Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter (O) March 25, 2020

Sensor-based ore sorting in 2020

Sensorgestützte Sortierung von Erzen in 2020
  • Hermann Wotruba

    Hermann Wotruba has a degree in mining engineering from RWTH Aachen University, Germany, where he also got his PhD in mineral processing, and where he, after nine years work in the industry, went back as a full professor and head of the Department of Mineral Processing in 1998, which is his current position. He has extensive experience in the area of mineral processing and environment with project experience in many regions like Europe, South America, Africa and Asia. His work includes mineral processing base studies to flow-sheet development, equipment and plant design, plant commissioning and optimization and environmental management with special emphasis on dry mineral processing and sensor-based ore sorting. He is one of the world leading experts in small scale and artisanal cleaner mining and processing technology.

    EMAIL logo
    and Christopher Robben

    Christopher Robben is an underground mining engineer graduated from RWTH Aachen University where he also completed his PhD. in Mineral Processing. His areas of expertise include international industrial equipment sales, distribution and service, research and development for innovative technology in all segments of mineral production. His focus lies on overall business strategy and improvement, sound engineering, mineral economics and financial modelling. He collected hands-on experience in pilot operations and production, interdisciplinary and intercultural project management and execution. He also has a scientific background on sensor applications, theory of sampling and resource-to-product integration. He is one of the world leading experts in sensor-based ore sorting.

Abstract

Sensor-based ore sorting is not a new technology. It has been around since more than 70 years, mainly for diamond concentration, where it was applied to eliminate the security risk of diamonds being stolen from the previously applied grease-tables [13]. Despite a few installations in uranium ore processing, it had no further widespread acceptance in the minerals industry, mainly due to low design capacity. Besides that, sensor-based colour sorters were used in the food industry for small particle sizes (e. g., rice cleaning). It is fact that the first machine designs appropriate for coarse bulk materials were not developed for the minerals industry, but for the upcoming recycling industry for plastics, glass, paper, metals in the late 1980s. In this sector, besides some magnetic separators, all the work was done by manual hand-picking, and it needed automation. After some years of optimization, these machines showed reliable performance under harsh conditions in scrap yards and recycling plants. Then, finally, the minerals industry, which at first was not convinced that this rather complicated machines were suited to be used with minerals, began with the first applications. These first installations of sensor-based ore sorters around the late 1990, all of them equipped with line-scan optical cameras, were mainly in industrial minerals, such as calcite, magnesite, quartz or rock salt. Since then, the technology has seen an enormous development in terms of available sensors, design capacity and availability, and the number of installations for minerals is growing – steadily but slower than expected, considering the many advantages it brings.

Zusammenfassung

Sensorgestütze Sortierung von Erzen ist keine neuartige Technologie. Nach ihrer Einführung vor mehr als 70 Jahren wurde sie hauptsächlich zur Sortierung von Diamanten eingesetzt, um das Risiko des Diebstahles von Diamanten an den bis dato eingesetzten Fettherden zu eliminieren. Trotz einiger weniger Installationen in der Uranerzaufbereitung gab es keine breite Akzeptanz in der Bergbauindustrie, nicht zuletzt aufgrund der relativ geringen Produktionskapazität. In der Lebensmittelindustrie wurden Farbsortierer für kleine Partikelgrößen zunehmend verwendet (z. B. zur Reisreinigung). Erste kommerziell Maschinenkonstruktionen für grobe Schüttgüter wurden nicht für die Mineralindustrie entwickelt, sondern für die aufkommende Recyclingindustrie für Kunststoffe, Glas, Papier, Metalle in den späten 1980er Jahren. Neben einigen Magnetabscheidern, wurde die ganze Arbeit wurde von Hand erledigt und es brauchte Automatisierung zur Steigerung der Produktivität. Nach einigen Jahren der Optimierung zeigten diese Maschinen zuverlässige Leistung unter rauen Bedingungen auf Schrottplätzen und in Recyclinganlagen. Allmählich ließ sich die Bergbauindustrie überzeugen, dass diese eher komplizierten Maschinen für den Einsatz mit Mineralien geeignet sind, und es ergaben sich erste Anwendungen. Diese ersten Installationen von sensorgestützten Sortierern in den späten 1980er Jahren waren alle mit Farbzeilenkameras ausgestattet und wurden hauptsächlich für die Sortierung von Industriemineralien wie Calcit, Magnesit, Quarz oder Steinsalz eingesetzt. Seitdem hat die Technologie eine enorme Entwicklung in Bezug auf verfügbare Sensoren, Design, Kapazität und Anlagenverfügbarkeit erfahren. Die Anzahl der Installationen für Mineralien wächst - stetig, aber langsamer als erwartet in Anbetracht der vielen Vorteile, die die Technologie mit sich bringt.

