Estimation of Lifters Wear in Ball and SAG Mills using Neuro-Fuzzy Modeling

Most of the energy used in mining is consumed in the grinding process. The optimization of mineral comminution leads to an increase in the productivity and energy efficiency of the process. This study presents a new method for the online determination of the state of the mill lifters, using electrical and process variables in the construction of a neuro-fuzzy model of lifter wear. This estimator allows avoiding mill downtimes caused by the inspection of lifters, with the consequent increase in availability and productivity. It is also an aid in planning the maintenance of this mining equipment.