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By A Karrech, G M. Hassan, A Varghese, E Lessing, S Martins

Pumps play a critical role in mining operations, and their energy consumption and environmental impact are significant. This paper addresses the need for a holistic approach to sustainable pump deployment by expanding on previous work presented at IMPC Asia Pacific 2022 and World Mining Congress 2023. The research takes a significant step forward by outlining a structured approach to estimate and demonstrate sustainability tailored for operational slurry pumps. It details the calculation methodologies used to quantify the carbon dioxide emissions from electricity, wear materials and transport, as well as sealing water usage. To enhance practicality and usability, a simplified visual representation—called sustainability metrics—has been developed to monitor overall efficiency. The sustainability metrics consist of the availability, pump efficiency, and water utilisation efficiency. The proposed methodology is integrated with Pumps Condition Monitoring Service to maximise benefits. Three case studies, from iron ore, copper, and nickel operations globally, were employed to evaluate the proposed methodology. The findings demonstrate the critical role of sustainability calculations in understanding pumps operation. These calculations improve awareness of the pump’s role in the sustainability journey and enable effective monitoring. The studies highlight that continuous monitoring paired with effective prescriptive maintenance strategy can significantly reduce power and water consumption while maximising pump availability. The case studies also reveal significant shortcomings in current operational practices and non-optimal maintenance regimes, emphasising the need for practical recommendations to maximise savings and optimise pump performance. In the context of increasing climate change awareness and the imperative for global decarbonisation, this research highlights the necessity of critically assessing methods and operations to drive sustainability in the mining industry. By adopting a holistic approach to sustainable pump deployment, mining operations can effectively reduce their environmental impact while enhancing operational efficiency and economic viability. The proposed methodology and case studies provide valuable insights and practical recommendations for mining companies seeking to achieve sustainable practices and contribute to a decarbonised future.

Sep 1, 2024

By H Zhang, M Karimi, M Hassan, S Saydam, B Li

With the prevalence of Mine Internet of Things (MIoT), different types of sensors have been widely deployed in mine sites for environmental monitoring and operational management. Currently, sensors in mine sites are mainly powered by cables or batteries. However, the deployment and maintenance of a power supply network can be difficult and expensive, and batteries have a limited lifespan. The vibration energy harvesting (VEH) technology can be used to provide power for lowpower sensors in mine sites. This presentation briefly introduces three widely used VEH methods (ie piezoelectric, electromagnetic, and electrostatic). The performance of a commercial electromagnetic energy harvester (ReVibe model D) is evaluated based on the vibration of a lab vibrator (3 g, 50 Hz) and an idling SUV automobile (0.3 g, 25 Hz). Experimental results indicate that a ReVibe energy harvester can generate adequate electricity to power a sensor, and its power output depends on the load resistance as well as the vibration frequency and amplitude of vibration sources. To apply VEH to mining applications, this study also analyses the characteristics of vibration sources at the mine site based on the vibration data collected from various operating machines in a coal handling and preparation plant (CHPP). The vibration analysis results indicate that all the measured vibration sources in the CHPP can generate stable and abundant vibrations, characterised by substantial amplitudes (up to 5.55 g) and low dominant frequencies (ranging from 14 Hz to 25 Hz), which are sufficient for VEH.

Sep 1, 2024

By A Tsang, D La Rosa, L Julian, W Hunt, R Pratama

Mineral extraction is facing the twin challenges of finite resources and increasing environmental and economic costs. Society’s growth is matched by an increase in demand for the earth’s resources. It is incumbent on us as contemporary mining professionals to promote and facilitate ethical and efficient practices. Technological developments have and will continue to allow a decrease in viable cut-off grades, creating new economic opportunities from deposits that were previously uneconomic. Mining low-grade deposits however, even with perfect recoveries, will have a significant environmental cost for the metal won. The greatest opportunity to increase metal with the least environmental cost is to increase the metal yield from existing mines. The determination of mining polygons is a critical juncture where rock is typically subjected to the binary grading of either ore or waste. This is undertaken using a number of factors, such as the mining equipment being used and the recovery in the processing plant. Traditionally, mining polygons were generated on the in situ grade control model. This ignores the complex differential blast dynamics that occur during blasting. Two opportunities exist to improve metal yields: optimise the blast design to achieve the post-blast muck pile that will support the greatest outcome; and generate optimised polygons on the post-blast muck pile. A data set from a Canadian Gold deposit is used to demonstrate the potential benefit of iterative blast movement modelling and grade control polygon optimisation on metal yield. The impact of blasting on the total recoverable metal is presented, highlighting blast design as a critical process in the mining value chain.

