Two types of control charts exist based on different quality characteristics: variable and attribute. These characteristics are commonly monitored using separate procedures. Only a few studies focused on the utilization of control charts to monitor a process with mixed characteristics. This study develops a new concept of the T2 control chart based on a Principal Component Analysis (PCA) Mix, that is a PCA method that can jointly handle continuous and categorical data. The Kernel Density Estimation (KDE) method is used to estimate the control limit. Through simulation studies, the performance of the proposed chart is evaluated using the Average Run Length (ARL). (Formula presented.) control limits obtained from KDE produce a stable ARL0 at ~ 370 for α = 0:00273. For the shifted process, the proposed chart demonstrates excellent performance for an appropriate number of principal components used. Applications of the simulated process and real cases show that the proposed chart is sensitive to monitoring the shifted process.

Original languageEnglish
Pages (from-to)364-384
Number of pages21
JournalProduction and Manufacturing Research
Issue number1
Publication statusPublished - 1 Jan 2018


  • Mixed chart
  • PCA mix
  • T control chart
  • average run length
  • kernel density estimation


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