Abstract
In recent years there has been a growing recognition of the impact that mining practices have on the efficiency of mineral processing operations. Head grade, dilution, particle size distribution and their variability are known to have a significant effect on the throughput and recovery achieved in mineral processing plants. Improved process monitoring and modeling have provided the opportunity to identify and quantify some of these impacts and to define very significant incentives to optimize the overall operation from the mining face through subsequent comminution and processing.
MineSense is a Canadian company headquartered in Vancouver, British Columbia, pioneering digital mining solutions by supplying real-time, XRF sensor-based ore characterization from mine to mill with two main solutions. ShovelSense, is the only ore sorting technology at the mining face, that corresponds to a robust sensor installed on loading equipment's that can scan and estimate the grades of the material in every bucket loaded into a truck. On the other hand, BeltSense is installed on the belt and used sequentially with ShovelSense to maximize ore and waste control downstream through precise measurement on downstream conveyors.
MineSense´s solutions have proven effective at the Copper Mountain mine in Canada, by installing ShovelSense in the whole loading fleet and two BeltSense systems in the conveyor belt before the SAG mill. Copper Mountain is a ~200 kiloton per day operation located near the town of Princeton, in southern British Columbia. The mine is owned by the Copper Mountain Mining Corp (75%) and Mitsubishi Materials Corp (25%), and the mineralization of the mine is an alkalic porphyry deposit that “consists of structurally controlled, multidirectional veins and vein peripheral disseminations”.
Recently the integration of XRF sensor-based sorting in shovels and conveyor belts, have proven the benefits and potential opportunities of the first online mine to mill real time measurements. The core use of this type of information is the predictive control of downstream process, having an accurate and real time measurement of elements reduces the uncertainty of the feed grade and ore characteristics. Also, the data analysis has demonstrated that using XRF response has the potential to determine characteristics as type of rock, mineralogy and grinding ratio generating downstream improvements.