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Automation and Robotics in Mining and Mineral Processing

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Springer Handbook of Automation

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Abstract

Digital transformation, Industry 4.0, and emerging networking technologies provide mining industries productivity, sustainability, and safety. Mining automation systems today typically control fixed plant equipment such as pumps, fans, and phone systems. Much work is underway around the world in attempting to create the moveable equivalent of the manufacturing assembly line for mining. Process automation systems in mineral processing plants provide important plant operational information such as metallurgical accounting, mass balances, production management, process control, and optimization. Cloud-based IIoT platforms collect and share data in the mines and concentrators to allow widespread monitoring, analyzation, optimization, and control. This chapter discusses robotics and automation for mining and process control in mineral processing. Teleoperation of mining equipment and control strategies for grinding and flotation serve as examples of current development in the field.

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References

  1. Hustrulid, W.A., Bullock, R.L.: Underground Mining Methods – Engineering Fundamentals and International Case Studies. Society of Mining Engineers, Littleton (2001)

    Google Scholar 

  2. Hodouin, D., Jämsä-Jounela, S.-L., Carvalho, M.T., Bergh, L.: State of the art and challenges in mineral processing control. Control. Eng. Pract. 9, 995–1005 (2001)

    Google Scholar 

  3. Baiden, G.R., Scoble, M.J., Flewelling, S.: Robotic systems development for mining automation. CIM Bull. 86(972), 75–77 (1993)

    Google Scholar 

  4. Baiden, G.R.: A Study of Underground Automation. Dissertation, McGill University, Montreal (1993)

    Google Scholar 

  5. Jämsä-Jounela, S.-L.: Current status and future trends in the automation of mineral and metal processing. Control. Eng. Pract. 9, 1021–1035 (2001)

    Google Scholar 

  6. Bergh, L., Jämsä-Jounela, S.-L., Hodouin, D.: State of the art in copper hydrometallurgic process control. Control. Eng. Pract. 9, 1007–1012 (2001)

    Google Scholar 

  7. Bouffard, S.C.: Benefits of process control systems in mineral processing grinding circuits. Miner. Eng. 79, 139–142 (2005)

    Google Scholar 

  8. Mishra, B.K., Rajamani, R.K.: The discrete element method for the imulation of ball mills. Appl. Math. Model. 16, 598–604 (1992)

    MATH  Google Scholar 

  9. Weerasekara, N.S., Powell, M.S., Cleary, P.W., Tavares, L.M., Evertsson, M., Morrison, R.D., Quist, J., Carvalho, R.M.: The contribution of DEM to the science of comminution. Powder Technol. 248, 3–24 (2013)

    Google Scholar 

  10. Jayasundara, C.T., Yang, R.Y., Yu, A.B., Curry, D.: Prediction of disc wear a model IsaMIll and its effect on the flow of grinding media. Miner. Eng. 24(14), 1586–1594 (2011)

    Google Scholar 

  11. Weerasekara, N.S., Liu, L.X., Powell, M.S.: Estimating energy in grinding using DEM modelling. Miner. Eng. 85, 23–33 (2016)

    Google Scholar 

  12. Bracey, R.J., Weerasekara, N.S., Powell, M.S.: Performance evaluation of the novel multishift mill using DEM modelling. Miner. Eng. 98, 251–260 (2016)

    Google Scholar 

  13. Morrison, R.D., Cleary, P.W.: Towards a virtual comminution machine. Miner. Eng. 21(11), 770–781 (2008)

    Google Scholar 

  14. Lipsett, M.G.: Information technology in mining: an overview of the Mining IT User Group. CIM Bull. 1067, 49–51 (2003)

    Google Scholar 

  15. Baiden, G.R., Scoble, M.J.: Mine-Wide Information System Development, Canadian Institute of Mining and Metallurgy – 93rd Annu. Gen. Meet. Bull, Montreal (1991)

    Google Scholar 

  16. Hulkkonen, A.: Wireless Underground Communications System, Telemin 1 and 5th Int. Symp. Mine Mech. Autom, Sudbury (1999)

