomous operations at mines. Autonomous controls and systems range from the start-up, control, and shutdown of processing plants to the autonomous operation of vehicles. These operations require the workers, engineers, and management to have additional skills for programming, debugging, tasking, and maintaining the equipment. The future survivability of many mining operations will be influenced by a company’s willingness and ability to understand, accept, and utilise this technology for safe and productive operations. This is an educational opportunity and challenge that needs to be addressed throughout the student’s experience, from first year to graduate level. This paper discusses the lessons learned from a decade of multidepartment effort at all student levels and many courses that are able to incorporate data science, controls, and autonomous design into the already topic-rich national curriculum. This approach also exposes other engineering disciplines to the mining industry which is a valuable recruiting tool for talent outside of the mining engineering departments.

Sep 1, 2024

By D Connelly

High purity alumina (HPA) is a processed, premium non-metallurgical alumina product characterised by its purity level ie 99.99 per cent (4N) or 99.999 per cent (5N). The market price, application, and performance of HPA varies widely according to its degree of purity. High purity alumina is a form of aluminium oxide (Al2O3) with growing use in LED lighting and coating on the ceramic cathode separator sheets in lithium ion batteries. This paper describes a study on producing high purity alumina from feldspar to produce HPA and potash for use as a fertiliser. The project was positive for a number of reasons. High potassium extraction (>99 per cent) was achieved in the alkali leach using sodium hydroxide as the leaching agent and full dissolution of the alkali leach residue was achieved using hydrochloric and sulfuric acid. The potential to produce a high purity alumina product via a complex but promising emerging process was assessed. The potential to extract potassium as potassium sulfate to add value to the project was also demonstrated with the test work.

Sep 1, 2024

By K Clode, J Al-Shdifat, S Daykin

Planning for a circular economy allows for previously untapped market opportunities to be explored, resulting in new, innovative revenue generating opportunities, while also reducing environmental impacts. In particular, rare earth elements (REE) are in rising demand as they are key components of over 200 products across a wide range of applications (Xie et al, 2023) including renewable energy technologies. There is a geographical disparity in deposits, with China being the top producer, generating 70 per cent of global production in 2022 (Laboure, 2023). This single dominating source has created supply chain concentration and hence supply risks for other nations, providing a driver for finding alternative sources, such as mine-influenced water (MIW) and tailings. In this study, Isle presents a robust due diligence methodology for undertaking a global horizon scan into REE recovery technology, for a large mining company, from tailings decant water on a specific site. Previous studies of the tailings decant water at this site had shown potentially significant concentrations of both heavy and light REE, but challenges such as high flow, very low pH and high concentrations of iron had previously made recovery unfeasible. Due to these challenges, the horizon scan focused on technologies that had the potential for selective recovery, despite the challenges with water quality, and considered a range of Technology Readiness Levels (TRLs). This included an adsorption-based process that has the potential to selectively separate individual REE, and a polymer based selective flocculation technology.

Sep 1, 2024

By T Hicks

Designers of mining facilities play a significant role in defining the overall mine greenhouse gas emissions performance. This demands an appreciation of all the greenhouse gas emissions sources, including Scope 3 emissions, which will form an increasing fraction of the emissions as we transition our generation sources to renewable energy. Traditionally overland conveyors are designed to operate as fast as practical, and through this approach, achieve relative minimisation of: conveyor belt tensions; belt width; mechanical equipment masses; structural steel quantities; and concrete quantities. It is well understood that higher belt speeds reduce capital cost and improve project economics. Operating at higher speeds introduces operating costs through system energy losses and increased wear rates. This paper assesses the life cycle greenhouse gas emissions for a typical iron ore overland conveyor to demonstrate how the design criteria and engineering decisions impact greenhouse gas emissions and project economics. An analysis of the decarbonisation potential and project economics using a range of operational parameters has been completed, developing a marginal abatement cost for each system configuration, creating a basis for integration of low emission overland conveyor designs as part of the broader facility decarbonisation strategy.

