Multivariate statistical analysis of an emulsion batch process

The power of multivariate statistical methodologies, namely, MPCA (multiway principal component analysis) and MPLS (multiway projection to latent structures or multiway partial least squares), for batch process analysis, monitoring, fault diagnosis, product quality prediction, and improved process insight is illustrated. These techniques were successfully applied to an industrial emulsion polymerization batch process. One key feature of this work is that reaction extent was used as the common reference scale to align batches with varying time durations. MPCA/MPLS technology (1) detected potential process abnormalities, (2) determined the time an abnormal event occurred, and (3) indicated the likely variable or variables which caused the abnormality. The results also indicated that variations in an ingredient trajectory and heat removal variables were primarily associated with viscosity variability. The resultant PLS model predicted the product viscosities within measurement error, thereby improving our wo...