Towards Mineral Beneficiation Process Chain Intensification

Markku Ohenoja; Mika Ruusunen; Antti Koistinen; Jani Kaartinen; Janne Paaso; Ari Isokangas; Marko Paavola

doi:10.1016/j.ifacol.2018.09.418

Towards Mineral Beneficiation Process Chain Intensification

Markku Ohenoja, Mika Ruusunen, Antti Koistinen, Jani Kaartinen, Janne Paaso, Ari Isokangas, Marko Paavola

Research output: Contribution to journal › Article in a proceedings journal › Scientific › peer-review

3 Citations (Scopus)

Abstract

As a part of the H2020 SPIRE project, Intensified by Design (IbD®), mineral beneficiation process chain will be intensified in terms of more efficient usage of energy and raw materials. The work focuses on optimizing control of the grinding circuit, coarse flotation process, new solids measurements and soft-sensors, as well as adaptive dynamic mass balancing. All demonstrators are interconnected through plant-wide optimization. In this paper, the process intensification activities carried out at the mini-pilot scale mineral beneficiation plant are briefly described. The real-time adaptation strategy utilizing Differential Evolution for parameter estimation in a sliding window is presented. The initial results show a successful parameter estimation result even in a short time window.

Original language	English
Pages (from-to)	201-206
Journal	IFAC-PapersOnLine
Volume	51
Issue number	21
DOIs	https://doi.org/10.1016/j.ifacol.2018.09.418
Publication status	Published - 1 Jan 2018
MoE publication type	A4 Article in a conference publication
Event	5th IFAC Workshop on Mining, Mineral and Metal Processing, MMM 2018 - Shanghai, China Duration: 23 Aug 2018 → 25 Aug 2018

Funding

This work was developed under the financial support received from The EU Framework Programme for Research and Innovation – H2020-SPIRE-2015 (IbD® - Intensified by Design. GA-680565).

Keywords

Adaptive algorithms
Decision support system
Mineral processing
Process control
Process intensification

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10.1016/j.ifacol.2018.09.418

Cite this

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title = "Towards Mineral Beneficiation Process Chain Intensification",

abstract = "As a part of the H2020 SPIRE project, Intensified by Design (IbD{\textregistered}), mineral beneficiation process chain will be intensified in terms of more efficient usage of energy and raw materials. The work focuses on optimizing control of the grinding circuit, coarse flotation process, new solids measurements and soft-sensors, as well as adaptive dynamic mass balancing. All demonstrators are interconnected through plant-wide optimization. In this paper, the process intensification activities carried out at the mini-pilot scale mineral beneficiation plant are briefly described. The real-time adaptation strategy utilizing Differential Evolution for parameter estimation in a sliding window is presented. The initial results show a successful parameter estimation result even in a short time window.",

keywords = "Adaptive algorithms, Decision support system, Mineral processing, Process control, Process intensification",

author = "Markku Ohenoja and Mika Ruusunen and Antti Koistinen and Jani Kaartinen and Janne Paaso and Ari Isokangas and Marko Paavola",

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AU - Ohenoja, Markku

AU - Ruusunen, Mika

AU - Koistinen, Antti

AU - Kaartinen, Jani

AU - Paaso, Janne

AU - Isokangas, Ari

AU - Paavola, Marko

PY - 2018/1/1

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AB - As a part of the H2020 SPIRE project, Intensified by Design (IbD®), mineral beneficiation process chain will be intensified in terms of more efficient usage of energy and raw materials. The work focuses on optimizing control of the grinding circuit, coarse flotation process, new solids measurements and soft-sensors, as well as adaptive dynamic mass balancing. All demonstrators are interconnected through plant-wide optimization. In this paper, the process intensification activities carried out at the mini-pilot scale mineral beneficiation plant are briefly described. The real-time adaptation strategy utilizing Differential Evolution for parameter estimation in a sliding window is presented. The initial results show a successful parameter estimation result even in a short time window.

KW - Adaptive algorithms

KW - Decision support system

KW - Mineral processing

KW - Process control

KW - Process intensification

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Towards Mineral Beneficiation Process Chain Intensification

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Keywords

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