Modern Mining April 2024

single-particle precision to high-throughput par ticle sorting and unlocks value through a wealth of extremely detailed and accurate data for better informed decision-making. Bartram explains that AI encompasses two sub fields that have progressed considerably in recent years: Machine Learning, which recognises pat terns, learns from data and improves without being programmed, and Deep Learning, which is a type of Machine Learning that uses artificial neural networks to analyse data and solve complex problems. These technologies process vast amounts of data very quickly and use it to make decisions without human intervention. Machine Learning and Deep Learning can further improve the sorting process for mining operations already using sensor-based sorting, but can also open new opportunities by enabling the processing of very low-grade materials that previously would have been discarded. A further advantage of AI is the vast amount of data it generates and processes, which provides mining operations with valuable insights into the sorter’s performance, input material characteristics, indicative grades and particle size distribution, and for predictive maintenance. “TOMRA is now breaking new ground with its latest innovation to introduce an industry-first: single particle precision in high-throughput ore sorting. The software uses a Neuronal Network to identify the properties of each particle accurately and indepen dently of the sorter’s capacity, achieving precision and reliability in detection and ejection. Based on specific requirements, the mining operation has the flexibility either to enhance the throughput of the sorter while maintaining consistent sorting efficiency or improve sorting precision without compromising the existing throughput. It is a true game changer.” OBTAIN TM proves advantageous for a fully operational mine by enhancing recovery rates and elevating product quality within the existing through put. Conversely, in mines with additional capacity it facilitates increased throughput without compromis ing product quality. Furthermore, the technology has the capability to unlock untapped value from low-grade ore, waste dumps, or materials previously deemed uneconomical for processing. The OBTAIN™ software has been developed for TOMRA’s XRT sorters. TOMRA has partnered with two customers to test the new OBTAIN TM in real working conditions. The software has been operating for close to 18 months at the Wolfram Bergbau & Hütten tungsten mine in Mittersill, Austria, where it has delivered consistent and reliable performance. The proximity of the mine to TOMRA’s development team made it a perfect testing ground for the first phase, as they were able to monitor it closely. A second phase of testing to quantify the improvements has been carried out with a long-standing customer in a magnesite application.

The successful tests have shown that OBTAIN™ is ready to transform sensor-based XRT sorting in numerous applications. Both Machine Learning and Deep Learning have great potential to further enhance the benefits of TOMRA Mining’s sorting technologies for mining operations. The company is constantly exploring the potential of these technologies and pushing the boundaries to offer technical solutions for sort ing applications that were previously impossible for sensor-based sorters. At the same time, it can use Machine Learning and Deep Learning to improve existing sorting technology, applying them to more areas of its activity, such as better customer support, deeper analysis of the sorted material for improved control of customers’ processing plants, and pre dictive maintenance and monitoring of the sorter’s components. 

TOMRA Mining team at their stand at Mining Indaba 2024.

COM XRT 2-1200 with OBTAIN.

April 2024  MODERN MINING  19