Exponentially Weighted Moving Average Control Charts with Time-Varying Control Limits and Fast Initial Response

The control limits of an exponentially weighted moving average (EWMA) control chart should vary with time, approaching asymptotic limits as time increases. However, previous analytic analyses of EWMA charts consider only asymptotic control limits. In this article, the run length properties of EWMAs with time-varying control limits are approximated using nonhomogeneous Markov chains. Comparing the average run lengths of EWMA with time-varying control limits and results previously obtained for asymptotic EWMA charts shows that using time-varying control limits is akin to the fast initial response (FIR) feature suggested for Cumulative Sum (CUSUM) charts. The ARL of the EWMA scheme with time-varying l mits is substantially more sensitive to early process shifts especially when the EWMA weight is small. An additional improvement in FIR performance can be achieved by further narrowing the control limits for the first 20 observations. The methodology is illustrated assuming a normal process with known standard deviation where we wish to detect shifts in the mean.