Sep 1, 2024

By D Connelly

Quartz deposits are common in nature but the presence of quartz suitable for yielding high purity quartz is exceedingly rare. This paper describes a test work study on producing high purity quartz (HPQ) product to meet the tight product specifications of greater than 99.97per cent, including four and even five nines, for uses including, lighting and fibre optics and modern-day high efficiency solar panels. Due to demand in renewable energy applications the market for high purity silica solar panels known for their increasing efficiency and durability is rapidly growing. Demand continues to rise for the use of high purity quartz in semiconductors, electronics, imaging and sensor markets. Microelectronic components are created by chemically fabricating wafers of semiconductors such as silicon to obtain the desired transport of electrical charge and control of the current. The production of silicon metal from high purity quartz has been designated a Strategic Mineral by the European Commission and by the US Department of Justice due to the growing significance of this metal in various industries. The subsequent processing of quartz is the key step to adding value and aiding technological advances. Overall, the high purity quartz market is a highly secretive, specialised market with increasing opportunities for stakeholders. The attempt to produce HPQ in this work was carried out using an Australian quartz ore following a typical HPQ process flow sheet. The unit processes included primary crushing, scrubbing, magnetic separation, flotation, acid leaching followed by hot chlorination. The results indicate that grinding of quartz requires specialist equipment due to the hardness and extreme abrasiveness of the ore leading to additional iron contamination in the ground ore. The critical impurities were aluminium, iron, sodium, potassium, lithium, titanium, zircon, calcium and magnesium. The chemical refining was found effective. The hot chlorination process needed to be done at 1200°C in a chlorine – hydrogen chloride gas atmosphere. The risk of any gas being released during this stage is very serious and only specialist companies should and can carry out this step. More recent studies reported many new options that appear to facilitate the production of HPQ with the requisite purities more easily, but costly equipment along with highly trained operators are required and hence unlikely to become available in standard metallurgical laboratories any time soon.

Sep 1, 2024

By G McCullough, J Bassan, d P. Knights, C T. Farrelly

By 2045, carbon-neutral mines will be economically producing products that are vital for the world’s transition to renewable energy. After overcoming significant technical challenges (and the investment of significant capital), leaders have successfully eliminated the use of diesel and other fossil fuels by introducing a wide range of new decarbonisation technologies. These leaders will be reaping the benefits of lower production costs (resulting from elimination of diesel), stable and predictable operations, and easier access to capital for their future projects. This paper describes a future scenario of how a net zero carbon and zero-entry mine could operate by taking maximum advantage of technologies in development or already proven in other industries. Some miners have been unsuccessful in their efforts to reach decarbonisation targets. Instead, they have been forced to close or offload their assets to be acquired by operators with better sustainability credentials, or, in some cases, to indigenous or community-based enterprises with vested interest in making operations viable and sustainable. Regardless of ownership structure, all successful mining operations will have fostered strong and positive community relations that bring education, health, security and economic development opportunities to the communities while respecting their traditions, land-uses and culture. As shallow, easy to mine deposits have become scarce, the majority of new mines are underground. Advancements in electric underground technology and the feasibility of ‘zero entry mining’ (with no personnel in active mining zones) has made it increasingly possible to economically operate underground mines, even at shallow depths. The newest mines have a near zero footprint on the surface, produce no harmful by-products, and are employing in-place or in situ methods of extraction that are efficient and low impact. Surface land-uses, such as agriculture and renewable energy generation, continue in the immediate vicinity of the mine, with no significant ground disturbance, community impact or environmental footprint.

