2017-Sustainable Industrial Processing Summit
SIPS 2017 Volume 4. Lotter Intl. Symp. / Mineral Processing
| Editors: | Kongoli F, Bradshaw D, Waters K, Starkey J, Silva AC |
| Publisher: | Flogen Star OUTREACH |
| Publication Year: | 2017 |
| Pages: | 226 pages |
| ISBN: | 978-1-987820-67-6 |
| ISSN: | 2291-1227 (Metals and Materials Processing in a Clean Environment Series) |
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The Application of Recent Advances in Automated Mineralogy to Address Problems in Mineral Processing Flowsheet Optimization
Benjamin Tordoff1; Shaun Graham2;1ZEISS, Cambridge, United Kingdom (Great Britain); 2CARL ZEISS, Cambridge, United Kingdom (Great Britain);
Type of Paper: Invited
Id Paper: 99
Topic: 5
Abstract:
Chemical assays have long been the benchmark technique to value prospects and mines from early stage exploration all the way through to metallurgical accounting. However, while the mines are looking at extracting metals, it is the minerals that dictate where the metals are located. This can also be extended to deleterious elements and problematic minerals for the processing circuit. Minerals, not elements, control processing behavior, therefore early and appropriate characterization in the mining lifecycle will add significant value to an operation.
The potential for process mineralogy to play a major role in process improvement is well recognized but has historically been limited in its practical application due to issues including expense, long turn-around time and data complexity. Recent technological advances have started to change this, making such information accessible and usable by minerals engineers in the field or on site. Automated Mineralogy (AM) is one of the primary tools used in such work, and ZEISS MinSCAN is the first truly ruggedized system that can be deployed on site. Based on technology used by the military in field operations, the instrument is designed to operate in environments not typically associated with such tools and can provide data such as bulk mineralogy, element assay and deportment, liberation, and association rapidly and easily.
Mine sites can now produce data, almost real time, to monitor the plant performance. There is also a growing demand to implement this solution at an earlier prefeasibility stage, to feed into geometallurigcal modeling to reduce risk in earlier prediction and decision. This data offers a common language and dataset that can be used by all stakeholders in the mine development from exploration geologists through to metallurgists.
This paper outlines the technological innovations of the AM solutions, the ruggedized developments and how they can be successfully employed to mine site operations.