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Analysis and perspectives on multivariate statistical process control charts used in the industrial sector: a systematic literature review

Ueda Renan M., Agostino Ìcaro R. S., Souza Adriano M.

Management and Production Engineering Review

2022

Vol. 13, No. 2

48--60

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 T2 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.

Some notes on multivariate statistical process control

Rogalewicz M.

Management and Production Engineering Review

2012

Vol. 3, No. 4

80-86

In the article some features of multivariate statistical process control were introduced. Advantages and disadvantages of multivariate control charts (Hotelling charts) - counterpart of traditional Shewhart control charts in multivariate space - were also shown. The author pointed out the advantage of Hotelling charts over traditional ones in some situations. The main part of the paper is a multivariate surveillance procedure based on the division on two stages: Phase I (phase of stabilization) and Phase II (phase of monitoring). After describing some elements of multivariate statistical process control implementation (considered from the methodological point of view) author introduced two most popular control charts used in industrial practice: control charts for individual observations and for means. The article is summarized by some author's conclusions concerning popularity of multivariate surveillance and future directions of his work.