The JKMRC Mill Filling Prediction Tool

Speaker: Dr Francisco Reyes, Research Fellow, JKMRC

Abstract: SAG mills are a key asset for mineral processing operations as one of the critical stages of extracting mineral out of ore, and their continued stable operation is central to productivity. However, the performance of a SAG mill changes rapidly in response to conditions such as feed size and hardness as well as longer-term variability due to liner wear – something no instrumentation can directly observe.

Researchers from the Sustainable Minerals Institute’s Julius Kruttschnitt Mineral Research Centre (JKMRC) are developing a soft sensor to overcome performance challenges facing Semi-Autogenous Grinding (SAG) mills. The new Mill Filling Prediction Tool (MFPT) is a soft sensor (a mathematical model that act as a sensor) that provides information about the mill’s contents and enables it to be controlled closer to its maximum capacity. The MFPT is developed by Dr Marko Hilden, a Senior Researcher at JKMRC. He transformed and updated models that have been developed by various researchers at JKMRC over the years and developed new models to suit this new application.

Bio: Francisco's research interests relate to developing and integrating dynamic models of mineral processing systems for advance process control and prediction purposes. His work also focuses on using advanced imaging and computational tools for quantifying the performance of comminution equipment and other mineral processing systems like leaching and flotation.

Francisco worked in research and development for a number of years before undertaking his PhD at Imperial College London. He joined JKMRC's Advanced Process Prediction and Control Group (APPCo) in 2019.