We have a new peer reviewed paper in Minerals Engineering showing how Deep Neural Networks predict standard comminution parameters directly from Geopyörä  breakage test data. The result is higher accuracy with smaller samples and faster turnaround.   What this means for you:   - Less sample mass, more samples across the orebody, better variability capture - Direct prediction of Axb/DWI and BWI from force, energy, t10, SG and related features - A clear path to scale geomet pro

Our paper, titled "The Geopyörä Index: A New Instrument for Assessing Comminution and Rock Strength Parameters,"  presented by Thiago de...

If you're attending the IMPC 2024 congress, we invite you to join us for an exciting presentation by our engineer  Thiago de Almeida  on...

A new paper, presented at the 20th Procemin Conference and based on a related thesis, is now available for easy download. The research...