Monitoring the Process Mean and Variance Using Individual Observations and Variable Sampling Intervals

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Individuals control schemes for monitoring the mean and variance of processes subject to drifts (2001, methodology): “1: Instead of using a single two-sided EWMA chart, we use two individual one-sided EWMA charts run in parallel, because the two-chart schemes are robust to potential inertial problems in the EWMA statistics that can increase the delay in detecting process changes (see Reynolds and Stoumbos [8], Stou”
Monitoring Process Mean and Variability with One Non-central Chi-square Chart (2004, methodology): “If it is important to detect small changes in the process, it is reasonable to consider an EWMA chart (see Reynolds & Stoumbos, 2001).”
Self-starting control chart for simultaneously monitoring process mean and variance (2010, methodology): “…that are designed for monitoring the mean and variability, respectively, such as the combination of Shewhart X (or X) and R (MR or S) charts (Rahim 1989, Saniga 1989, Costa 1993, Rahim and Costa 2000) and the combination of EWMA-type charts (Domangue and Patch 1991, Reynolds and Stumbos 2001).”
Multivariate EWMA control charts using individual observations for process mean and variance monitoring and diagnosis (2008, background): “If a mean shift occurs but the control charts for variability give the signal, then a misleading signal takes place and vice versa (see Reynolds and Stoumbos 2001 for the univariate cases).”