Editorial Feature

The Future of Mining: Trends Shaping the Global Industry in 2024

Mining is critical for society as minerals are required to support the increased demand for applications in digital electronics and renewable energy. The digital transformation titled Mining 4.0 and Mining 5.0, achieved through the utilization of automation, the Internet of Things (IoT), Robotics, and Artificial Intelligence (AI) has revolutionized the mining industry, and companies are opting for sustainable mining through the development of technologies and sensors that are safe for the environment. This article will discuss the trends shaping the mining industry in 2024.

Engineer programs autonomous bulldozer using digital tablet

Image Credit: Scharfsinn/Shutterstock.com

New Mining Technologies

In the new technological model for the mining industry, digital communication technologies, supported by cyber-physical systems and the Internet of Things, enable unprecedented levels of labor safety and a significant increase in productivity.1

This is particularly evident within the mining industry, where IoT solutions have assisted mining firms in avoiding operational redundancies, increasing productivity while lowering costs, and improving safety measures.

IoT in mining includes drilling, where machines operate independently; haulage and transport, where trucks operate independently; health and safety; energy usage; and environmental monitoring. The prime technologies optimizing mining operations using IoT are integrated into autonomous drones, proximity sensing mechanisms, analytics frameworks, and safety technology.2 

Mine Internet of Things

A specialized form of IoT called Mine IoT (MIoT) has become a preferred technology for mining companies worldwide. The MIoT enables a systematic interconnection between mining devices. In simple terms, MIoT can be summarized as a specialized network of sensors and actuating mechanisms connected to share data related to mining operations. Sensors collect data, and actuators adjust systems and warn of abnormal conditions when values exceed preset limits. In other words, MIoT facilitates real-time monitoring of mines, predicts potential accidents, optimizes mining processes, and manages personnel and equipment.3

Mining 5.0

Mining 5.0 encompasses three innovative technological domains, including Large Language Models (LLMs), scenario engineering, and digital twins.4 LLMs are neural network models with a massive number of parameters, representing significant advancements in deep learning and Natural Language Processing.

The mining LLM is a typical multimodal model, distinguished from autonomous driving LLMs by its incorporation of specialized knowledge in mining operations. This specialized knowledge includes geological features of mining areas, traffic rules, and operational patterns, enabling the mining LLM to intelligently and efficiently accomplish various tasks in practical applications.5

Artificial intelligence

Artificial intelligence has evolved immensely, and analytical models have been developed to provide insights into specific situations. Certain models trained using deep learning and other latest approaches achieve a high level of accuracy but are very slow and limit their interpretability. To address these challenges, scenario engineering has emerged, focusing on designing and reconstructing scenarios, assessing the intelligence level of models, developing corresponding metrics, calibrating and certifying training data, and formulating strategies for model training and validation.

Digital twin technology

Digital twin (DT) technology, originating from the industry, emphasizes constructing a digital model based on ontology to comprehensively replicate a product's entire lifecycle. One of the critical attributes of DT is the ability to receive data from the ontology and offer real-time feedback, enabling bidirectional information flow.5

Simulation modeling of geophysical and technological processes using DT enables testing in a virtual environment. This transition moves decision-making from an autonomous support system to a networked one, verifying decisions in real-time.

A mining industry DT system enables bidirectional real-time data flows between the physical and virtual worlds. Most mining setups utilize DTs to solve issues related to geological complexities, integrating older systems and mechanisms, cybersecurity threats, and lack of standards.6

Advanced digital technologies

Major mining companies have adopted digital technologies to efficiently optimize mining operations. The research team at Rio Tinto in the UK has created a framework called the Mine Automation System (MAS). The system's usefulness lies in its ability to collect 98 % of data from the company’s mines and assemble it into a simple standard format, which can be visually displayed using Rio Tinto Visualization (RTVis). It successfully includes data from autonomous equipment made by various manufacturers. Furthermore, Rio Tinto also tested the first fully automated water trucks at the Gudai-Darri iron ore mine in Western Australia, making it the only mining company to integrate the novel technology in mining operations.

Another major mining firm, Legacy Minerals, deployed AI technology to uncover platinum group elements (PGE) and nickel-copper-iron sulfides at the Fontenoy project in New South Wales, Australia.

"The key driver of this discovery is the implementation of artificial intelligence through our alliance partner Earth AI," said Legacy Minerals CEO and Managing Director Christopher Byrne.

He added, "This is the first confirmed discovery of magmatic-related nickel-copper sulfide mineralization in the 700 km long ultramafic belt that hosts the Fontenoy project."

In another key development, US-based Earth AI developed a predictive mineral detection model. The company’s predictive model successfully predicted mineral deposits in two out of three attempts, with a success rate of 75 %. The mining industry's general success rate is only 0.5 %, making it a significant breakthrough.

