Editors: | Kongoli F, Kumar P, Senchenko A, Klein B, Silva A.C., Sun C, Mingan W |
Publisher: | Flogen Star OUTREACH |
Publication Year: | 2016 |
Pages: | 270 pages |
ISBN: | 978-1-987820-44-7 |
ISSN: | 2291-1227 (Metals and Materials Processing in a Clean Environment Series) |
Although the benefits of sensor-based sorting are well documented, the technology has not been widely applied. There are two main technical barriers that prevent the broader application, including limitations of sensors to accurately classify rocks and limited throughput capacities of the rock sorting platforms. Artificial intelligent approaches applied to sensor outputs has lead to improved discrimination. The integration of these sensors into the material-handling equipment has enabled sorting of bulk materials. The greatest beneficiaries of these breakthroughs are low-grade large tonnage deposits where sensor based grade control leads to greater resource utilization and more consistent and higher quality ore reporting to the mill leading to lower comminution costs and higher metallurgical recoveries. This paper presents the results of pilot scale bulk sorting studies and the operational improvements that are achieved.