    Google Scholar 

  17. Cunningham, P.: Automatic Toping System, Telemin 1 and 5th Int. Symp. Mine Mech. Autom, Sudbury (1999)

    Google Scholar 

  18. Bissiri, Y., Baiden, G.R., Filion, S., Saari, A.: An automated surveying device for underground navigation. Min. Technol. 117, 2 (2008)

    Google Scholar 

  19. Zablocki, A.: Long hole drilling trends in Chilean underground mine applications, capacities and trends. In: 5th Int. Conf. Exhib. Mass Min., Lulea (2008)

    Google Scholar 

  20. Jämsä-Jounela, S.-L.: Future automation systems in context of process systems and minerals engineering. IFAC-PapersOnLine. 52(25), 403–408 (2019)

    Google Scholar 

  21. McCoy, J.T., Auret, L.: Machine learning applications in minerals processing: a review. Miner. Eng. 132, 95–109 (2019)

    Google Scholar 

  22. Jovanovic, I., Miljanovic, I., Jovanovic, T.: Soft computing-based modelling of flotation processes – a review. Miner. Eng. 84, 34–63 (2015)

    Google Scholar 

  23. Napier-Munn, T.J., Morrel, S., Kojovic, R.D.: Mineral Comminution Circuits: Their Operation and Optimization. JKMRC, Queensland (1999)

    Google Scholar 

  24. Kohmuench, J.N., Mankosa, M.J., Thanasekaran, H., Hobert, A.: Improving coarse particle flotation using the HydroFloat ™. Miner. Eng. 121, 137–145 (2018). https://doi.org/10.1016/j.mineng.2018.03.004

    Article  Google Scholar 

  25. Koivistoinen, P., Kalapudas, R., Miettunen, J.: A new method for measuring the volumetric filling of a grinding mill. In: Kaeatra, S.K. (ed.) Comminution Theory and Practice, pp. 563–574. Society for Mining, Metallurgy and Exploration, Littleton (1992)

    Google Scholar 

  26. Järvinen, J.: A volumetric charge measurement for grinding mills. IFAC Proc. Vol. 37(15), 41–46 (2004)

    Google Scholar 

  27. Spencer, S.-J., Campbell, J.-J., Weller, K.-R., Liu, Y.: Acoustic emissions monitoring of SAG mill performance. In: Proc. 2nd Int. Conf. Intell. Process. Manuf. Mater. IPMM’99, pp. 939–946 (1999)

    Google Scholar 

  28. Jämsä-Jounela, S.-L.: Modern approaches to control of mineral processing. Acta Polytech. Scand. Math. Comput. Sci. Ser. 57, 61 (1990)

    Google Scholar 

  29. Zhou, P., Gao, Y., Chai, T.: Multivariable grinding circuit control: an modified analytical decoupling control approach within a unity feedback control structure. Adv. Mater. Res. 433–440, 6832–6837 (2012)

    Google Scholar 

  30. Craig, I.K.: Grinding mill modelling and control: past, present and future. In: Proceedings of the 31st Chinese Control Conference, pp. 16–21 (2012). ISBN 9789881563811

    Google Scholar 

  31. Ma, T.-Y., Gui, W.H.: Optimal control for continuous bauxite grinding process in ball mill. Control Theory Appl. 29(10), 1339–1347 (2012) ISSN 10008152

    Google Scholar 

  32. Karelovic, P., Razzetto, R., Cipriano, A.: Evaluation of MPC strategies for mineral grinding. IFAC Proc. Vol. 46(16), 230–235 (2013)

    Google Scholar 

  33. Estrada, F., Cipriano, A.: Hybrid model predictive control for mineral grinding. In: Proceedings of the 19th IFAC World Congress, pp. 11512–11517. Cape Town (2014)

    Google Scholar 

  34. Nieto-Chaupis, H.: Predictive control of the mineral particle size with kernel-reduced Volterra models in a balls mill grinding circuit. In: 2015 IEEE 24th International Symposium on Industrial Electronics (ISIE), pp. 113–118. IEEE (2015)

    Google Scholar 

  35. Coetzee, L.C., Ramonotsi, M.: Applying StarCS RNMPC with real-time optimiser to pilanesberg platinum mines primary UG2 milling circuit. IFAC-PapersOnLine. 49(20), 78–83 (2016). https://doi.org/10.1016/j.ifacol.2016.10.100

