The future of the mining industry will be shaped by a range of disruptive themes, with artificial intelligence (AI) being one of the themes that will have a significant impact on mining companies. A detailed analysis of the theme, insights into the leading companies, and their thematic and valuation scorecards are included in GlobalData’s thematic research report,Artificial Intelligence (AI) in Mining – Thematic Research. Buy the report here.
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The mining industry is under more pressure than ever to increase efficiencies. This comes as declining ore grades and more disparate and remote deposits create greater challenges in securing new resources, and rising mining costs drive the need for greater productivity at the mine site. At the same time, there is a strong focus on ensuring safety and sustainability within mines. AI can address many of these challenges and inefficiencies through several key technologies in the value chain, including computer vision, smart robots, data science, and machine learning.
Exploration costs can be reduced by using AI to identify the most likely locations of mineral deposits. Predictive maintenance can ensure that equipment defects are solved before they become extremely costly and ensure that equipment downtime is kept to a minimum, increasing productivity. Smart sensors and cameras aid automated equipment while also monitoring the safety of workers in mines.
However, not all companies are equal when it comes to their capabilities and investments in the key themes that matter most to their industry. Understanding how companies are positioned and ranked in the most important themes can be a key leading indicator of their future earnings potential and relative competitive position.
According to GlobalData’s thematic research report, Artificial Intelligence (AI) in Mining, leading adopters include: Goldcorp, BHP, Rio Tinto, Freeport-McMoRan, Fortescue Metals Group, Newcrest, Barrick Gold, and Dundee Precious Metals.
Insights from top ranked companies
Fortescue Metals Group
Fortescue has undertaken one of the largest fleet conversions to autonomous haulage projects, with almost 200 autonomous trucks operating at its Solomon and Chichester hubs. The fleet includes Cat 793F, 789D, and Komatsu 930E haul trucks. Since 2013, the fleet has safely travelled over 52 million km and moved 1.5 billion tonnes of material. Some 900 additional assets, such as excavators, wheel loaders, and light vehicles, are integrated with the autonomous fleet using CAT Minestar Command for Hauling Technology. Fortescue’s autonomous haulage fleet has delivered a 30% increase in productivity. Fortescue plans to use the data collected from the autonomous haulage fleet to understand their operations better and look for ways to optimise, such as haul road design and maintenance scheduling.
Rio Tinto has been incorporating automation into its operations for more than a decade to improve safety, efficiency, and reduce the cost of operations. Automated trucks, drills, and trains are used to remove driver error, thus improving safety. Rio Tinto is closing the gap on BHP – the opening of its Gudai-Darri iron ore mine will add 23 CAT 793F autonomous haul trucks.
The company’s Iron Ore business operates AutoHaul, the world’s first fully autonomous heavy-haul long-distance railway system. AutoHaul transports iron ore to port facilities in the Pilbara region of Western Australia. Around 200 locomotives on more than 1,700km of track have travelled over 7 million km to date. Each 240-wagon hauler is 2.4km long, requiring two to three locomotives to transport 28,000 tonnes of iron ore, an average of 800km over 40 hours. Using this autonomous technology reduces risk at level crossings and auto-responds to speed restrictions and alarms, improving overall safety. By eliminating the need to transport drivers to and from trains mid-journey, almost 1.5 million km of road travel are saved annually. This also removes the need to change drivers two to three times during the journey, saving an hour from each journey and increasing average speeds by between 5% and 6%. AutoHaul can move about one million tonnes of iron ore a day. Loading and unloading product from the wagons is an entirely automated process.
BHP’s Maintenance Centre of Excellence performs ML on vast troves of data collected from its operational equipment. This provides actionable insights for predictive maintenance on items such as haul trucks and improving supply chain management. The company also employs self-driving trucks to reduce accidents caused by fatigued drivers and automated drills. BHP fortified its supply chain during the COVID-19 pandemic using analytics. At its 2019 SmartMine conference, the company demonstrated its use of ML to interpret geological data and generate targets.
The company also currently has the largest fleet of autonomous trucks in operation with 300 spread across ten mines. The company has invested evenly across Komatsu and Caterpillar with a recent investment at South Flank with 42 Komatsu 930E ATs. It has operated a fully-autonomous truck fleet at its Jimblebar mine in Western Australia since 2017 and has cited benefits such as productivity increases of 20%, operating cost reduction of 20% and over 90% reduction in haul accidents due to the automation of trucks.
To further understand the key themes and technologies disrupting the mining industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Mining. The mining companies featured in our thematic scorecard are listed below.
- Boliden
- Newcrest Mining
- Gold Fields
- Anglo American
- Newmont
- Freeport-McMoRan
- Barrick Gold
- Sumitomo Metal Mining
- Nornickel
- Sibanye-Stillwater
- Kinross Gold
- Polymetal International
- Zijin Mining
- POSCO
- South32
- Northern Star
- Saudi Arabian Mining
- Jiangxi Ganfeng Lithium
- AngloGold Ashanti
- Grupo Mexico
- Tianqi Lithium
- First Quantum Minerals
- Nippon Steel
- Vedanta
- Evraz
- Jiangxi Copper
- Tata Steel
- RUSAL
- Hindalco Industries
- Impala Platinum
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Thematic Scorecard ranks companies within a sector based on their overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of their future earnings and relative position within key strategic areas.