Using predictive technology trained on remote sensing, geophysical, and exploration data, Earth AI’s solution identifies nickel, copper, zinc, and vanadium prospects over 100 times faster and more cost-effectively than traditional methods.7

An Overview of Sustainability in the Mining Sector

Mining companies harness digital technologies and green energy sources to power their mining operations to entirely or partially replace conventional hydrocarbon energy sources.

The harmful emission data and GHG concentrations are collected using IoT to monitor emissions in different regions. AI algorithms then process this data using advanced analytics to provide insights. These help minimize costs, reduce energy consumption, reduce waste, and identify ways to mitigate GHG emissions.8

Mining decarbonization

The utilization of renewable energy sources has proved to be a game changer. Using low-carbon emitting sources reduces harmful emissions by around 40 %. It involves decarbonized energy sources for powering mining activities, automated electric vehicles and trucks, and battery-powered drilling equipment where possible.

A prime example is the Borden mine in Canada, where electrification was achieved without compromising mining efficiency. The mine has replaced conventional diesel-powered trucks with electrically powered trucks, leading to energy savings and a significant CO2 reduction.9

Land restoration in mining

Mining companies and governments worldwide are paying significant attention to restoring land damaged by mining activities and implementing water restoration and waste management strategies.

Land restoration is a complex process involving thorough geological conditions analysis, the study of hydrological conditions, soil analysis, etc. to meticulously finalize a plan. Various processes, such as fly ash and biomass-based adsorbents, have been used for water treatment and the removal of heavy metals from water bodies affected by mining activities.10

Social, Economic Factors, and Supply Chain Trends Affecting the Mining Sector

Due to the growing focus on Corporate Social Responsibility (CSR) and the development of various standards and principles in the global mining industry, analyzing the relationship between CSR and economic performance in this sector seems necessary.

The term "social license" initially used to describe the challenge of establishing a relationship between local communities, organizational behavior, and CSR, now represents community support during mining operations.

Since mining operations occur in specific locations and companies cannot relocate their activities, establishing and maintaining good relationships with indigenous, local, and societal groups is crucial.

Mining can be beneficial as it directly impacts the Human Development Index (HDI), reduces corruption, fosters a stable political situation, enhances accountability, eradicates inequality, and improves the Gini coefficient. It has actively decreased the unemployment rate and provided vital materials to supply chains in other sectors.11

With supply chains facing severe disruptions such as global pandemics, climate events, floods, bushfires, hostility in the Red Sea, industrial action at shipping ports, and ongoing military conflicts, the downstream effects on businesses, consumers, and the global mining industry are significant.

Dr. Elizabeth Jackson, Associate Professor of Supply Chain Management at Curtin University, has highlighted the importance of supply chain technologies that can be used to develop activities in the mining industry. The adoption of blockchain technology ensures product authenticity throughout the supply chain, which is crucial for mining products sourced from Australia and other countries with less sophisticated environmental and social governance (ESG) around mining practices.

Digital twins, used for simulating scenarios, are valuable for planning and product delivery, adding value throughout the supply chain. Investing in technology is a great way to improve operations, but it comes at a cost. In an economic environment characterized by high inflation, high diesel prices, and high labor costs, small operators in the mining sector may be criticized for not adopting this technology quickly.12

Regulatory Changes and Overview of Risks in the Mining Industry

This year’s edition of KPMG’s Mining Risk Forecast explores the shifting concern for the mining and metals sector, with climate change risk as the emerging frontrunner.

With new rules and regulations emerging almost every day, climate change is now closely related to maintaining a social license to operate.

While mining companies have long considered their impact on communities and the environment, the urgency to meet decarbonization objectives has intensified due to regulatory changes. In 2023, commodity price risk was the top concern but has dropped to the third position.

By recognizing and addressing these risks, mining companies can better prepare for the future and align their operations with global sustainability goals, securing their social license to operate and ensuring long-term viability.13

Workforce in the Mining Industry

For years, training and education programs in the mining industry have focused on short-term needs with a quick return on investment. However, miners should develop long-term education strategies.

Instead of only focusing on immediate needs, miners must predict future talent demands and create training and education plans accordingly.

Some mining companies have begun formal training programs to fill skill gaps expected in 2024, particularly in Canada and Australia. However, much of the training investment goes to managers and high-level professionals.14

With Washington's policies and funding to boost fair trade mineral partnerships and develop a domestic supply, the US mining sector intends to quickly train a new workforce to keep production going.

"The U.S. must prepare the next generation of mining engineers, metallurgists, and geoscientists to build a secure, transparent, and high-quality critical minerals supply chain that will support our economic and national security," said Danielle Woodring, director of legislative affairs for SAFE's Center for Critical Minerals Strategy.15

Conclusion

The major trends in the mining industry focus on sustainable mining and implementing digital technologies to optimize mining operations.

The mining sector is undergoing a profound transformation driven by advancements in digital technologies, including IoT, AI, and digital twins, collectively pushing the boundaries of efficiency, safety, and sustainability.

