Effect of multivariate process instability on principal component analysis: a case study.
With the rising use of principal component analysis/partial least squares (PCA/PLS) in the process analytical technology (PAT) initiative of the pharmaceutical industry, it seems appropriate to view that approach from a statistical process control (SPC) perspective. The purpose of this study was to demonstrate the effect of process instability (ie, state of statistical out-of-control) on use of PCA/PLS. The demonstrated differences in results should encourage PCA/PLS users to incorporate SPC as an active part of their process analytical control (PAC) toolkit to check for stability prior to drawing conclusions based on PCA/PLS analysis.
Holmes
Donald S
DS
Stochos Inc, 14 North College Street, Schenectady, NY 12305, USA.
Mergen
A Erhan
AE
D016009:Chi-Square Distribution; D003198:Computer Simulation; D016018:Least-Squares Analysis; D015999:Multivariate Analysis; D025341:Principal Component Analysis