Sep 1, 2024

By B Y. Luan, Y Tian, W Zhou, X Lu, Q X. Cai

The unmanned driving technology in open pit coalmines is an important technology that relies on innovation to drive the development of the open pit coal mining industry in China’s transformation of growth drivers and industrial structure upgrading. It is an important path to solve the shortage of mine truck drivers in the future mining, an important way to improve the working environment of open pit mining personnel, and an important foundation for achieving flexible production capacity in open pit mining to cooperate with the coordinated development of new energy. The communication rules at intersections are key to ensuring the safety and efficiency of unmanned driving in open pit coalmines. This paper proposes a collaborative traffic strategy between unmanned trucks for the single bucket unmanned truck intermittent process system in open pit coalmines. Based on the gap theory, this paper analyses the conflict characteristics and establishes a coordinated traffic strategy for the common intersection and merging conflicts of unmanned truck trucks in open pit coalmines, A multi-agent system simulation platform was built to evaluate the coordinated traffic efficiency under different initial average gap sizes of vehicles, with intersection traffic density, vehicle speed, and gap changes as key indicators. The results show that under the simulation conditions of this article, when the initial average gap of vehicles reaches three (four) times or more of the safe distance, the coordinated traffic performance of intersection conflicts (merging conflicts) is better, and the traffic capacity of intersections is close to the traffic capacity without conflicts.

Sep 1, 2024

By J Q. Shi, M Karakus, Y Liu

Predicting the spatial distribution of rock mass properties in cave mining is a critical challenge. In this study, we introduce a novel machine learning-based model to advance our comprehension of rock behaviour. This model specifically focuses on the spatial distribution of rock mass and mechanical properties, a crucial aspect of our understanding of rock mechanics. Our model is inspired by the recognition that neighbouring information serves as crucial prior knowledge for predicting the spatial distribution of these properties, wherein closer neighbours are likely to exhibit similar characteristics. To effectively capture and model these neighbour relationships, we design a neural network-based model to map the spatial locations within the data set into a new highdimensional space. Within this transformed space, we utilise Euclidean distance to identify N neighbours. Leveraging these neighbours, we introduce a straightforward yet highly effective approach—label propagation—to construct a graph that illustrates neighbour relationships. This graph not only facilitates the prediction of the spatial distribution of rock mass properties but also offers a measure of uncertainty for these predictions. We validate the proposed method using a real rock data set and showcase its efficacy in capturing intricate relationships and distributions within rock properties, enabling precise predictions across diverse spatial scales. Our results underscore the potential of machine learning-based approaches to revolutionise the field of rock mechanics, providing valuable insights applicable to geotechnical engineering, mining, and other sectors where an accurate understanding of rock properties is paramount. This model has direct practical implications, offering a new tool for geotechnical engineers and mining professionals to enhance their understanding and prediction of rock properties, thereby improving safety and efficiency in their operations.

Sep 1, 2024

By K Zhao, H Gong, B Li

Health and safety are the first priority for Australian minerals sector. Australia has a global reputation in the mining industry. However, accidents occur every year. Legislation and regulation are important to prevent the accident from occurring, so do the new technologies. It is sad to witness the collision incident persisting and the long called collision avoidance system (CAS) is still not widely used in underground mines. The main reason is that the existing systems are still not advanced enough. The current CASs utilise GPS, infrared, ultrasonic, RFID, Radar, electromagnetic etc have their limitations and disadvantages. For instance, GPS is widely used in a surface mine, but it cannot be applied in underground mine; Infrared and electromagnetic have the false positive problem.

Sep 1, 2024

By M Yadav, K Clode, S Daykin

The mining industry faces numerous challenges related to sustainability and circular economy principles, necessitating strategic approaches to innovation and resource management. As demands for mineral resources continue to rise, mining companies are under increasing pressure to address environmental impacts, minimise waste generation, and optimise resource utilisation. These challenges underscore the importance of Research and Development (R&D) roadmaps as strategic tools for guiding innovation and sustainability efforts within the sector (Jochen Berbner, 2022). A design-led methodology offers a structured approach to R&D roadmap development, emphasising stakeholder engagement, collaboration, and alignment with industry objectives. By leveraging design principles, mining companies can ensure that their R&D initiatives are responsive to evolving challenges and opportunities, fostering a culture of innovation and continuous improvement. Against this backdrop, the project aims to address the pressing challenges associated with sustainability and circular economy in the mining industry. Through the development of R&D roadmaps and the application of a design-led methodology, the project seeks to identify innovative solutions for enhancing resource efficiency, minimising environmental impacts, and promoting sustainable practices within mining operations. This paper highlights the collaborative efforts among Isle, the mining industry, and water utilities, which have yielded tangible benefits. The study demonstrates how the outcomes from the roadmaps outlined below effectively align research with strategic objectives, fostering innovation to address pressing challenges.

