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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 S F. Wang, J J. Yin

Dust pollution poses a persistent challenge within mining processes, giving rise to a spectrum of concerns, including occupational diseases, mechanical degradation, diminished visibility, and the potential for dust explosion incidents. Existing dust detection and monitoring methodologies face limitations, including insufficient measurement accuracy and intricate processing procedures. Consequently, a comprehensive identification and evaluation system rooted in image processing technology is proposed to facilitate real-time measurements of dust pollution in mining worksites. The study primarily employs grey scale average and fractal dimensions to characterise particle features evident in collected dust images. As a result, the data processing platform can dynamically process data and present dust pollution conditions. Notably, this research integrates the monitoring and assessment of dust pollution with the systematic adjustment of mining parameters, ventilation parameters, and strategies for dust reduction. Through statistical analysis of dust concentration and particle size during mining processes, rock properties such as components and cuttability can inform mining parameters. This information, in turn, guides detailed excavation strategies, including cutterhead speeds, torque, and excavation speed. Similarly, analysing dust characteristics derived from images is a valuable resource for gaining deeper insights into the efficacy of implemented ventilation strategies. By harnessing vision-based information detailing dust concentration and distribution, a wealth of direct guidance becomes available for refining ventilation parameters. This encompasses crucial aspects such as the selection of appropriate ventilation systems tailored to the specific mining environment and the optimisation of operational conditions for ventilation fans. Additionally, the detailed information derived from the visual data allows for strategic decisions on factors like the spatial arrangement of ventilation outlets and the calibration of airflow rates. Moreover, precise choices for dust reduction measures and parameters can be made based on the prevailing dust conditions. Upon real-time monitoring of dust pollution using the proposed method, corresponding measures such as spraying and foaming can be promptly implemented. Crucial parameters, such as spray angles and volume, are integral to these application processes. In essence, the proposed method assumes a pivotal role in not only dust monitoring but also the formulation of preventative and control measures within mining processes.

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 B Taylor, S Evans

Bulk explosive technology for underground mining has not seen any significant technological advances since the widespread transition from ammonium nitrate fuel oil (ANFO) to ammonium nitrate emulsions (ANE) commencing in the 1980s. The in-hole energy profile that conventional ANE systems deliver is limited by the physics of chemical gassing and simple control systems. This compromises the range, precision, and accuracy of energy delivery into the blasthole, and in some cases limits the length of charge that can be delivered. Orica’s 4D™ bulk system removes many of these constraints, enabling better blasting performance across all underground mining methods. This paper reviews work completed at three mining operations across Australia, the United States, and Chile with a focus on how this system can improve mining operations and deliver sustained commercial and productivity benefits into the future. These benefits include improved ore recovery, reduced dilution from waste rock, and reduced overall explosives consumption. This paper also reviews how this new technology can be applied for planning future mining operations.

Sep 1, 2024

By B Gyngell, P Culvenor

Large language models (LLMs) have generated a lot of hype since ChatGPT was released in early 2023. In essence, they allow people to interact with computer systems through natural language and have the ability to generate highly complex text, images and videos (Patil and Gudivada, 2024). It is clear that this technology has significant potential, however most mining companies have not yet found practical applications for it within their operations. In this paper, we present a range of such applications along with the tactical considerations associated with developing and implementing them. We have identified use cases across a variety of operational and functional areas within the mining industry and evaluated them based on their potential business value and ease of implementation. Firstly, we provide an overview of how LLMs work and a review of how LLMs are being applied in other industries to provide best practice inspiration for mining. Next, we present a list of possible applications in mining and a critical assessment of each use case. This section also includes a technical deep dive into the different methodologies for developing the technologies as well as an analysis of barriers to adoption within mining organisations. Finally, we share a discussion of the potential path forward for LLMs in mining and the impact they could have on the industry. We analyse the potential differences between early adopters and laggards in the artificial intelligence (AI) space. This research draws on interviews and surveys with artificial intelligence experts as well as mining subject matter experts to connect cutting edge thought leadership with the specific problems faced by our industry.

Sep 1, 2024

By T Zhao, K Wang, Z Zhang

Tailings pond safety monitoring is vital for preventing dam failures and ensuring environmental safety. Unmanned Aerial Vehicles (UAVs) can enhance tailings pond monitoring with flexible operational cycles and the ability to collect remote sensing data from inaccessible areas. While many mining operations have adopted UAVs for tailings pond management, their full potential in data acquisition and subsequent analytical processing remains largely untapped. This paper explores various case studies where UAVs have been utilised for monitoring key aspects of tailings ponds such as beach line indicators, dam displacement and erosion, slurry discharge processes, and tailings pond capacity. We also present examples where data derived from UAVs have been instrumental in slope stability analysis, seepage modelling, Tailings Dam Breach Analysis (TDBA), and risk prediction. By integrating UAV technology with traditional ground-based sensor techniques, this approach significantly enhances the precision and reliability of hazard prevention and management in tailings pond operations.

