29 kesä Sustainable mineral processing by on-line optical measurements towards better process management – MineSense
Name: MineSense – Sustainable mineral processing by on-line optical measurements towards better process control
Duration: February, 2013 – October, 2014
Total costs (€)/Tekes support University of Oulu: 278ke /250ke, VTT: 277ke/249ke
Leading research organization partner: University of Oulu: Control Engineering, VTT: Optical measurements
Contact persons Kauko Leiviskä, Oulun yliopisto (kauko.leiviska(at)oulu.fi), Marko Paavola (Oulun yliopisto), marko.paavola(at)oulu.fi, Katariina Rahkamaa-Tolonen, VTT, (katariina.rahkamaa-tolonen(at)vtt.fi)
Research organization partners: University of Oulu, VTT
Company partners: Outotec, Metso, Schneider-Electric, First-Quantum Minerals, Belvedere Mining, Sofimine
International partners: Luleå University of Technology, University of Cape Town
Number of reviewed publications, incl. submitted manuscripts 3
Number of other publications and reports: 1
Number of thesis: Master 1
Need and motivation of the project:
Minimize the environmental and social impacts of mining, simultaneously maintaining the production efficiency.
Main set targets:
The goal of the project was to apply novel optical instrumentation and process control to the whole cycle of ore beneficiation aiming to improve sustainability. Using the latest on-line optical instrumentation for monitoring important process parameters of each stage together with advanced mill-wide process control would enable better control and optimization of the processes, leading to savings in raw material use, chemicals, water and energy.
During the project UO focused in modelling and soft sensor development and VTT to the development of optical and machine vision based measurements. The modelling work was divided to two distinctive tasks, development of a static and dynamic models. The developed models will assist in commissioning of the mini-pilot line in several ways. For example, they can be used to simulate different operating conditions and alternatives giving important information for process optimization. Also operator decisions can be simulated and thus the plant can be operated in more efficiently. In industrial scale, all these result would make more efficient raw materials usage possible. The models have been presented in international conferences and at the moment one of the papers is submitted to Minerals Engineering journal. The modelling work was supported by researcher exchange to Luleå University of Technology.
A researcher exchange was also carried out at University of Cape Town during the project. There, the objective of M.Sc. Senni Uusi-Hallila was to study the froth phase behavior in order to understand the flotation performance and to develop machine vision based flotation monitoring algorithms. Series of batch flotation experiments were executed in University of Cape Town with the wide range of operating conditions. The work concluded that online measurements obtained from FrothSense™ with wide range of operating conditions can be used for soft sensors. Soft sensors can estimate the stability of the froth with the robust predictions. A journal paper about the results is being prepared with University of Cape Town.
VTT evaluated and selected both machine vision and optical measurements-based monitoring technologies for mineral beneficiation process monitoring. The use of machine vision for monitoring bubble size inside the flotation cell was motivated by a clear industrial need for this kind of measurement device. On-line bubble size measurement inside froth in flotation processes gives faster response to changes in the process, enabling better process control and yield. In addition, it gives better understanding of bubble behavior in different depths of flotation cells. The performance of the technique was verified in a laboratory batch reactor and at the minipilot. The measurement was shown to be usable for monitoring the Cu grade in flotation.
VTT developed also measurement for monitoring dry and wet particle size from the grinding circuit and studied measurement of ore moisture content using SWIR. The measurements were developed in laboratory (wet particle size, moisture content) and at the minipilot (particle size, dry). All the measurements were shown to be applicable for their tasks, however, the aforementioned bubble size monitoring inside the flotation cell was commercially the most interesting one.
MineSense-project also resulted into several H2020 applications. Intensified by Design®, IbD, was accepted and was started in autumn 2015. Holonic-Based Virtualization Platform for the Real-Time Optimization and Scheduling of Plant-Wide Operations (TOTUM), was positively evaluated (2016), but received no funding (at the moment, on reserve list). Last, a proposal submitted together with Keliber, LightMine, is in the evaluation.
Commercialization measures and/or potential:
The modelling work and development of mineral processing control with the aid of optical measurements are further continued in the accepted H2020-project (Intensified by Design®, IbD). The MineSense-partners participating the IbD-project are University of Oulu, VTT, Outotec and Pyhäsalmi mine (FQM). The research in IbD focuses on grinding circuit. Moreover, the use of the developed bubble size measurement in flotation monitoring is further studied.
If funding is received, the plant-wide control and modelling work is also continued in the two other aforementioned H2020 projects (TOTUM and LightMine).
LIST OF PUBLICATIONS
Decision support system based on a dynamic flotation circuit model (Submitted to Minerals Engineering Journal).
Development and calibration of a dynamic flotation circuit model A. Sorsa, P. Seppälä, M. Paavola, J. Ruuska, H. Kumar, K. Leiviskä, A. Remes P. Lamberg. Flotation ’15, Cape Town, 2015.
Seppälä, P., Sorsa, A., Paavola, M., Remes, A., Ruuska, J., Leiviskä, K.: Pilot Plant Simulation as a Tool for More Efficient Mineral Processing . 19th IFAC World Congress, Cape Town, South Africa, 2014.
Uusi-Hallila, S. Utilizing Froth Phase Behaviour and Machine Vision to Indicate Flotation Performance. M.Sc. Thesis, 2014.
Paavola, M., Sorsa, A., Seppälä, P., Rahkamaa-Tolonen, K., Mitikka, R., Leiviskä, K.: MineSense Sustainable mineral processing by on-line optical measurements towards better process management – Final Report, February 2015.