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By A Seneviratne, Y Li, N Udugampola, X Ai, B Li

LoRa (Long Range) is a low-power, long-range wireless communication technology that has gained significant research interest for its potential use in multi-hop linear wireless sensor networks (LWSNs) for underground mines. These networks deploy LoRa-enabled sensor nodes in underground mines, together with LoRa repeaters placed along mine tunnels to relay sensor data to a LoRa gateway, which connects to a backend network for application-level processing. Since the packets generated by sensor nodes farthest from the gateway have to hop through many repeaters, their probability of successfully reaching the gateway is significantly lower due to the higher chance of packet collisions compared to sensor nodes closer to the gateway, resulting in a lack of network fairness for the sensor nodes. In this paper, we first present an algorithm to improve the fairness of a LoRa LWSN by grouping neighbouring nodes and adjusting the number of packet re-transmissions and transmission intervals for each group. Then, we demonstrate that the fairness of a simulated LoRa LWSN can be improved by approximately 500 per cent by applying our algorithm. We verify our algorithm with network simulations under different network traffic levels and grouping strategies, obtaining fairness improvements in each scenario. Our algorithm and results will pave the way towards developing highly fair LWSNs for underground mining applications.

Sep 1, 2024

By Y Tang, G Si

The analysis of rock fragment sizes plays a pivotal role in various stages of geotechnical and mining engineering. Traditional case-based methods often falter in addressing the variability in rock fragment images due to fluctuating geological conditions and imaging environments. To counter this challenge, AI-based models necessitate training on expansive and diverse data sets, encompassing a wide range of conditions and fragment types. However, the creation of such data sets is often hampered by financial and environmental constraints. This paper introduces a novel approach for rock fragment recognition, which leverages the power of AI for data augmentation, automated annotation and prediction. The methodology integrates three key components: Style-Based Generator Architecture for Generative Adversarial Networks (StyleGAN) for data augmentation, the Segment Anything Model (SAM) for automated annotation, and the multiscale version of you only look once (YOLO-MS) real-time instance segmentation model. The proposed method begins by training a new StyleGAN model using the original data set. It then delves into exploring the latent vectors of different rock fragment images to generate specific ‘style representations’. These latent vectors form the foundational elements of each image in a high-dimensional space, encapsulating critical features such as size, shape, texture, and colour variations. The next step involves conducting quality checks on the generated images to ensure their realism and suitability as training data. Subsequently, the augmented image set is annotated using modified SAM module, followed by training the YOLO-MS real-time instance segmentation model. The performance of this model, trained on the augmented data set, is compared with a model trained on the original data set, particularly in terms of generalisation abilities in new scenarios. The results exhibit a significant enhancement in accuracy, robustness, and generalisability of the model trained on the augmented data set, underscoring the potential of StyleGAN as a powerful tool for data augmentation in geotechnical engineering image analysis.

Sep 1, 2024

By C Zhang, R Liang, I Canbulat, S Saydam, B Li

The integration of digital twins in mining represents a significant advancement towards enhancing operational efficiency and decision-making. Central to this development is the role of visualisation, a crucial element in mining digitalisation. This paper aims to develop a data-driven visualisation solution for the construction of mining digital twins, highlighting how this innovation revolutionises the representation of physical mining environments. It spotlights the shortcomings of conventional visualisation methods, particularly their inability to accurately depict complex underground environments and their predominantly historical orientation. To address these challenges, this paper proposes a novel, data-driven approach. This approach extensively utilises CAD files, encompassing data from geological surveys to intricate mine plans, thereby significantly elevating the precision of digital twins. It supports real-time updates and enables flexible interaction with a variety of data types. Moreover, it introduces a comprehensive data diagram alongside the adaptation of a 3D tile index. This strategy ensures the efficient rendering of extensive mining environments, allowing for a more dynamic and interactive digital twin model. In conclusion, the implementation of data-driven visualisation in the construction of mining digital twins marks a pivotal advancement in the industry’s digital transformation. It promises a more detailed, accurate, and dynamic depiction of mining operations.