Sep 1, 2024

By B Murphy

Seeking to reduce the likelihood of uncontrolled personnel entry into the operating footprint of a dragline, Coronado Global Resources initiated a review of proximity detection systems currently available and equipment interactions in and around dragline operational areas. At the time of the assessment, there were no established personnel proximity detection systems in compliance with functional safety standards for large machinery in Australia. Our primary objective was to guarantee a functionally safe outcome, particularly by implementing a performance-level-rated system in accordance with AS4024 (Safety of Machinery series of Australian Standards). Applying appropriate detection technologies, the goal was to reduce the residual operating risk for machine-to-machine and machine-to-personnel interactions. A comprehensive analysis of available or in-development technologies was conducted, and a layered approach (demonstrated in Figure 1) was adopted to achieve the desired risk reduction by segregating the sensing zones into distinct areas using diverse and disparate technologies consisting of radar (short); light detection and ranging (LiDAR) (medium); and optical (long). To address the potential limitations of each technology, overlapping layered sensing zones were designed. With LIDAR and optical using two distinct artificial intelligence (AI) systems to classify detections, these were specifically trained to handle the unique environments of a mining operation.

Sep 1, 2024

By H S. Shin, H Jin, B H. Ryu, J Lee

Prospecting ice on the Moon necessitates drilling systems to obtain subsurface samples and measure the composition of ice deposits. Landers and rovers equipped with drilling equipment are essential for analysing ice and subsurface resources located at the Moon’s poles. These devices must be small, lightweight, low-power, highly efficient, and high-performance units to function properly in the extreme conditions of the lunar environment. Researchers have developed a prototype drilling apparatus capable of operating in atmospheric and cold environments. A newly developed drilling system in Korea, capable of performing not only sampling but also subsurface investigation, is introduced.

Sep 1, 2024

By C Xu, B Li

Multi-sensor fusion visual perception technology significantly enhances visual perception capabilities in complex and harsh environments by combining visual data from different sensors. This technology is especially useful for scenarios where traditional single visible light sensors, such as standard cameras, struggle due to poor lighting, adverse visual conditions, or other visual obstructions. In environments with low light, smoke, or dust, the performance of conventional visible light sensors degrades, limiting their application. By integrating data from various sensors like radar, infrared thermal imaging, and others, multi-sensor fusion technology provides a more comprehensive and complementary visual solution. This fusion not only enhances the robustness of visual systems but also greatly expands their potential applications in fields like visual surveillance. In recent years, deep learning methods have become the mainstream technology for addressing multi-sensor fusion issues, demonstrating significant advantages in adaptive feature selection compared to traditional machine learning methods. However, deep learning-based multi-sensor fusion algorithms still face several challenges. The design of network structures is often redundant, lacking effective screening of useful components within multimodal information. Mainstream fusion algorithms focus excessively on improving display effects without adequately considering the needs of downstream applications and tasks. Existing fusion perception algorithms are generally designed for open visual scenes and lack targeted design for complex visual degradation factors present in tunnel environments of mines. Current deep learning methods for designing multi-sensor fusion networks heavily rely on manual experience to create fusion modules. This reliance increases the complexity of network design and can lead to redundancy. Redundant network modules are difficult to identify in end-to-end learning tasks at this stage, significantly slowing down network inference and potentially interfering with the output of fusion perception. Additionally, training these fusion modules typically requires large amounts of well-annotated multimodal data, further increasing implementation difficulty and cost. For instance, the fusion network design proposed by Li and Wu (2018) focuses on extracting multimodal fusion features, while Zhao et al (2020) introduced a feature decomposition mechanism in the feature fusion and extraction modules. Researchers like Zhang and Ma (2021), Xu et al (2020), and Liu et al (2017) have attempted to improve network structures through dense cascades and the introduction of residual connections. Although these methods have improved the handling of multimodal information to some extent, they still face limitations in distinguishing between useful and redundant information, with redundancy persisting in network designs. Ideally, the design of fusion networks should be more intelligent, guiding network structure design heuristically based on the importance of different modal information for the current task. This would reduce information redundancy and network weights, requiring the development of new algorithms or frameworks capable of automatically identifying and optimising fusion strategies, thereby reducing dependence on manual experience while improving fusion efficiency and network performance. Current deep learning designs for multi-sensor fusion algorithms often overlook the

