Resumen de Monitoring Multivariate Process Variability for Individual Observations
Longcheen Huwang, Arthur B. Yeh, Chien-Wei Wu
Two control charts are proposed to monitor multivariate process variability for individual observations. The charts are constructed based on the traces of the estimated covariance matrices derived from the individual observations. When there is only one quality characteristic, these charts respectively reduce to the exponentially weighted mean squared deviation and exponentially weighted moving variance charts. Simulation studies and an example from the semiconductor industry show the charts are superior in detecting increases in variance and changes in correlation.