    Article  Google Scholar 

  36. Botha, S., le Roux, J.D., Craig, I.K.: Hybrid nonlinear model predictive control of a run-of-mine ore grinding mill circuit. Miner. Eng. 123, 49–62 (2018)

    Google Scholar 

  37. Bouchard, J., Desbiens, A., Poulin, É.: Reducing the energy footprint of grinding circuits: the process control paradigm. IFAC-PapersOnLine. 50(1), 1163–1168 (2017)

    Google Scholar 

  38. Olivier, L.E., Craig, I.K.: Should I shut down my processing plant? An analysis in the presence of faults. J. Process Control. 56, 35–47 (2017)

    Google Scholar 

  39. Vyhmeister, E., Reyes-Bozo, L., Rodriguez-Maecker, R., Fúnez-Guerra, C., Cepeda-Vaca, F., Valdés-González, H.: Modeling and energy-based model predictive control of high pressure grinding roll. Miner. Eng. 134, 715 (2019). https://doi.org/10.1016/j.mineng.2019.01.016

    Article  Google Scholar 

  40. Laurila, H., Karesvuori, J., Tiili, O.: Strategies for instrumentation and control of flotation circuits. In: Mular, A.L., Halbe, D.N., Barratt, D.J. (eds.) Mineral Processing Plant Design, Practice and Control. Society of Mining, Metallurgy and Exploration, Littleton (2002)

    Google Scholar 

  41. Kampjarvi, P., Jämsä-Jounela, S.-L.: Level control strategies for flotation cells. Miner. Eng. 16(11), 1061–1068 (2003)

    Google Scholar 

  42. Aldrich, C., Marais, C., Shean, B.J., Cilliers, J.J.: Online monitoring and control of froth flotation systems with machine vision: a review. Int. J. Mineral Process. 96(1–4), 1–13 (2010)

    Google Scholar 

  43. Jämsä-Jounela, S.-L., Laine, S., Ruokonen, E.: Ore type based expert systems in mineral processing plants. Part. Part. Syst. Charact. 15(4), 200–207 (1998)

    Google Scholar 

  44. Lu, M., Xie, D.H., Gui, W.H., Wu, L.H., Chen, C.Y., Yang, C.: A Cascaded recognition method for copper rougher flotation working conditions. Chem. Eng. Sci. 175, 220–230 (2018)

    Google Scholar 

  45. Brooks, K., Munalula, W.: Flotation velocity and grade control using cascaded model predictive controllers. IFAC PapersOnLine. 50(2), 25–30 (2017)

    Google Scholar 

  46. Brooks, K.S., Koorts, R.: Model predictive control of a zinc flotation bank using online X-ray fluorescence analysers. IFAC-PapersOnLine. 50(1), 10214–10219 (2017)

    Google Scholar 

  47. Baiden, G.: Geospatial Mapping and Surveying Robotics for both GPS and GPS Denied Environments. Society of Mining Engineers, Annual General Meeting, Denver (2017)

    Google Scholar 

  48. Baiden, G.: Robotic Hang-up Assessment and Removal of Rock Blockages in Mining Operations. Massmin 2016, Sydney (2016)

    Google Scholar 

  49. Li, Q., Chen, Z., Zhang, B., Li, B., Lu, K., Lu, L., Guo, H.: Detection of tailings dams using high resolution satellite imagery and a single shot multibox detector in the Jing-Jin-J Region, China. Remote Sens. 12(16), 2626 (2020). https://doi.org/10.3390/RS12162626

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Biotechnology and Chemical Technology, Aalto University, Espoo, Finland

    Sirkka-Liisa Jämsä-Jounela

  2. School of Engineering, Laurentian University, Sudbury, ON, Canada

    Greg Baiden

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  1. Sirkka-Liisa Jämsä-Jounela
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  2. Greg Baiden
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Correspondence to Greg Baiden .

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Editors and Affiliations

  1. PRISM Center and School of Industrial Engineering, Purdue University, West Lafayette, IN, USA

    Shimon Y. Nof

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Jämsä-Jounela, SL., Baiden, G. (2023). Automation and Robotics in Mining and Mineral Processing. In: Nof, S.Y. (eds) Springer Handbook of Automation. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-030-96729-1_41

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