Skip to content

A soft sensor for the Bayer process

Research output: Contribution to journalArticlepeer-review

  • Vincent Cregan
  • William 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.
Original languageEnglish
Pages (from-to)1-6
Number of pages7
JournalJournal of Mathematics in Industry
Volume7
Issue number7
DOIs
Publication statusPublished - 4 May 2017

Documents

Related information

Relations Get citation (various referencing formats)

ID: 7032672