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 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 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 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 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

By M Berner, N A. Sifferlinger, E Fimbinger

Today, the advance rate of underground roadway development by drill and blast operation is limited by the need to ventilate the toxic blast fumes after each cycle. In deep mines this usually is only possible during shift changes when the related mine sections are free of persons. This results in roadway development advance rates of 4 m per shift, or 12 m per day. For long roadways this is a limiting factor in mining development in deep mines. Companies like EPIROC, KOMATSU, ROBBINS and SANDVIK are making serious R&D efforts to disc-cutting mobile miners to overcome this bottleneck. However, today, the achieved advance rates are less than 12 m per day in hard rock. If we achieve full robotisation and/or teleoperation from a safe place for drill and blast operation of an underground roadway development section, we could eliminate this bottleneck. Poisonous blasting fumes do not affect robots and machines as long as these fumes do not create aggressive acids. If we can keep the blast fumes isolated in the roadway development section for the shift until the next ventilation opportunity (eg shift change or designated ventilation times), we can do the drill and blast cycle more often in a shift, which will significantly speed up the advance rate. This requires robotisation of all work steps in the section: surveying, drilling, charging of explosives, blasting, loading and transporting material, roof support, installation of infrastructure etc. Also, cache storage for the material is needed. Special care for the ventilation system to keep the blasting fumes under control in the section is necessary. The paper discusses the aspects needed to achieve this robotisation and the related technical and operational tasks.

Sep 1, 2024

By A De, B Palmer, rade, P Stowasser, A Fanning

Mining and tunnelling share many commonalities (eg confined working environments, excavation equipment and processes), but of significance is an overarching commitment to provide safe work conditions and environments. This includes reducing exposure to hazardous airborne contaminants such as dust and fumes, in particular Respirable Crystalline Silica (RCS) and Diesel Particulate Matter (DPM), with methods that are environmentally sustainable. In mining, wet methods are common to suppress airborne contaminants, however these methods are reliant on water availability, can be less effective for respirable dust, can have implications for environmental water contamination and can increase maintenance on mining equipment. In contrast, the use of dust scrubbers that provide filtration of airborne contaminants are well established in the tunnelling industry and frequently used to provide spot extraction (dust control at the source) and act often as a complement to the main ventilation system. This paper sought to learn more about the advancements in tunnelling that could be readily applied to mining to improve health outcomes. The paper includes a review of literature and legislation related to health and sustainability and interviews with three respected, and experienced managers from the global tunnel construction industry. It is from these interviews that the focus of the paper turns to Sydney’s WestConnex underground tunnel network and the success of stage 3A M4-M5 construction link. The findings position dust scrubbers as integral to the overall project success as they enabled a Tunnel Production Line (TPL), where multiple stages of construction could take place simultaneously by controlling high volumes of dust at the source. The findings also suggest efficiencies of using mobile scrubbers, both track mounted and hydraulic stepping systems, to accompany road headers and other equipment throughout the excavation process. The findings have transferable applications to underground mining processes in which workers are exposed to high volumes of dust (eg drill and blast) or situations in which dust control at the source, mobility and flexibility offer value (eg room and pillar mining).

Apr 16, 2024

By M Qiao, A Sugden, W Zong, J Hines, J Roberts, T Ren

Long-term exposure to respirable dust continues to present an occupational health and safety hazard to mine workers in underground mines. Workers who are exposed to mine dust can develop occupational lung diseases including coal workers’ pneumoconiosis (CWP) or ‘black lung’, progressive massive fibrosis (PMF) and chronic obstructive pulmonary disease (COPD). To demonstrate the exposure impact of certain working conditions and improve dust management in longwall development panels, this paper details the development of a computational fluid dynamicsvirtual reality (CFD-VR) based training tool. The tool has been developed as an educational platform to facilitate the effective communication of workplace health and safety (WH&S) dust control measures for continuous miner operators and engineers. The study introduces a promising approach to model ventilation and dust flow patterns based on site-specific data, employing computational fluid dynamics (CFD) for a detailed analysis and visualisation of these mechanisms. Additionally, an algorithm has been developed for processing the large and complex CFD data sets into a form amenable for visualisation within a virtual reality (VR) environment using standalone VR headsets with limited processing power. This training tool has been deployed to mine sites with the specific purpose of educating users on the hazards of dust emissions and the best practices for control.