Sep 1, 2024

By S Raval

The estimation of greenhouse gas emissions from coalmines is increasingly becoming a priority for both operators and regulators. At the same time, involved scientific challenges in the methane measurements is generating significant interest from global research community. Various technology providers are also actively engaged in improving their sensors and platforms to address the measurement challenges and capitalise the market opportunities. This presentation highlights rapidly evolving multifaceted landscape of coalmine greenhouse gas emissions. It covers the advances in sensors for the detections, including ground-based, airborne, and satellite-based systems as well as models for the emission estimations, including attempts to reduce the involved uncertainties.

Sep 1, 2024

By I Mason, M van de Werken, B Zhou, J Hargreaves, W Stasinowsky

A critical step in open cut coal mining is clean removal of the overburden. This is usually achieved by drilling, blasting and digging. A key part of this process being successful is to stop drilling at the correct blast ‘stand-off distance’. The stand-off distance is the distance between the base of the drilled blasthole and the top of the coal horizon to be mined. Having this correct provides a protective cap of rock above the coal horizon so that the blast will fracture all the overburden without damaging the coal horizon or mixing it with the overburden. Drilling beyond the correct stand-off distance causes the blast to continue into the coal horizon, damaging it and mixing it with the overburden, leading to significant losses of coal product. Conversely, drilling short of the correct stand-off distance results in additional work to remove the intact overburden.

Sep 1, 2024

By C Staak, H Mischo, A Fichtner, F Reuter

In mining and remote areas of resource industry, there has been a development towards lacking emergency medical first aid response, that creates a potential disadvantage for patients after work accidents and other medical emergencies compared to standard population. This raises the question how a professional emergency medical coverage can be provided underground, taking into account lacking medical professionals in small resource companies combined with long rescue times. Aiming on the closure of this gap, a team of the mine rescue brigade from the Research and Training Mine Reiche Zeche (Forschungs-und Lehrbergwerk (FLB) Reiche Zeche) of the TUBAF Technische Universität Bergakademie Freiberg in Freiberg/Germany and its cooperating emergency departments of the Freiberg District Hospital and the Zeisigwaldkliniken Bethanien Chemnitz developed a totally new rescue concept using elements from tactical medicine and advanced emergency medicine combined with a specifically designed compact equipment and a highly standardised teaching curriculum. A fully new standardised and condensed tactical medical approach was developed including specifically adjusted equipment, and was taught in a didactically optimised way within 16 lessons in two days. Objective Structured Practical Examinations (OSPE) using manikins and simulated patients were conducted and compared to the identical exam of the reference group, which consisted of advanced paramedics. The standardised tactical medical scheme includes vital functions and body checks, advanced life support, nasal and intraosseous drug application, supraglottic airway management, artificial ventilation, thoracocentesis, bleeding control including tourniquet, fracture repositioning and splinting, transport bedding and thermal preservation. The developed Tactical Medical Mining Rescue (TMR) concept was subsequently included in the German guidelines for mine rescue services in 2022 and is already implemented in many companies in Germany and several international projects.

Sep 1, 2024

By S Gulati, N Sarkar, T Vink, S Battersby, L Okada

This paper examines a successful project implemented by BHP Mitsubishi Alliance (BMA) and the Polymathian team at Deswik, aimed at enhancing short-term scheduling processes to reduce vessel turn times in the BMA Central Queensland coal value chain. The project’s objective was to digitalise the planning process to enable planners to make data-driven insights to improve the profitability of the value chain. The strategy involved developing a digital mining system that incorporates data storage, cloud computing, and the ability to meet the integration needs of both internal and external business systems. This was complemented by a sophisticated, optimisation-based, decision-support tool to enhance the planning teams’ ability to make timely and effective decisions.