Sep 1, 2024

By S Warden, T Neville, P Leckie

At its simplest, the classification and characterisation of an orebody is a matter of Where, What and When. Where and with what spatial resolution are measurements taken, What properties are measured, and When are the data acquired, processed, and delivered to create the most value. This paper delves into how existing and near-term advances in measurement technologies, field automation, and whole-system-digitisation are combining to open new routes for mine and exploration productivity improvement. Commencing when the initial exploration hole is dug, the advancement in deployment of survey technology—from expert-operated, to driller-operated, to driller-integrated—is used to demonstrate a template for adoption of higher technology measurements. We then introduce and discuss the multi-use measurement as offering outsized returns from a single measurement run, highlighting two new technologies that acquire rock strength while drilling and downhole assay data as examples. For rock strength, we highlight a novel approach to determining Uniaxial Compressive Strength (UCS) while drilling, its relationship to and advantages over Mechanical Specific Energy (MSE), and how it offers utility to multiple downstream processes. For downhole assay, we detail how a back-tophysics approach to Pulsed Fast and Thermal Neutron Activation (PFTNA) analysis offers significant advantages over other measurement methods and earlier implementations of PFTNA, generating a rich data set that can significantly extend and improve the information on which mining decisions are made. Finally, we discuss the possibilities enabled via optimising data delivery, collection, and curation— noting a fundamental limitation of historical systems and exploring the possibilities that will be unlocked by soon-to-market solutions that better enable Orebody Characterisation data to (virtually) move in space and time with rock material post-blasting. Ultimately, the value of optimising the Where, What, and When from point of measurement to the moment it generates maximum value will create greater life-of-asset production for a lower cost and energy input.

Sep 1, 2024

By A Krishnan, C Garcia, I Luna-Berbesi

The discovery and exploration of deposits are progressively shifting to extremely remote regions and greater depths. As a result, exploration costs and the economic risk of a bad investment increase. Current megatrends in the exploration and mining sector indicate a growing demand for the implementation of automation, digitalisation, and machine learning techniques. The implementation of a multi-sensor-based core logging device (DMT, 2024) was done on 400 m of drill cores to optimise interdisciplinary processes in terms of time and quality, by using interlinked and consistent data in real-time, to obtain reliable predictions that support and speed up decision-making. The results are consistent with the laboratory data previously obtained by the mining company, highlighting the benefits of introducing ANCORELOG into their core logging procedures.

Sep 1, 2024

By A Innis, A Bye, B McCarthy, S Glover

Technology adoption in the mining industry has been steadily increasing over the past decade, driven by the need to improve operational efficiency, safety, sustainability, and profitability. As mining companies wish to implement solutions to improve mining safety and productivity, various technologies are being integrated into mining operations to enhance processes, reduce risks, and optimise resource utilisation. Adoption of new technologies such as autonomous trucks requires a strong focus on foundational operational technology (OT) and a systems-thinking approach. OT support is critical however, OT is traditionally not considered or integrated into standard maintenance activities. Consequently, sourcing and applying service support to OT systems in real-time has posed significant challenges to date. Neglecting the monitoring and upkeep of these operational technologies and equipment can lead to a host of adverse consequences. Operating instability becomes more prevalent, necessitating reactive measures, and the vulnerability to cybersecurity threats increases significantly. To address OT monitoring and maintenance challenges, a systems wide mindset and remote support discipline must be utilised. Remote operations support refers to real-time, 24/7 monitoring, control and support of site OT: network, production systems, maintenance systems, enterprise systems and mobile and fixed plant through a single interface remote from site. The presence of a disciplined team, grounded in a systems-oriented approach, is of the utmost importance to remote monitoring, given the intricate interdependencies of OT systems. The ability to understand the relationships among multiple systems, coupled with the capacity to distinguish between symptoms and root causes, assumes a pivotal role in operations. Through diligent monitoring and the astute understanding of system thresholds, remote operations support can actively identify and alleviate constraints, in turn, serving as the enabler for transformative advancements in technology output.

