Multivariate charting techniques: A review and a line-column approach

Abstract

The primary objective of multivariate statistical process control is to monitor the related process quality characteristics over time and identify the assignable causes affecting the process using multivariate control charts. When an outof-control signal is obtained from the chart, it is imperative to be able to detect the component variables that have gone out-of-control. In this paper we propose a new charting procedure for T2, multivariate exponentially weighted moving average and multivariate cumulative sum control charts. The proposed charts will facilitate in identification of the source of out-of-control signal and are simple, economical and easier to implement. Copyright © 2009 John Wiley & Sons, Ltd.