Sep 1, 2024

By K Sherry, N Shahbazi

Scope 3 emissions are a set of often overlooked indirect greenhouse gas emissions within a company’s value chain and represent the majority of emissions for many sectors. These emissions arise from activities conducted by entities beyond the reporting organisation’s ownership or direct control and are often challenging to calculate. Scope 3 emissions typically encompass purchasing goods and services, transportation and distribution, managing operational waste, downstream processing and utilising sold products. Within the mining sector, scope 3 emissions often constitute a significant portion of the overall carbon footprint. Therefore, these emissions are a significant aspect of the future of sustainable mining. As the journey towards a world committed to achieving Net Zero Emissions has started, the time to spark a transformative conversation in the mining industry has arrived. Consequently, a better knowledge of scope 3 footprints allows organisations to assess their emission mitigation projects against the total carbon impact of their operations and products.

Sep 1, 2024

By S Padekar, C Tapia, D Likhachev, S Harlikar, D Sapkale

In the quest to access valuable critical minerals, humankind is expanding the frontier into extreme environments like space and deep-sea mining. These ambitious enterprises involve considerable costs and lengthy development cycles to ensure the robustness of mining systems in the face of the harshest conditions and unforeseen challenges. Unfortunately, obtaining information from these unexplored territories is complicated. Data is often scarce, incomplete or impossible to obtain until equipment is deployed, leaving engineers facing many uncertainties throughout the design, testing, production and preparation of such missions. Despite these challenges, these extreme environments operate under consistent physical and chemical principles that can be faithfully digitally replicated. However, unexplored areas and dynamic systems like weather and geology continue to carry uncertainties. While eliminating uncertainties remains elusive, Digital Twins offers a means of robust risk management tool. These virtual replicas can excel in simulating extreme conditions and unexpected events, helping optimise and validate mining system designs tailored for such hostile environments. This study takes inspiration from the Mars Science Laboratory (MSL) Curiosity Rover’s wheel damage rate to develop a Multiphysics Modelling and Virtual Motion Simulation (MMVMS) system. Using advanced Generative Design, this MMVMS system refines the MSL’s design, simulates component and system performance, and assesses the risk of premature damage while operating on Mars. Additionally, MMVMS integrates cutting-edge CAD design technologies from aerospace and manufacturing to realistically recreate the Martian environment and a detailed representation of MSL, allowing mobility verification and validation simulation to test different components in terms of materials, design, weight, power and, therefore, cost. The research highlights the precision of MMVMS in replicating extreme conditions, simulating and evaluating internal and external variables influencing the entire system (Rover) in real-time, and predicting movements, failures, and premature damage. This sophisticated Digital Twin technology, showcased in this research, holds promise not only for space missions but also to be adapted for terrestrial and deep-sea mining operations.

Sep 1, 2024

By T Y. Ko, Y S. Kang, S J. Park, J H. Hwang

The lunar subsurface, particularly the lava tubes formed by ancient volcanic activity, presents a promising environment for establishing safe and sustainable human habitats on the Moon. Tunnel Boring Machines (TBMs), widely used for excavating tunnels on Earth, offer a potential solution for developing these subsurface spaces. However, the unique lunar conditions, including extreme temperatures, high vacuum, radiation, and the extraordinary strength and abrasiveness of lunar rocks, necessitate significant adaptations to existing TBM technology. This study investigates the feasibility of utilising TBMs for lunar subsurface exploration and base construction, addressing the challenges posed by the harsh lunar environment. We review previous conceptual designs for lunar TBMs, highlighting their strengths and limitations in addressing these challenges. Additionally, we explore innovative excavation methods, such as microwave-assisted rock weakening and undercutting techniques, to enhance the efficiency and effectiveness of lunar TBM operations. By evaluating the geological characteristics of the lunar crust and analysing the potential of lava tubes as launching points for TBM operations, this study provides a comprehensive assessment of the technical requirements and operational considerations for lunar TBM implementation. The findings of this research contribute to the growing body of knowledge on lunar base development and pave the way for future human exploration and utilisation of the Moon’s subsurface resources.