Sep 1, 2024

By L Muñoz, L Steffen, W Vilas Boas, G Gontijo, R Macedo, C Braga, d D Machado, G Stevenson

Mines operating close to communities face growing challenges, especially with their drilling and blasting activities. Proper management of environmental and community impacts is critical to provide sustainability to the mining business in the long-term, by enabling the licensee to operate. This paper will present new technology solutions to minimise the impacts to communities and the environment from blasting operations. A case study of the wireless initiation projects conducted at Kinross Morro do Ouro Mine (located in Paracatu, Minas Gerais – Brazil), will be presented. Focused on overcoming the complex challenges in the mine, Orica and Kinross searched for initiatives to optimise the drilling and blasting operations. The team evaluated the WebGen™ wireless initiation system for controlling environmental impacts as well as operational flexibility and productivity. Since January 2023, three planned wireless blasts to demonstrate the technology and applications were executed. In the tests, the vibration level was able to be maintained lower than the limit of 3.0 mm/s while dust and flyrock impacts were well controlled. The main benefits of using this technology for the Morro do Ouro Mine are: reducing the number of blasts while increasing the blasted mass per month; control of projection of fragments using additional cover; dust control by watering the bench easily; lightning initiation risk reduction due to the absence of wires or tubes on the surface; flexibility in changing the blast day to better control the noise and dust; flexibility in mine planning mining (potential application in the future). The use of the WebGen™ wireless initiation system, enables improved productivity while enhancing safety and reducing impacts to communities. Implementation of this technology has enabled Kinross Morro do Ouro Mine to build trust with its neighbours, maintain the license to operate, and helping to mobilise resources in a sustainable way. This has allowed Kinross to position Morro do Ouro Mine as a world reference operation, especially in relation to innovation, safety, and social responsibility.

Sep 1, 2024

By K Rau

The overall success of a mining operation is directly impacted by the reliability and availability of mining equipment. Heavy-duty vehicles such as excavators and haul trucks are used for conveying of bulk material and improving such assets’ availability helps reduce costs, increase throughputs and improve safety (Ravande, 2022). If a mining operation’s key performance indicators (KPIs) are tied to operational performance, then overall equipment effectiveness (OEE) is an essential metric to track progress and to identify areas of improvement.

Sep 1, 2024

By P Mugebe, M Yahyaei, M S. Kizil, R Low

This paper seeks to establish an empirical relationship between the impact of mining technological innovation implementation and a company’s market value. The company’s market value is represented by its stock price. In a bid to ascertain the relationship, a stock price prediction model is sought to be established using the firm-specific factors impacted by the implementation of innovative technology. This work is performed under the watch of the prevailing macroeconomic factors. The background anchors in the understanding that the difference between the economic status of a mineral deposit and its uneconomic status lies in the level of mining technological innovation most prevalent at a given time (Hartwick, Olewiler and Preuss, 1986; Wellmer and Scholz, 2017; Wright and Czelusta, 2003). This is derived from productivity improvement, resulting in sustainable profitability due to technological innovation. Unfortunately, there is not an adequately established relationship that links this technological innovation impact to the share price performance of the mineral commodity company.

Sep 1, 2024

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 R Daiyan, G Burge, M Haider Ali Khan

Australia’s mineral and metal exports have a substantial carbon footprint, twice that of its domestic emissions, mainly due to fossil-fuel-dependent downstream processes like processing into secondary metals and their transport. The country’s vast renewable energy and low-carbon hydrogen potential offer a promising alternative to mitigate this impact. These resources can be leveraged to displace fossil fuel use and become embedded into the metals value chain. Ultimately, it will yield ‘Green Metals’ that can be scaled to reduce the environmental footprint and provide an avenue for Australia’s vast green resources to be embedded (incorporated during production and supply) in green metals that can be exported. One potential green metal is copper, which is in great demand and likely to drive global decarbonisation through renewable electrification due to its role as an energy conductor. Given that Australia is a large producer and exporter of copper, this paper provides a techno-economic model of the copper value and applies it to Queensland (a hub of Australia’s copper production) as a case study. The results show that under incumbent hydrogen (A$8/kg) and renewable energy costs, the cost of green copper would be A$9704/t (~10 per cent higher than current copper costs). Further analysis revealed that the cost of hydrogen is a major cost driver; therefore, if the cost of hydrogen can be reduced to A$2/kg (a 2030 target of the Australian government), the cost of green copper would become competitive. Furthermore, if a carbon pricing regime ($54–79/kgCO2) is introduced, green copper would become competitive at a hydrogen cost of A$3/kg. Altogether, these findings provide insights for a future green copper export opportunity in Australia. Additionally, as the next step, the model can be extended to include other metals and released as an open-source resource for assessing global green metal opportunities.