Keywords: sensor; sorting; mining
Schlagwörter: Sensor; Sortierung; Bergbau

About the authors

Hermann Wotruba

Hermann Wotruba has a degree in mining engineering from RWTH Aachen University, Germany, where he also got his PhD in mineral processing, and where he, after nine years work in the industry, went back as a full professor and head of the Department of Mineral Processing in 1998, which is his current position. He has extensive experience in the area of mineral processing and environment with project experience in many regions like Europe, South America, Africa and Asia. His work includes mineral processing base studies to flow-sheet development, equipment and plant design, plant commissioning and optimization and environmental management with special emphasis on dry mineral processing and sensor-based ore sorting. He is one of the world leading experts in small scale and artisanal cleaner mining and processing technology.

Christopher Robben

Christopher Robben is an underground mining engineer graduated from RWTH Aachen University where he also completed his PhD. in Mineral Processing. His areas of expertise include international industrial equipment sales, distribution and service, research and development for innovative technology in all segments of mineral production. His focus lies on overall business strategy and improvement, sound engineering, mineral economics and financial modelling. He collected hands-on experience in pilot operations and production, interdisciplinary and intercultural project management and execution. He also has a scientific background on sensor applications, theory of sampling and resource-to-product integration. He is one of the world leading experts in sensor-based ore sorting.

References

1. Bamber, A. S. (2016). Development and testing of real-time shovel-based mineral sensing systems for enhanced recovery of mined material. In Procedings of the 7th Sensor-Based Sorting and Control. Aachen, Germany.Search in Google Scholar

2. Dammers, M. (2017). Development and Evaluation of Novel Integrated Underground Mining and Sorting Systems. Aachen, Germany: Shaker Verlag GmbH.Search in Google Scholar

3. Holl, I., Feldman, V., Zampini, J. and Cunningham, R. (2019). The comissioning and start-up of Quebec’s first Diamond mine - Stornoway’s Renard Mine. In Procedings of the 51st Annual Canadian Mineral Processors Operators Conference. Ottawa, Canada: Canadian Institute of Mining, Metallurgy and Petroleum.Search in Google Scholar

4. Lucara. (2015, November 18). Lucara Makes Diamond History; Recovers 1,111 Carat Diamond. Retrieved from https://www.lucaradiamond.com/newsroom/news-releases/lucara-makes-diamond-history-recovers-1-111-carat-diamond-122558/.Search in Google Scholar

5. Lucara Diamond. (2019, April 25). Lucara Diamond Corp. Retrieved from Newsroom: https://www.lucaradiamond.com/newsroom/news-releases/lucara-recovers-record-1-758-carat-diamond-from-karowe-122771/.Search in Google Scholar

6. Madderson, G. (2018). Improved diamond recovery through implementation of TOMRA XRT bulk Sorting - Karow Mine Botswana. In Procedings of th 7th Conference on the Geology of Diamond Deposits. Salvador, Brazil.Search in Google Scholar

7. Robben, C. (2013). Characteristics of Sensor-Based Sorting Technology and Implementation in Mining. Aachen, Germany: Shaker Verlag.Search in Google Scholar

8. Robben, C. and Mosser, A. (2014). X-ray-transmission-based sorting at the Mittersill tungsten mine. In Proceedings of the 27th International Mineral Processing Conference IMPC. Santiago de Chile: GECAMIN.Search in Google Scholar

9. Robben, C. and Takala, A. (2018). High volume sensor-based ore sorting solutions. In Procedings of the Sensor-Based Sorting and Control Conference. Aachen, Germany: Shaker Verlag GmbH.Search in Google Scholar

10. Robben, C., Condori, P. and Takala, A. (2018). Sensor-based ore sorting at San Rafael Mine. In International Mineral Processing Conference. Moscow: IMPC Council, The Russian Academy of Sciences.Search in Google Scholar

11. Robben, M. R. (2008). NIR Sensor Sorting, Basic study for application of NIR spectroscopy for sorting minerals. Bachelor Thesis. RWTH Aachen.Search in Google Scholar

12. Robben, M., Korsten, C., Pressler, N. and Audy, P.-L. (2012). Theory and operational experience of NIR sorting in the Talc industry. In Proceedings of the Sensor-Based Sorting Conference 2012. Aachen, Germany: GDMB Gesellschaft für Bergbau, Metallurgie, Rohstoff- und Umwelttechnik e. V.Search in Google Scholar

13. Taggart, A. F. (1945). Handbook of Mineral Dressing: Ores and Industrial. Wiley Handbook Series. New, York, NY, USA: Wiley.Search in Google Scholar

14. Wotruba, H., Knapp, H., Neubert, K. and Schropp, C. (2014). Application of sensor-based sorting for the processing of mineral resources. Chemie - Ingenieur - Technik 86, 773–783.10.1002/cite.201300174Search in Google Scholar

Received: 2019-06-03
Accepted: 2020-02-03
Published Online: 2020-03-25
Published in Print: 2020-04-28

© 2020 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 21.5.2024 from https://www.degruyter.com/document/doi/10.1515/auto-2019-0060/html
Scroll to top button