Benefits of optimisation and model predictive control on a fully autogenous mill with variable speed

• Industrial DMC significantly reduced power and load variance of an AG mill.
• This enabled tests to find the finest product size for a given mill feed rate.
• Operating at this point increases potential recovery by 0.27% (absolute).
• Reducing variance resulted in a further 0.04% potential recovery increase (absolute).

Autogenous (AG) milling is utilised around the world for particle size reduction. The system exhibits highly non-linear behaviour in addition to being subject to unmeasured variability associated with most ore bodies. Anglo American Platinum aimed at improving online optimisation of the circuit by implementing industrial model predictive control (MPC) to reduce system variability and continuously drive towards the optimal operating point within system constraints.The industrial dynamic matrix controller commissioned on the AG mill with a variable speed drive resulted in a 66% reduction in power and a 40% reduction in load standard deviation. These are the main controlled variables of the mill. The controller also improved the objective function, effective power utilisation, by 11%. This reduction in operated variable variability enabled a test campaign where the mill was controlled at various operating regions in order to establish the conditions conducive to the finest product size at a given mill feed rate.Moving the mill operating region from the benchmarked plant to the optimal grind environment and stabilising the mill at this point with the model predictive controller provided an estimated potential recovery increase of 0.32% (absolute) due to better liberation.