Sep 1, 2024

By B Bradák, D Asahina, S Saydam, S Akdag

Human exploration of Mars has been on the horizon of scientific goals for decades now, and as part of the objectives of human missions to various planets, one of the possible goals is opening new economic frontiers by the potential extraction and utilisation of resources, eg mining minerals and using surface regolith (Neukart, 2024). A comprehensive understanding of surface morphology, lithostratigraphy, basic structural geology, and civil engineering technology is essential to conduct mining operations for resource extraction on extraterrestrial planets. For instance, proper assessment of the risks associated with excavation and infrastructure construction under unique environments such as low gravity, surface irregularities, and the presence of regolith is fundamental. Such knowledge has been accumulated through satellite imagery and numerical topographic data using remote sensing technology, as well as seismic surveys by the on-site lander (Knapmeyer- Edrun et al, 2021; Banerdt et al, 2020; Giardini et al, 2020). Recent studies show that Marsquakes could be caused by the release of strain energy generated by the contraction of Mars. In particular, Marsquakes occur around the graben where many faults exist and form regularly spaced patterns. This implies that Marsquakes occur when the stress field of the Martian crust is an extension condition, and normal faults appear on the surface. In this study, we focus on so-called graben structures, one of Mars’s common tectonic structures (Plescia, 1991; Banerdt et al, 1992; Hoogenboom Hagen, 2014). The study aims to provide additional information about the tectonic environment during the formation of such features and, in addition, the internal mechanical-rheological structure of Mars, revealed by the geometrical pattern of faults modelled and simulated in a laboratory environment.

Sep 1, 2024

By O J. Restrepo Baena, S Nowosad, R Webber-Youngman, N Mojtabai, P Foster, A Binder, S Hazuria, erson, S Raval, L Liu

As the mining industry faces times of change, new challenges arise to ensure raw material supply for the younger and future generations. Different scenarios are currently shaping the way we mine and teach mining engineering. Led by an increasing demand for raw materials, net zero requirements for improving long-term operation performance, technological advancements such as automation and digitalisation, safety improvements, environmental considerations and a need for social acceptance, mining is pursuing to change and adapt to these requirements at a faster pace. Such changing times raise new concerns, one of the most relevant is the lower number of students interested or enrolling in mining engineering and related fields leaving mining engineering as one of the less preferred career options between the younger generations. Nonetheless, it is essential to continue addressing and supplying the skill sets that is suited to contemporary and future of the mining industry. To this end, globally, academia is currently undergoing several initiatives such as curricula updates and adaptation, up skilling, improving teaching practices and techniques, including e-learning techniques, enhancing industry-academia and inter-university collaboration, and much more

Sep 1, 2024

By N Udugampola, d A. Seneviratne, X Ai, B Li

With the evolution of mining technology, wireless mesh networks using low-power, long-range technologies such as LoRa are increasingly utilised in underground mining operations. Efficient deployment of wireless nodes in such mesh networks necessitates understanding radio wave propagation behaviour in underground mines. While existing propagation models either remain theoretical or apply only to basic geometric shapes, we propose a practical approach to analyse radio wave propagation behaviour in underground mines using ray tracing simulations with reconstructed 3D models of targeted environments. Our method validated using a set of corridors as a substitute for underground mine environments, involves constructing a 3D model using SolidWorks from LiDAR scans of the environment and performing wireless transmission simulations using the MATLAB ray tracing toolkit. Our simulation model is also fine-tuned by calibrating the raytracing parameters based on real-world LoRa transmission experiments in the actual environment corresponding to the 3D model. This method offers a practical solution for optimising wireless node placement in underground mines, facilitating efficient network deployment while reducing the need for extensive physical testing of radio wave transmissions.

Sep 1, 2024