Top 10: Uses of Artificial Intelligence in Mining

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Mining Digital considers some of the top use cases for AI in the mining industry, along with stand out companies.
Mining Digital considers some of the top uses for artificial intelligence (AI) in mining and how smart mining is leading changes in the industry

AI is disrupting the mining industry by transforming the way that daily operations are handled. These intelligent systems are capable of analysing large quantities of data and providing digital solutions for companies, with the technology helping to increase speed and safety in mining operations.

Mining Digital considers some of the top use cases for AI in the mining industry and some of the highest profile companies that have adopted these technologies.

10: Predicting supply chain disruptions

In 2021, McKinsey stated that supply-chain management solutions based on AI transformation are expected to be “potent instruments” to help organisations tackle industry challenges. AI models can be used to predict future supply chain information such as forecasting demand for specific products and optimising inventory levels. 

It can also identify disruptions in the supply chain and aim to streamline processes. IBM in particular has its Watson Supply Chain that uses AI to enable proactive disruption management through smart alerts and real-time insights for mining companies' operations.

9: Energy optimisation

The use of AI and similarly advanced technologies to optimise energy use can benefit the mining industry by analysing data to identify energy-saving opportunities and improving efficiency as a result.

Rio Tinto has undergone mass developments in order to ensure smooth operation and safety of its mines. In particular, it has been working towards greater innovation for its smart mines by setting up Centres of Excellence that are focused on analytics, automation, asset management and energy and climate change.

8: Environmental data

AI in mining can work to reduce environmental impact and risk on location by analysing data quickly and efficiently. In particular, AI can work to identify areas where operations can be optimised, as well as considering the impact on the surroundings.

Mining leader BHP and tech giant Microsoft are utilising AI and machine learning (ML) to boost copper production. The companies are doing this by using real-time data from the copper concentrators and Azure Machine Learning to make hourly predictions. These are then consequently used to make recommendations to the operations team.

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7: Exploration

AI can help with mining exploration by analysing huge amounts of data, identifying on-site targets and providing insights on both. It provides greater efficiency on site with regards to both time and cost.

Barrick Gold Corporation, one of the world's largest gold mining companies, is an example of a company that has been implementing AI technologies for mine exploration for several years. The company uses AI algorithms to process geological and geophysical data and helps to identify potential mining locations and optimise drilling operations.

6: Predictive maintenance

AI predictive maintenance models have the capacity to evaluate variables that reflect an asset’s current status, make predictions based on usage trends and consequently inform maintenance teams of potential equipment failures in advance. This not only ensures greater on-site safety for human workforces, but also allows companies to better plan in advance.

ABB Global uses predictive maintenance for mining with its ABB Ability Predictive Maintenance service. It provides mine operators user-friendly real-time dashboards and reports with the condition of each asset. This allows for fast repairs and removes unnecessary maintenance that might be a safety risk.

5: Safety and risk assessments

As previously mentioned, AI has the ability to evaluate and alert to possible risks at a mine site. This could be transformative for mining operations, as it creates an equally more efficient and safer environment for human workforces.

Optimisation of systems also helps manage and understand risk assessments. Tomorrow.io in particular has weather forecasting technology that uses AI to predict weather and provide mining companies with a competitive edge. Therefore, companies can make more informed decisions in various aspects of their operations.

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4: Robotics

Automation is continually increasing with the introduction of more electric mining tools that can sometimes reach where miners cannot. AI powered robotic platform maker Offworld announced in January 2023 that it is taking orders to deploy its AI industrial swarm robotic mining systems commencing in 2024. 

The line of autonomous robots is built for surveying environments, both on the surface and underground, performing excavations, collecting, hauling and processing materials. Its battery units extend the operational run time of each robot by performing autonomous in-situ battery swapping and charging.

3: Ore sorting

AI-based sorting systems can identify valuable minerals from waste rock in real-time and ultimately improve recovery rates and reduce processing costs as a result.

Leading global mining company Vale launched its first AI centre in 2020 in Espírito Santo. With a commitment to sustainability and safety, the company uses the technology to analyse ore samples and make decisions on the best sorting methods to maximise mineral recovery, which has led to the improvement of environmental, health and safety on site.

2: Decision support systems

There are lots of benefits to AI being used to support decision making, including better worker safety, improvement of previously lengthy processes and cost reduction. In particular, mining company Anglo American has been consistently exploring AI applications in its mining operations in its efforts to be more sustainable and produce less waste.

The company has developed AI solutions for mineral exploration and resources estimation and helps workers identify potential mining sites more efficiently. AI tools allow the company to make the best decision possible whilst ensuring all of the above key factors.

1: Autonomous vehicles

Autonomous vehicles can make working conditions safer in mining as they do not have to attempt to reach potentially dangerous areas of a site. Komatsu in particular ranks high in the mining industry in regard to automated vehicles as its approach to smart mining aims to maximise operations but with the utmost safety. 

The company uses electric drive mining trucks for both construction and mining operations, boasting a broad range of 30 to 400 tonne capacity trucks to help its customers meet their productivity targets, ultimately pushing innovation in suspension, transmission, and autonomous operation.

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