Sep 1, 2024

By H Bao, M Nehring, M Kizil, P Knights

The mining sector, a notably energy-intensive industry worldwide, is a major consumer of fossil fuels, leading to significant carbon emissions globally. The move towards electrification, coupled with advancements in battery technology, has redirected focus from traditional diesel-powered solutions to battery-powered alternatives. This paper introduces a novel mining haulage system, termed the Battery Trolley system, and examines its theoretical foundations, configurations, and operational processes. It offers a comprehensive analysis of the system’s characteristics and limitations. Through a hypothetical road simulation, the study analyses various battery mining trucks, calculating energy consumption based on force parameters and tailoring battery sizes to contemporary materials and technology. When assessing various battery truck alternatives—considering aspects such as battery size, effective payload, duty cycle, energy efficiency, productivity, and single-shift production—a range of performance outcomes and characters become apparent within the mining context. The findings indicate that Battery Trolley configurations, requiring smaller battery capacities, entail lesser compromises on effective payload. Consequently, these configurations achieve a higher duty cycle, reduced energy consumption per tonne, heightened productivity, and enhanced singleshift production capabilities compared to Battery-only alternatives. The comparative analysis of Battery Trolley with stationary charging (BT-S) and Battery Trolley – dynamic charging (BT-D) underlines that battery Trolley systems are capable of overcoming the challenges associated with battery size, thus successfully fulfilling the production demands of large truck applications in mining. This positions Battery Trolley systems as a more advantageous option for the decarbonisation of mining fleets, underscoring their potential in contributing to the sector’s sustainable evolution.

Sep 1, 2024

By M Liang, C Putzmann, D Gokaydin

The mining industry faces numerous challenges in swiftly evaluating and exploiting new mineral deposits to meet the escalating demand for critical minerals and metals. These challenges necessitate the adoption of innovative techniques and technologies to expedite development cycles and facilitate the efficient exchange of knowledge and expertise. Traditional mineral exploration methods rely heavily on data governance, visualisation tools, and expert interpretation skills, often operating in isolation and limiting the integration of valuable data and knowledge (Lindsay and Perrouty, 2019). To address these integration challenges and bridge the industry’s knowledge gap, the concept of a digital twin offers a holistic solution (Ahn, 2021; Nagovitsyn and Stepacheva, 2021).

Sep 1, 2024

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 S Nowosad, A Binder, O Langefeld, M Bothe-Fiekert, F Apollo

The mining industry faces complex and urgent challenges driven by an increasing demand for raw materials, and a socially demanding globalised world. The extraction of primary raw materials is today more important than ever as one of the cornerstones towards a sustainable future since the increasing demand for the raw materials required for the energy transition. In the last three years, leading countries as USA, China, Canada, Australia, and the European Union (EU) have developed and adopted strategies to enhance domestic extraction capabilities, diversifying sources, fostering innovation in recycling, and promoting international collaboration related to critical raw materials. On 2022, the Inflation Reduction Act was signed into law in the USA, in June 2023, the Australian Critical Minerals Strategy 2023–2030 was published and in March 2024, the Council of the EU adopted the European Critical Raw Materials Act. On the other hand, raw materials extraction is facing higher environmental and safety standards and regulations, as well as scrutiny from the broader public. Regrettable environmental accidents as tailing dam failures or acid mine drainage occurrences have led to a general distrust of mining activities leaving mining companies with the dual imperative of increasing output while implementing sustainability, decarbonisation, and circularity as a core value in their production processes. This challenging environment offers the opportunity to enhance ‘blue mining’ (BM) as a sustainable holistic approach that integrates the principles needed to plan sustainable, reliable, and responsible mines for today’s and future generations by implementing the principles of circular economy (CE). This requires a fundamental shift from the traditional linear economy approach to a sustainable, circular economy strategy. At its essence, BM encapsulates four crucial aspects – energy, ergonomics, water, and circularity and integrates these four aspects into integrative mine planning, defining clear goals and objectives from the ‘blueprint’ of a mine towards a beneficial post-mining activity. Its implementation can lead to maximisation of resources beyond the life of the extractive mine and sustainable use of materials by integrating the principles of circular economy and multiuse mine, see Figure 1. These concepts complement and recognise the need to minimise environmental and social impacts while advancing economic development. Finally, this contribution explains the requirements and challenges of moving from linear to dynamic planning approaches under the BM concept. This way, BM stands as an approach that can contribute to the mining industry receiving necessary approvals and support from society leading to a long-term transformation of the industry’s image.

Sep 1, 2024

By M Yahyaei, P Knights, M S. Kizil, J Qu

Digital Twins (DTs) are transforming business operations across many industries through their accurate representations of physical entities enabled by IoT technologies.

Sep 1, 2024