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) |
CD shopping page
Automated Mineralogy: The Past, Present and Future
Shaun Graham1;1CARL ZEISS, Cambridge, United Kingdom (Great Britain);
Type of Paper: Invited
Id Paper: 310
Topic: 5
Abstract:
Automated Mineralogy, and specifically the SEM-EDS-AM solutions available, have played vital roles in the development and application of modern process mineralogy. Since the initial development and introduction into the market, these technologies have contributed to optimizing mineral processing plants around the world. Despite their success and undisputed value, until recently the development of these solutions, in terms of the solutions methodology and analytical capabilities, has been limited. This talk aims to introduce and outline the history of these solutions with the view to providing an insight into the current state of play and new capabilities of the solutions within automated mineralogy. This will include modern trends and case studies that show these solutions are moving towards mine sites that utilize these newly ruggedized and deployable automated mineralogy solutions to adopt an operational mineralogy approach. This will act as the background, and as an introduction, to what future developments we can expect to see in automated mineralogy, and how these developments will be critical in providing reliable and routine on-site mineralogical analysis that will be required as mines of the future looks to adopt a Mining 4.0 capability. In addition, technological developments such as the use of machine learning and widening the analytical capability with 3D data and wider analytical instrumentation. These topics will be used to outline the future roadmap of AM and how these solutions will become strategically more valuable for 4.0 mining operations.
Keywords:
Characterization; Control; Efficiency; Industry; Mineral; Modeling; Ore; Performance; Processing; Production; Recovery; Tailings; Technology; Variability;References:
[1] Allan, R.W. & Lynch, A.J. (1983): Characterization of the behavior of composite particles in a lead-zinc flotation circuit. Part Science Technology, 2, 155-164.[2] Andersen J C Ø, Rollinson G K, Snook B, Herrington R, and Fairhurst R J (2009). Use of QEMSCAN® for the characterization of Ni-rich and Ni-poor goethite in laterite ores. Minerals Engineering 22, 1119–1129.
[3] Ashton, T., Chi, V. L., Spence, G. and Oliver, G. 2013. Drilling Completion and Beyond. Oilfield Technology, April 2013.
[4] Bernstein, S., Frei, D., McLimans, R.K., Knudsen, C. & Vasudev, V.N. (2008): Application of CCSEM to heavy mineral deposits: Source of high-Ti ilmenite sand deposits of South Kerala beaches, SW India. – Journal of Geochemical Exploration, 96, 25-42.
[5] Brough, C., Strongman, J., Fletcher, J., Graham, S. D., Barnes, A., Bowell, R., Warrender, R and Ward, L. 2017. 2D-3D liberation comparisons in HCT testwork for the Hannukainen IOCG deposit, Finland. Process Mineralogy, 2017.
[6] Brownscombe, W., Harman, E. M., Graham, S. D., Wilkinson, C. C. and Wilkinson, J. 2015. Autoamted mineralogical SEM as a precursor to trace element analysis by laser ablation ICP-MS. Society of Electron Microscope Technology, 2015 meeting.
[7] Butcher, A.R., Gravestock, D.I., Gottlieb, P., Cubitt, C. & Edwards, G.V. (2000): A New Way To Analyse Drill Cuttings: A Case Study From Deparanie – 1, Cooper Basin, South Australia. – APPEA J, 40, 774-775.
[8] Cabri, L.J., 1981. Relationship of mineralogy for the recovery of PGE from ores. In: Cabri, L.J. (Ed.), Platinum-Group Elements: Mineralogy, Geology, Recovery, Special vol. 23. Canadian Institute of Mining, Metallurgy and Petroleum, 233–250.
[9] Chetty, D., Bushell, W. C. C., Sebola, T. P., Hoffman, J., Nshimirimana, R., & De Beer, F. 2011. The use of 3D X-ray computed tomography for gold location in exploration drill cores. 10th International Congress for Applied Mineralogy, Trondheim.
