Combining EDEM and HyperStudy to Optimize the Design and Operation of a SAG Mill

Through the use of a coupled workflow involving Altair HyperStudy, HyperMesh and EDEM, a largely automated optimization methodology was utilized to create an example case optimization of a Semi-Autogenous (SAG) mill. Designs of Experiments (DOEs) were performed to generate useful data which allowed for the determination of which parameters (both geometric and operational) contribute most significantly to efficient size reduction of the ore-charge. Leveraging the generated synthetic data, predictive models could be built which allowed for subsequent application of optimizations across a range of desired output responses, for example, varying SAG mill liner design/operational parameters to maximize beneficial collisions and minimize mill liner wear-down.

Presented as part of the virtual ATCx DEM in November 2022.
Speaker: Bruno Mimouni, Intern, Altair
Duration: 10 minutes