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How Freeport achieved 10% higher copper extraction through AI and seven different ore recipes

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(Kitco News) - The Freeport-McMoRan ore processing team at Bagdad operations used data science and AI to increase ore output.

McKinsey released a study last week about AI applied to mining and some case examples using its work at Freeport-McMoran's operations. The study is good round up of concrete examples showing how AI and data science can be applied to different aspects of a mine's operations.

;One anecdote from the report on ore processing follows.

Beginning in late June, Freeport-McMoRan's Bagdad team and data scientists from McKinsey built a machine-learning model to check whether the mill truly ran as efficiently as people believed. The model, a type of extreme gradient-boosting model, consisted of an ensemble of thousands of decision trees that had been engineered to include a great deal of metallurgical knowledge.

The staff at Bagdad and Freeport-McMoRan's central operations group believed all the ore entering the mill was of the same type. Consequently, they had defined a single "recipe" of lower and upper parameters for the mill's 42 control settings: the mix of differently sized ore chunks being fed into the mill, the pH level in the flotation cells, and so on.

But when the agile team at Bagdad ran the data from the mill's performance sensors through its model, the members of the team learned something new. From the mill's perspective, the mine was actually producing seven distinct types of ore.

What's more, the mill's standard recipe for control settings didn't match the properties of all those ore types. Ore containing more iron pyrite, for example, would yield more copper if the pH level in the flotation cells were set higher than the recipe prescribed.

"Thinking about ore clusters in terms of data from the mill's instruments, rather than classifications from traditional geology, was a major mindset shift—and it opened up many new possibilities for improving performance," said Sean Buckley, a McKinsey partner who led the analytics work.

All told, the team's analysis suggested that adjusting the mill's controls to suit each of the seven ore types could increase copper production by 10 percent or more.

That prospect convinced Freeport-McMoRan's leaders to let the agile team at Bagdad build an AI model that would look at the ore coming into the mill and suggest control settings to heighten production of copper from that ore.

Disclaimer: The views expressed in this article are those of the author and may not reflect those of Kitco Metals Inc. The author has made every effort to ensure accuracy of information provided; however, neither Kitco Metals Inc. nor the author can guarantee such accuracy. This article is strictly for informational purposes only. It is not a solicitation to make any exchange in commodities, securities or other financial instruments. Kitco Metals Inc. and the author of this article do not accept culpability for losses and/ or damages arising from the use of this publication.

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