On the Use of Multivariate Statistical Methods to Detect, Diagnose and Mitigate Abnormal Events in Aluminium Smelters
- 2 February 2018
- book chapter
- Published by Springer Nature
- p. 475-483
Abstract
No abstract availableKeywords
This publication has 21 references indexed in Scilit:
- Multivariate statistical monitoring of the aluminium smelting processComputers & Chemical Engineering, 2011
- Aluminium process fault detection by Multiway Principal Component AnalysisControl Engineering Practice, 2011
- Estimation of alumina content of anode cover materials using multivariate image analysis techniquesChemical Engineering Science, 2008
- Data-based latent variable methods for process analysis, monitoring and controlComputers & Chemical Engineering, 2005
- Application of latent variable methods to process control and multivariate statistical process control in industryInternational Journal of Adaptive Control and Signal Processing, 2005
- PLS-regression: a basic tool of chemometricsChemometrics and Intelligent Laboratory Systems, 2001
- The development of aluminum reduction cell process controlJOM, 1999
- Process analysis, monitoring and diagnosis, using multivariate projection methodsChemometrics and Intelligent Laboratory Systems, 1995
- Principal component analysisChemometrics and Intelligent Laboratory Systems, 1987
- Partial least-squares regression: a tutorialAnalytica Chimica Acta, 1986