BHP and Microsoft have partnered to use artificial intelligence (AI) and machine learning to improve copper recovery at the world's largest copper mine, Escondida, in Chile.
The project is expected to increase copper recovery by up to 5 per cent, which could generate an additional $1 billion in revenue for BHP each year.
Real-time data from copper concentrator plants and Azure Machine Learning is used by BHP to make hourly predictions, providing recommendations for the Escondida operations team to optimise copper concentrator performance, the mining company explained.
Other Azure services such as Synapse Analytics and Data Lake Storage are also used at Escondida.
The project is also expected to reduce operating costs by up to 10 per cent as the AI can identify and optimise processes that are not efficient.
Safety at the mine is also expected to be improved with the AI identifying and preventing potential hazards.
Using AI/ML and data analytics helps BHP to keep up production of copper from existing mines as grade declines and fewer new deposit discoveries made.
Augmenting new digital technology capabilities with new ways of working, will help Escondida generate more value from an existing resource, BHP chief technical officer Laura Tyler said.
“We expect the next big wave in mining to come from the advanced use of digital technologies," Tyler said.
There are a number of similar projects using AI and machine learning in the mining industry around the world.
For example, Rio Tinto is using AI to improve the efficiency of its iron ore mines in Australia.
Anglo American uses AI to improve the safety of its mines in South Africa.
BHP inked a deal in 2021 with AI/ML exploration firm KoBold to look for metals such as copper and nickel, in Australia and around the world.
Escondida has been operational for over 30 years in the Atacama desert in Antofagasta, northern Chile.
It produces over a million tonnes of copper a year.
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