posted on 2022-12-12, 11:43authored byVincent Cregan, William T. Lee, Louise Clune
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
History
Publication
Journal of Mathematics in Industry;7:7
Publisher
SpringerOpen
Note
peer-reviewed
Other Funding information
SFI, Embark Initiative postgraduate Award
Language
English
Also affiliated with
MACSI - Mathematics Application Consortium for Science & Industry