Abstract: Concurrent PLS (CPLS) further extracts information from the residuals of input variables and quality variables drawn by PLS, thus the raw data are projected into five subspaces. The process monitoring based CPLS provides a whole framework for the monitoring of input variables and quality variables. The model for residuals is developed by a deterministic manner while the residuals are inherently stochastic; therefore a probabilistic model is more proper for describing their features. This paper introduces factor analysis (FA) into CPLS, in which FA instead of PCA is used to analyze the residuals to develop the improved CPLS model, and the monitoring indices for checking the validity of variables satisfying Gaussian distribution are built to improve the consistence between the modeling objective and the monitoring indices.

Key words: CPLS, factor analysis, expectation maximization (EM) algorithm, process monitoring