Monitoring multivariate-attribute quality characteristics in two-stage processes using discriminant analysis based control charts

In this paper, we focus specifically on a two-stage process with multivariate attribute quality characteristics in the second stage. the main purpose of this study is extending discriminant analysis (da) based control charts to monitor a two-stage process. we propose three methods including ewma (da), integrated ewma (da), and p-value (da), and integrated multivariate exponentially weighted moving average (mewma) and t^2 charts based on the da approach to monitor the multivariate-attribute quality characteristic in a two-stage process. the performance of the proposed methods is evaluated through simulation studies as well as a real case.