[10] Dhawan, N., Sadgeh Safarzadeh, M., Miller, J. D., Moats, M. S., Rajamani, R. J. and Lin, C-L. 2012. Recent Advances in the Application of X-ray Computed Tomography in the Analysis of Heap Leaching System. Minerals Engineering, 35, 75-86.
[11] Godel, B. 2005. High-Resolution X-Ray Computed Tomography and Its Application to Ore Deposits: From Data Acquisition to Quantitaive Three-Dimensional Measurements with Case Studies from Ni-Cu-PGE Deposits. Economic Geology, 108, 2005-2019.
[12] Goodall, W.R., Scales, P.J. & Butcher, A.R. (2005): The use of QEMSCAN and diagnostic leaching in the characterisation of visible gold in complex ores. Minerals Engineering, 18, 877- 886.
[13] Graham, S. D. & Girard, R. 2016. Gold Grain and X-ray Microscopy – A new exploration tool for identifying proximal and distal gold deposits. International Geological Congress, Cape Town, 2016.
[14] Graham, S. D. and Brough. 2017. An evaluation of the application of x-ray microscopy in understanding gold losses in tailings. Conference of Metallurgists, Vancouver.
[15] Graham, SD, Brough, C and Cropp, A (2015)An Introduction to ZEISS Mineralogic Mining and the Correlation of Light Microscopy with Automated Mineralogy: A Case Study Using BMS and PGM Analysis of Sample from a PGE-bearing Chromitite Prospect, Precious Metals, Falmouth, 2015
[16] Gregory, M.J., Lang, J.R., Gilbert, S. & Hoal, K.O. (2013): Geometallurgy of the Pebble porphyry copper-gold-molybdenum deposit, Alaska: Implications for gold distribution and paragenesis. Economic Geology, 108, 463-482.
[17] Gu, L., Schouwstra, R. P. and Rule, C. 2014. The value of automated mineralogy. Minerals Engineering, 58, 100 – 103.
[18] Harman, E, M., Wilkinson, C. C., Brownscombe, W., Wilkinsion, J. J. and Graham, S. D. 2014. Toward the Developlment of Automated Mineral Identification with the ZEISS Mineralogic Platform for the Routine Analysis of Mineral Exploration Samples by Laser Ablation Inductively-Coupled Mass Spectrometry. 38th Annual Meeting of the Mineral Deposits Studies Group.
[19] Holwell, D. A., Adeyemi, Z., Ward. L. A., Graham, S. D., Smith, D. J., McDonald, I. & Smith, J. W. 2017. Low temperature alteration and upgrading of magmatic Ni-Cu-PGE sulfides as a source for hydrothermal Ni and PGE ores: a quantitative approach using automated mineralogy. In Press
[20] Holwell, D. A., Mitchell, C. L., Howe, G. A., Evans, D.M., Ward, L. A. & Freidman, R. (2017). The Munali Ni sulfide deposit, southern Zambia: A multi-stage mafic-ultramafic, magmatic sulfide-magnetite apatite-carboante megabreccia. Ore Geology Review, In Press
[21] J. D. MILLER , C. L. LIN & A. B. CORTES (1990) A Review of X-Ray Computed Tomography and Its Applications in Mineral Processing, Mineral Processing and Extractive Metallurgy Review, 7:1, 1-18
[22] Jones, M. P. & Cheung, T. S. 1988. Automatic method for finding gold grain in ores and mill products. Asian Mining, 73-81.
[23] Kalichini, MS Goodall, WR, Paul, EM, Prinsloo, A, Chongo, C (2017)Applied Mineralogy at Kansanshi mine -Proof of the Concept of On-Site Routine Process Mineralogy for Continous Improvement of Plant Operations, Process Mineralogy, 2017.
[24] Knudsen, C., Frei, D., Rasmussen, T., Rasmussen, E.S. & McLimans, R. (2005): New methods in provenance studies based on heavy minerals: An example from Miocene sands in Jylland, Denmark. – Geological Survey of Denmark: Greenland Bullentin, 7, 29-32.
