Abstract

The ball mill is usually the largest energy consumer at a mine site and significantly affects operational expenditures. Given a target particle size, Bond Mill Work Index estimates are used to predict a ball mill’s throughput. In order to maximize ball mill throughput and optimize energy utilization, it is important to get these estimates right. At the Tropicana Gold Mine, Work Index estimates, derived from X-Ray Fluorescence and Hyperspectral scanning of Grade Control samples, are used to construct spatial GeoMetallurgical models (GeoMet). Inaccuracies in block estimates exist due to limited calibration between grade control derived and laboratory Work Index values. To improve the calibration, an updating algorithm has been tested at the Tropicana Gold Mine. The aim of the study was to demonstrate a new process for updating block estimates using actual mill performance data. Deviations between predicted and actual mill performance are monitored and used to locally improve the Work Index estimates in the GeoMet model. The updating algorithm improves the spatial Work Index estimates, resulting in a real-time reconciliation of already extracted blocks and a recalibration of future scheduled blocks. The case study shows that historic and future production estimates improve on average by about 72 and 26%.

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