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Engineering    2017, Vol. 3 Issue (2) : 183 -187
Research |
Recent Progress on Data-Based Optimization for Mineral Processing Plants
Jinliang Ding(),Cuie Yang,Tianyou Chai
State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China

In the globalized market environment, increasingly significant economic and environmental factors within complex industrial plants impose importance on the optimization of global production indices; such optimization includes improvements in production efficiency, product quality, and yield, along with reductions of energy and resource usage. This paper briefly overviews recent progress in data-driven hybrid intelligence optimization methods and technologies in improving the performance of global production indices in mineral processing. First, we provide the problem description. Next, we summarize recent progress in data-based optimization for mineral processing plants. This optimization consists of four layers: optimization of the target values for monthly global production indices, optimization of the target values for daily global production indices, optimization of the target values for operational indices, and automation systems for unit processes. We briefly overview recent progress in each of the different layers. Finally, we point out opportunities for future works in data-based optimization for mineral processing plants.

Keywords Data-based optimization      Plant-wide global optimization      Mineral processing      Survey     
Corresponding Authors: Jinliang Ding   
Just Accepted Date: 21 March 2017   Online First Date: 13 April 2017    Issue Date: 27 April 2017
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Jinliang Ding
Cuie Yang
Tianyou Chai
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Jinliang Ding,Cuie Yang,Tianyou Chai. Recent Progress on Data-Based Optimization for Mineral Processing Plants[J]. Engineering, 2017, 3(2): 183 -187 .
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