[25] Kodali, P., Dhawna, N., Depci, T., Lin, C. L., & Miller, J. D. 2011. Particle Damage and Exposure Analysis in HPGR Crushing of Selected Copper Ores for Column Leaching. Minerals Engineering, 24, 1478-1487.
[26] Kyle, J. R. & Ketcham, R. A. 2015. Application of high resolution X-ray computed tomography to mineral deposit origin, evaluation and processing. Ore Geology Review, 65, 821-839.
[27] Lin, C.L., Garcia, C., 2005. Microscale characterization and analysis of particulate systems via cone beam X-ray microtomography (XMT). In: Young, C.A., Kellar, J.J., Free, M.L., Drelich, J., King, R.P. (Eds.), Innovations in Natural ResourceProcessing. Proceedings of the Jan D., Miller Symposium, SME, 421–432.
[28] Lotter, N.O., 2011. Modern process mineralogy – an integrated approach to flowsheeting, Minerals Engineering, 24, 1229-1237.
[29] Lotter, N.O., Kowal, D.L., Tuzun, M.A., Whittaker, P.J. & Kormos, L. (2003): Sampling and flotation testing of Sudbury Basin drill core for process mineralogy modelling. Minerals Engineering, 16, 857-864.
[30] MacDonald, M., Latti, D., Adair, B., Bradshaw, D., and Dunn, M., 2011. Learnings from five years of MLA at Kennecott Utah Copper Corporation. Proceedings, 10th ICAM, 419-426.
[31] Miller, J. D., & Lin, C. L. (2016). Opportunities for plant-site 3D coarse particle characterization with automated high speed X-ray tomography. In 2016 SME Annual Conference and Expo: The Future for Mining in a Data-Driven World (811-814). Society for Mining, Metallurgy and Exploration.
[32] Miller, J.D., Lin, C.-L., Hupka, L., and Al-Wakeel, M.I., 2009, Liberation-limited grade/recovery curves from X-ray micro CT analysis of feed material for the evaluation of separation efficiency: International Journal of Mineral Processing, 93, 48−53.
[33] Petruk, W., 1976. The application of quantitative mineralogical analysis of ores to ore dressing. CIM Bull. 767, 146–153.
[34] Petruk, W., 1988. The capabilities of the microprobe Kontron image analysis systems: application of mineral beneficiation. Scan. Microsc. 2, 1247–1255.
[35] Pfau, K. D. and Oliver, G. M. 2011. Technology Puts Mineralogy On Rig Site. The American Oil & Gas Reporter.
[36] Pirrie, D., Butcher, A.R., Power, M.R., Gottlieb, P. & Miller, G.L. (2004): Rapid quantitative mineral and phase analysis using automated scanning electron microscopy (QemSCAN); potential applications in forensic geoscience. Geological Society Special Publication, 232, 123-136.
[37] Pirrie, D., Rollinson, G.K., Power, M.R. & Webb, J. (2013): Automated forensic soil mineral analysis; testing the potential of lithotyping. Geological Society Special Publication, 384, 47-64.
[38] Rule, C. and Schouwstra, R.P., 2011. Process mineralogy delivering significant value at Anglo Platinum concentrator operations. Proceedings of 10th ICAM, Trondheim, 613-620.
[39] Ryan, E. & Hill, E. 2017. A review of new automated mineralogy functionality in ZEISS Mineralogic Mining. ZEISS White Paper
[40] Santoro, L., Boni, M., Rollinson, G.K., Mondillo, N., Balassone, P. & Clegg, A.M. (2014): Mineralogical characterization of the Hakkari nonsulfide Zn(Pb) deposit (Turkey): The benefits of QEMSCAN®. – Minerals Engineering, 69, 29-39.
[41] Strongman, J, Brough, C, Fletcher, J, Garside, R and Tordoff, B (2017)Optimising AutomatedMineralogy for Operational Mine Site Applications. Process Mineralogy, Cape Town, 2017.
[42] Sutherland, D.N. & Gottlieb, P. (1991): Application of automated quantitative mineralogy in mineral processing. – Minerals Engineering, 4, 753-762.