MALCOLM POWELL1, CEREN BOZBAY2, SARMA KANCHIBOTLA1, BENJAMIN BONFILS1,3, ANAND MUSUNURI4, VLADIMIR JOKOVIC1, MARKO HILDEN1, JACE YOUNG2, & EMRAH YALCIN2
1JKMRC, Sustainable Minerals Institute, University of Queensland, 2Barrick Cortez Mine, Elko, Nevada, USA 3Hatch Engineering, JKTech
In expanding the mine to process considerably more competent ore sources, this semi-autogenous-ball mill-crusher (SABC) circuit with a single ball mill is not just throughput constrained but will shift to being permanently ball mill limited. The application of a fully integrated processing objective that relies on close cooperation between mine, dispatch, and mill is required to address this challenge. Moving beyond the general perception of mine–to-mill, a deeper processing knowledge is applied along the mining chain, considering blasting as the first stage of comminution and recovery. Grade deportment and dilution are considered at the mining stage and modelled with the new Sustainable Minerals Institute (SMI) blast movement simulator, linking with the block model data. Based on field trials, blast design and blending strategies are developed to couple with new operating strategies at the mill.
It has been found that accounting for blast movement for the higher intensity blasts could generate additional value of over $1 million per high-intensity blast. Strategies to shift the workload and debottleneck the milling circuit were proposed and proven during the milling trials, demonstrating an increase in throughput of 16% is achievable. A number of process improvement opportunities, including changing the semi-autogenous (SAG) mill control strategy, have been identified to enhance current productivity and ensure long-term capability to process the considerably more competent future ores. In a departure from traditional once-off applications of mine-to-mill changes, on-site technology transfer is being embedded in online tools to sustain advanced mine-to-mill capability in the daily planning and operation.
Mine-to-mill, grind curves, model-informed process control