Grinding Circuit Optimisation 2018-08-16T14:27:30+00:00

Grinding Circuit Optimisation

The Grinding Circuit Optimisation Application is the first technology to accurately predict critical SAG Mill performance variables. It then correlates this data to give an accurate picture of conditions inside the mill. This allows mines to reduce downtime in operations by reducing scheduled liner wear inspections and unnecessary changes. It also increases p80 consistency by keeping ball charge levels within the correct design ranges.


To accurately measure conditions inside a SAG Mill where there are no physical sensors, Virtual Sensors are generated using an asset specific library of mathematical models to determine missing engineering parameters in real time. The data is assimilated using an Ensemble Kalman Filter and automatically calibrated using mill inspection reports to ensure that they provide a consistent and correct picture of conditions inside the SAG Mill.


The Grinding Circuit Optimisation Application uses the Material Transport Model to track geometallurgical and physical properties of the material entering the SAG Mill. Virtual sensors are used to understand the current conditions within the SAG Mill and determine when liner wear inspections or changes are needed. This data is supplied to the operator in real time to allow them to make the best decision when operating SAG Mills.


The optimisation engine uses complex Machine Learning techniques to balance operational and financial optimisation by proactively providing control variables required for continuous optimisation. By predicting the geometallurgical and physical properties of the material entering the process, the product liberation (P80) will be optimised using the minimum energy required at the highest throughput possible. This maximises the recoverable metal downstream and delivers process value optimisation.


  • Drastically increase recoverable metal.
  • Reduced specific energy consumption when keeping ball charge levels at a constant.
  • Increased P80 stability by accurately predicting the conditions inside the SAG Mill.
  • Reduce number of liner wear inspections, keeping SAG Mills running for longer.

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