Apr 16, 2024

By J Holdsworth, L Sutton, A Lavrinec, D Ilic

Air quality is a big topic of discussion in regional mining communities as well as urban environments situated close to port terminals handling bulk solids. Community perception of poor air quality can significantly affect the reputation of the mining operation and handling facilities. Dust monitoring for regulatory compliance relies on using a handful of accurate but very expensive sensors, usually situated at the boundary, relatively far from the activities that generate the airborne dust. These reference monitors measure dust leaving the site but dust mitigation and management on-site largely relies on operator judgement. At a fraction of the cost, small wireless solar powered units can be used to supplement reference monitors in real-time. Due to their compact nature, portability and low price, these units can be implemented on a mass scale to increase spatial resolution of dust measurements and, more importantly, in much closer proximity to both the dust generating activity and the sources of dust. This can provide valuable insights into the origins and timing of dust generation thus producing datadriven decision-making while minimising subjectivity. Similarly, light detection and ranging (LiDAR) is another supplemental technology that can be used to increase the spatial resolution of dust measurements in near real-time, however, the cost of commercial systems even exceeds that of regulatory monitors. LiDAR also presents difficulties in quantifying dust plume concentrations. This study presents learnings of implementing both technologies for dust emissions management. Several low-cost sensor units and a fast-scanning custom-built 3D LiDAR system operating at a range of 1.5 km with a resolution of 1.5 m were deployed on a surface mine to monitor dust emissions from different activities. The project explores the use of real-time sensor data to quantify LiDAR measurements in parallel with integration into mine planning. The approach can assist in prioritising dust mitigation activities thereby reducing instances of emissions exceedance and minimising water use through databased and targeted application. Demonstrated is an opportunity for a step-change in industry best practice as well as commercialisation and operationalisation of the method across different industries, including future mineral extraction.

Sep 18, 2023

By R Mackay, J Brereton

On 30 June 2020, the Mine Land Rehabilitation Authority (the Authority) superseded the Latrobe Valley Mine Rehabilitation Commissioner as the independent overseer of Victoria’s declared mine rehabilitation. Currently, only the Latrobe Valley’s three brown coalmines are declared, with each mine at a different stage of rehabilitation and closure planning: Hazelwood ceased mining in 2017, Yallourn is scheduled to end mining in 2028 and Loy Yang in 2035. The three declared mines are very large, close together (Figure 1) and present significant environmental risks that must be mitigated during rehabilitation and post closure. In addition to fire risks, the brown coalmines are inherently unstable and require continuous monitoring and management of ground movements and groundwater pressures. Since 2007 several damaging events have occurred, highlighting the difficulties of achieving long-term stability, even with good landform design and rigorous ground control management plans

Aug 2, 2023

By L McCallum, G Dale, B Silverwood, T Roscoe, A Costin

The introduction of Progressive Closure and Rehabilitation Plans (PCRPs) in Queensland from 2019 places greater importance on planning and implementation of mine rehabilitation activities. The progress and outcomes of progressive rehabilitation activities is monitored and reported upon to demonstrate success in achieving progress towards the approved post-mining landform, and to inform corrective action where required. The requirements of PCRPs place additional emphasis on mine sites to quantify the risks of successfully achieving planned outcomes. This is particularly challenging given mined-land rehabilitation is a complex process involving decisions on multiple inter-acting management interventions, climatic conditions and spatially variable site characteristics.

Aug 2, 2023

By B Taylor

Although the underground mining environment is arguably safer now than at any time in history, as underground mining operations across the globe increase in-depth, magnitude, and complexity, protecting workers from harm becomes increasingly challenging. In deep, stressed, seismic mines the development face is one of the most hazardous work areas. The active face is usually the furthest extent of the underground workings, so ventilation can be difficult to maintain, exposing workers to high temperature and humidity while working on foot and doing manual labour. While mechanisation has made many tasks easier in modern times, the reality of underground mining is that development charge-up workers still spend long periods directly exposed hazards at the face. In 2019, Orica and Epiroc partnered to co-develop the world’s first fully mechanised development charging unit using fully wireless initiation, called Avatel™. Built on Epiroc’s M2 Boomer carrier platform, the system is designed to allow one person to charge a development face from the safety of a fully enclosed cabin, thereby reducing exposure to hazards at the face. The system was prototyped in Europe before entering commercial introduction in 2022. This paper reviews earlier attempts to mechanise underground charge-up and describes the development journey and engineering challenges of building a mechanised development charging machine.