Sep 1, 2024

By A G. Dempster, N Barnett, J Oh, S Saydam

NASA’s Artemis III mission is expected to return astronauts to the surface to explore and sample the lunar volatiles by 2026. These volatiles are anticipated to provide scientific insights as to how the Moon was created and economic value to off-Earth operations. These same volatiles can pose health implications to astronauts and Earth based personnel handling lunar regolith samples. Using Australian, USA and NASA airborne contaminant exposure limits and the Lunar CRater Observation and Sensing Satellite (LCROSS) measurements of lunar volatiles in the Cabeus crater ejecta, the minimum mass of lunar regolith that can be safely handled by humans on Earth and in spacecraft can be calculated. This analysis determined a 0.15 grams pure sample of Cabeus crater regolith within a cubic metre of air has enough volatiles to exceed safe working conditions, and 14.9 grams of pure Cabeus crater regolith per cubic metre of air can impact human life. The intent of this analysis is to assist safe handling and exposure calculations for the safe handling procedures of lunar regolith containing volatiles.

Sep 1, 2024

By B P. Voutharoj, R A. Dutch, M Paknezhad, T Ostersen

With the proliferation of new sensor technologies, acquiring multiple data sets over the same ground is becoming cheaper and easier than ever. This new, higher resolution multivariate data provides a significant resource for exploration and resource geologists but comes with the added complexity of effectively integrating the various data sets in useful and meaningful ways to elucidate new geological understanding. Both geophysical data sets and hyperspectral data are extensively used for exploration targeting, providing different information at different resolutions and crustal scales. One of the biggest challenges comes from trying to effectively integrate data sets that record very different physical properties, across the different scales these data are captured at, in a way which can allow for a data-driven analysis of these combined data sets.

Sep 1, 2024

By J Leem, S Mehrishal, J Kim, A Fereshtenejad, J Song

Rock mass discontinuity mapping plays a crucial role in developing a reliable Discrete Fracture Network (DFN), providing insights into the distribution of geometrical and mechanical properties of discontinuities. This enables an accurate assessment of geotechnical infrastructure and mining excavations. Data obtained through conventional mapping approaches are substantially limited by factors such as accessibility and subjectivity. Moreover, these conventional methods may pose inherent risks due to manual techniques, exposing practitioners to potential dangers. Recent digital developments in remote surveying techniques offer opportunities for safer and more reliable rock mass discontinuity surveys. These technologies allow extensive three-dimensional surveying and the production of high-resolution 3D surface models, applicable at any time. This paper presents a workflow for digital discontinuity mapping employing drone technology and photogrammetry. Additionally, the capabilities and challenges of applying artificial intelligence (AI) algorithms in the rock mass discontinuity characterisation process are discussed.

Sep 1, 2024

By A Murphy, I Samsonova, N Eastwood, D Whittle

Part XI of the United Nations Convention on the Law of the Sea (UNCLOS or the Convention) (United Nations (UN) Division for Ocean Affairs and the Law of the Sea, 1982) establishes a comprehensive regulatory framework for the conduct of deep seabed mining (DSM) activities of mineral resources in the Area (defined in Article 1(1) of UNCLOS as ‘the seabed and ocean floor and subsoil thereof, beyond the limits of national jurisdiction’). Under that framework, DSM activities can only take place in the Area pursuant to an approved Plan of Work in the form of a contract with the International Seabed Authority (ISA) (the Authority), a 168-member international body created under UNCLOS to administer the Area. Private contractors can undertake DSM activities if they are sponsored by Member States of UNCLOS, providing a dual system of international and domestic regulatory control and oversight for activities in the Area.

Sep 1, 2024

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, 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 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 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