Multivariate statistical process control methods for batch production: a review focused on applications

Abstract

In this paper, we highlight the basic techniques of multivariate statistical process control (MSPC) under the dimensionality criteria, such as Multiway Principal Component Analysis, Multiway Partial Squares, Structuration à Trois Indices de la Statistique, Tucker3, Parallel Factors, Multiway Independent Component Analysis, Multiset Canonical Correlation Analysis, Slow Features Analysis, and Parallel Coordinates. Furthermore, we summarize the procedures of each statistical technique and the usage of multivariate control charts. In addition, we review the most significant proposals and applications in practical cases. Finally, we compare and discuss the benefits and limitations within methods.