Mar 29, 2023

By P Oikkonen

Sprayed concrete has played an integral role in underground rock support for nearly a century. However, concrete is also considered to be one of the biggest environmental problems in construction and mining, largely because of the high carbon footprint of cement and aggregates production. This is driving the industry to find ways to cut concrete usage where possible. Improving sustainability by cutting concrete material consumption also reduces application time and costs. Improving concrete properties can make it possible to design thinner linings, but as awareness of safety and longer design lifetimes are driving developments in the opposite direction, it is not realistic to see this as a major factor in cutting concrete consumption. More accessible solutions are focusing on layer thickness control and minimising rebound and wastage. Digital technology and innovation offer excellent tools for improving sustainability while optimising other aspects of the spraying process at the same time. A digital layer thickness control system gives near-real-time information to the sprayer operator with full coverage of the sprayed surface. This enables the operator to achieve consistent layer thickness on the first pass, in comparison to the traditional methods of overspraying with the aim of achieving sufficient layer thickness, probe drilling after the concrete has set, and respraying at a later stage if needed. Operator competence is the single biggest variable in a successful sprayed concrete process, affecting rebound and wastage levels. Unfortunately, the learning curve to become a master sprayer is quite steep and training on a real sprayer and real concrete requires a significant amount of time and money. Training in a virtual reality (VR) environment enables operator training to be carried out in a low-risk environment and provides a way of measuring performance and assessing and certifying the operators. After the VR training period, a novice nozzle operator has the basic understanding to start working on a real sprayer, and an experienced nozzle operator can benefit from the possibility of assessing their performance.

Mar 29, 2023

By R Talebi

A research project to better understand the rock mass behaviour and the seismic response has been conducted during the design and construction of the 9215 level at the E-Block sector of the Northern Star Kanowna Belle Mine. The research program was undertaken at a tunnel located 1100 m below the surface with the results applicable to feasibility studies on underground mining projects in highstress conditions, where failure can occur very soon after tunnel construction. Semi-circular excavation shapes coupled with the use of de-stress blasting techniques were designed to monitor the excavation in conditions of very high stress. The ground support was designed considering high energy dissipation ground support schemes (HED) as described by Arcaro et al (2021). The results indicate a decreased rock mass demand due to the change of excavation shape. Also, localised reduction in rock mass stiffness was achieved due to the implementation of de-stress blasting. Finally, increased ground support capacity was gained by the implementation of the high energy dissipation ground support schemes. The Kanowna Belle Mine has significant ore reserves at depths exceeding 1000 m below the surface. The results of this research will be used to optimise the extraction of the remaining E Stoping Block at depths exceeding 1350 m.

Mar 29, 2023

By B Roache

Ground support installation into the face of development headings has become an accepted practice at many Australian hard rock mines. Ground support is installed in the development face to reduce personnel exposure to rockfall while conducting work tasks such as marking up, installing lifter tubes, charging, and face sampling. The ground support system installed in the face is typically friction bolts and mesh. This support system can be effective at reducing rockfall occurrence, but it also increases the cost of development per metre, in terms of capital for the ground support, jumbo and operator capital allocation and the installation time slowing each drill and blast cycle. Other issues associated with meshing and bolting the development face include management of rock bolts and mesh sheets in the fired dirt of every cut, damage to services such as vent duct, geometry issues when installing ground support onto irregular development profiles and operator error. Fibrecrete installation onto the development face for support is an option considered by many mines, but it can be difficult to manage due to the removal of visual indications of misfires and slowing the mining cycle due to the wait time for fibrecrete curing. The use of Thin Spray Liner (TSL) products in underground hard rock mines has been relatively infrequent in the past, mainly due to issues with cost, health and safety, and liner strength. Kanmantoo Mine investigated the use of TSLs for the purpose of development face support, while collecting data on the costs and practicalities associated with their use. Several TSL products were trialled and a preferred TSL product was selected for use as face support. Cost savings, drill and blast cycle timing improvements and other benefits were achieved while meeting the requirement to reduce rockfall risk.

Mar 29, 2023

By M Bellamy

The DeGrussa copper deposit was discovered by Sandfire Resources in April 2009. Construction of the 1.6 Mt/a concentrator, open pit and underground mining operations commenced in March 2011 with first concentrate production achieved in October 2012. Over the next ten years, DeGrussa grew to include both the DeGrussa and Monty underground mines, establishing itself as one of the world’s premier copper producers with total production of 663 000 t of contained copper by the time the mine closed. Final ore was trucked from Degrussa on 5 October 2022. This paper examines the mine closure experience from both a planning and operational perspective. The paper provides an overview of the site’s mine planning process including the factors involved in determining the end of the mine life and how this was tracked and communicated in the lead up to the end of mining operations. It will also look at some of the specific operational aspects involved in maintaining steady state production all the way through to the last day while facing increasingly challenging conditions. These factors, along with the external factors faced by most of the industry such as labour shortages and COVID related disruptions, contributed to making it an interesting journey to the end of operations at DeGrussa.

Mar 29, 2023