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Obtaining maximum value from mineralogical fingerprint datasets

Aug. 2 2019

Bureau Veritas’ latest innovation combines cutting edge techniques with Artificial Intelligence and Data Analytics to obtain maximum value from mineralogical fingerprint datasets.

Bureau Veritas launched an unprecedented large-scale initiative three years ago in the mining sector, called the “Minerals Machine Learning” project. It is using Artificial Intelligence to accurately estimate the mineralogical composition and chemical and physical properties of ore and mineral samples.

“With a simple infrared spectrometry test, AI can produce analyses for a much lower cost than previously," says Dr. John Carter, Global Technical Manager at Bureau Veritas in charge of the project.  

In the mining sector in particular, costs can quickly prove prohibitive, whether in relation to exploration or exploitation. Since the cost/benefit ratio is sometimes unfavorable, some of these tests are excluded from the process by some industrial companies.

In these cases, AI ​​opens up new perspectives, both in terms of productivity gains and coverage of new risks. For example, it makes it possible to estimate the hardness of a fragment of ore simply by analyzing a powder from it.

The method developed in the Bureau Veritas laboratory in Canning Vale, which is based on AI, will make it possible to create “digital twins” of mines based on historical test data.

This significant first step reveals the extraordinary potential of the "Minerals Machine Learning" project.

Contact our Exploration & Mining team or watch the video below from more information about this project.

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