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Date
2017
Abstract
A soft sensor for measuring product quality in the Bayer process has been developed. The soft sensor uses a combination of historical process data recorded from online sensors and laboratory measurements to predict a key quality indicator, namely particle strength. Stepwise linear regression is used to select the relevant variables from a large dataset composed of monitored properties and laboratory data. The developed sensor is employed successfully by RUSAL Aughinish Alumina Ltd to predict product strength five days into the future with R-squared equal to 0.75 and to capture deviations from standard operating conditions
Supervisor
Description
peer-reviewed
Publisher
Springer Open
Citation
Journal of Mathematics in Industry;7:7
Files
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Lee_2017_Bayer.pdf
Adobe PDF, 1.09 MB
ULRR Identifiers
Funding code
Funding Information
Science Foundation Ireland (SFI), Embark Initiative postgraduate Award