Analysis and Perspectives on Multivariate Statistical Process Control Charts used in the Industrial Sector: a Systematic Literature Review

Abstract

The objective of this article is to carry out a systematic review of the literature on multivariate statistical process control (MSPC) charts used in industrial processes. The systematic review was based on articles published via Web of Science and Scopus in the last 10 years, from 2010 to 2020, with 51 articles on the theme identified. This article sought to identify in which industry the MSPC charts are most applied, the types of multivariate control charts used and probability distributions adopted, as well as pointing out the gaps and future directions of research. The most commonly represented industry was electronics, featuring in approximately 25% of the articles. The MSPC chart most frequently applied in the industrial sector was the traditional T 2 of Harold Hotelling (Hotelling, 1947), found in 26.56% of the articles. Almost half of the combinations between the probabilistic distribution and the multivariate control graphs, i.e., 49.4%, considered that the data followed a normal distribution. Gaps and future directions for research on the topic are presented at the end.