Advanced process monitoring and control methods in mineral processing applications

Antti Remes

    Research output: ThesisDoctoral ThesisCollection of Articles


    In minerals processing the high material volumes yield the fact that benefits of even small improvements in the process efficiency are remarkable. On a daily basis, the efficiency of a concentrating plant relies on the performance of the process control system, and secondly, on the adequate information of the process state provided for the plant operators. This thesis addresses the problems in the monitoring and control of the selected, widely applied mineral concentration unit processes and the processing circuits. The case studies cover operations in the ore grinding stages, including size separation units, followed subsequently by the concentration and the thickening stages in the downstream process. The developed methods and applications are all verified with industrial data, industrially identified models or by the practical implementations and tests on the industrial case plants. Advanced control systems - including a rule-based, a fuzzy and a model predictive control, with different combinations and setups - are studied with simulated grinding and flotation processes. A new model-based expert system for controlling of the ground ore particle size and the circulating load of the grinding process is proposed. The system was tested with a simulation model representing an industrial milling of apatite ore. In a plant-wide process monitoring, a data-based modeling approach is applied to predict the concentrate quality and the impact of the grinding stage parameters on that. The plant model, used for the monitoring, is updated adaptively; this enables timely information on the process. The monitoring system was set up based on the data of a chromite ore processing plant. Two unit operations, a hindered settling separator and a thickener, were modeled from a viewpoint of equipment monitoring and control purposes. The hindered settling separator incorporates both a mechanistic particle-settling model and a separation efficiency characterization curve in a novel manner. Separation characteristics in a pyrite concentrate case and in a ground apatite ore case were studied with the model. Operation of a thickener was modeled based on on-line mass-balance estimation. The monitoring application was implemented in an industrial apatite concentrate thickener. This thesis demonstrates the benefits of the above described monitoring and control methods. The metallurgical performance improvements are pointed out for each case. Also this thesis outlines the practical implementation and robustness issues for the methods. Thus the thesis promotes the advantages of more extensive use of plant models in process operation purposes.
    Translated title of the contributionRikastusprosessien moderni säätö ja monitorointi
    Original languageEnglish
    QualificationDoctor's degree
    Awarding Institution
    • Aalto University
    • Koivo, Heikki, Supervising Professor
    • Koivo, Heikki, Thesis Advisor
    Print ISBNs978-952-60-4511-5
    Electronic ISBNs978-952-60-4512-2
    Publication statusPublished - 2012
    MoE publication typeG5 Doctoral dissertation (article)


    • minerals processing
    • mining
    • modeling
    • simulation
    • control
    • optimisation


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