摘要：Misleading signals (MS) are valid alarms which correspond to the misinterpretation of a shift in the process mean (resp. variance) as a shift in the pro cess variance (resp. mean), when we deal with simultaneous schemes for these two parameters. MS can be fairly frequent, as reported by some authors, and o ccur for instance when: – the individual chart for the mean triggers a signal before the one for the variance, even though the process mean is on-target and the variance is o.-target; or – the individual chart for the variance triggers a signal before the one for the mean, although the variance is in-control and the pro cess mean is out-of-control. This paper illustrates how (un)reliable are the traditional simultaneous Shewhart- and EWMA-type schemes in identifying which parameter has changed, under the false assumption of independence, namely when the output process within each sample follows AR(1), AR(2) or ARMA (1,1) models. This is done by means of Monte Carlo simulation and the estimation of the probability of a misleading signal (PMS). Finally, we go on to compare these estimates of PMS with the values of the PMS of simultaneous Shewhart- and EWMA-type residual schemes whose control statistics take into account the autocorrelation structure of the output process.
关键词：statistical process control; misleading signals; time series; simultaneous residual schemes