As Mining 4.0 and Mining 5.0 take hold, these technologies are optimizing operations and paving the way for greener practices and more robust supply chains.

The industry's focus on sustainability, workforce development, and regulatory compliance is essential for securing its future, ensuring that it remains a critical pillar in the global economy while meeting evolving environmental and societal expectations.

References and Further Reading

  1. Zhironkina, O. et. al. (2023). Technological and Intellectual Transition to Mining 4.0: A Review. Energies. 16. 1427. Available at: https://doi.org/10.3390/en16031427
  2. Global Data (2024). Leading mining companies in the Internet of Things theme. Mine. Digital. (Online). Available at: https://mine.nridigital.com/mine_feb24/leading-mining-companies-internet-of-things [Accessed on: June 05, 2024].
  3. Zhang, H. et. al. (2023). Recent Advancements in IoT Implementation for Environmental, Safety, and Production Monitoring in Underground Mines. in IEEE Internet of Things Journal, vol. 10 (16). 14507-14526. Available at: https://www.doi.org/10.1109/JIOT.2023.3267828
  4. Chen, L. et. al. (2023). Mining 5.0: Concept and framework for intelligent mining systems in CPSS, IEEE Trans. Intell. Veh. 8(6). 3533–3536. Available at: https://www.doi.org/10.1109/TIV.2023.3285417
  5. Chen, L., Li, W. et. al. (2024). Smart Mining With Autonomous Driving in Industry 5.0: Architectures, Platforms, Operating Systems, Foundation Models, and Applications. in IEEE Transactions on Intelligent Vehicles. 9(3). 4383-4393. Available at: https://www.doi.org/10.1109/TIV.2024.3365997
  6. Plavšić, J., & Mišković, I. (2023). Industrial applications of digital twin technology in the mining sector: An overview. CIM Journal, 14(2), 97-106. Available at: https://doi.org/10.1080/19236026.2022.2145431
  7. McClelland C. et. al. (2024). Legacy uses AI to discover platinum in Australia. Mining.com (Online). Available at: https://www.mining.com/legacy-uses-ai-to-discover-platinum-in-australia/ [Accessed on: June 06, 2024].
  8. Groundhog Mine Digitization & Automation (2024). How Mine Digitization and Automation is Increasing Productivity and Safety in Mining? (Online). Available at: https://groundhogapps.com/mine-digitization-increasing-productivity/ [Accessed on: June 06, 2024].
  9. Pradhan, G. et. al. (2023). Bauxite Mining Waste Pollution and Its Sustainable Management through Bioremediation. Geomicrobiology Journal, 41(4), 335–344. Available at: https://doi.org/10.1080/01490451.2023.2235353
  10. Ighalo, J. et. al. (2022). A review of treatment technologies for the mitigation of the toxic environmental effects of acid mine drainage (AMD). Process Safety and Environmental Protection, 157, 37-58. Available at: https://doi.org/10.1016/j.psep.2021.11.008
  11. Yousefian, M. et. al. (2023). Corporate social responsibility and economic growth in the mining industry. The Extractive Industries and Society, 13, 101226. Available at: https://doi.org/10.1016/j.exis.2023.101226
  12. Southway, K. (2024). BROKEN LINKS: Fixing Australia’s mining supply chain. (Online). Available at: https://australianminingreview.com.au/features/broken-links-fixing-australias-mining-supply-chain/ [Accessed on: June 07, 2024].
  13. Ampla. (2024). Mining strategies and risks for 2024. Energy Resources Law. (Online). Available at: https://erlaw.org.au/News-Resources/Latest-News/mining-strategies-and-risks-for-2024 [Accessed on: June 07, 2024].
  14. Parysl, D. (2024). Labour shortage: Doubling down on workplace training in Canada’s mining sector. (Online). Available at: https://www.canadianminingjournal.com/featured-article/labour-shortage-doubling-down-on-workplace-training-in-canadas-mining-sector/ [Accessed on: June 08, 2024].
  15. Warner, K. (2024). U.S. seeks to rebuild mining workforce. (Online). Available at: https://www.metaltechnews.com/story/2024/05/29/tech-bytes/us-seeks-to-rebuild-mining-workforce/1780.html [Accessed on: June 08, 2024].

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Ibtisam Abbasi

Written by

Ibtisam Abbasi

Ibtisam graduated from the Institute of Space Technology, Islamabad with a B.S. in Aerospace Engineering. During his academic career, he has worked on several research projects and has successfully managed several co-curricular events such as the International World Space Week and the International Conference on Aerospace Engineering. Having won an English prose competition during his undergraduate degree, Ibtisam has always been keenly interested in research, writing, and editing. Soon after his graduation, he joined AzoNetwork as a freelancer to sharpen his skills. Ibtisam loves to travel, especially visiting the countryside. He has always been a sports fan and loves to watch tennis, soccer, and cricket. Born in Pakistan, Ibtisam one day hopes to travel all over the world.

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