Quality control charts are extensively used to monitor processes. The EWMA chart is a good alternative to the Shewhart chart to quickly detect small and moderate shifts in the process mean. The DEWMA charting procedure is an enhanced approach for the EWMA chart and performs much better, especially for small and moderate shifts. In this article, we propose the triple EWMA (TEWMA) chart in an effort to improve much more the detection ability of the classical EWMA chart. Monte Carlo simulations are used to evaluate the run-length characteristics of the proposed chart. A comparison study versus the DEWMA, EWMA and GWMA charts indicates that the TEWMA chart with time-varying control limits is more effective in detecting small shifts while it is comparable with the other charts in moderate and large shifts. Moreover, the proposed chart has better inertia properties than the competing charts and is also shown to be in-control robust for small values of the smoothing parameter. Finally, two examples are given to display the application of the TEWMA chart.

TIn high quality processes when the events occur rarely, the times between events (TBE) are observed and also monitored instead of the number of events. In this case, it can be assumed that the times between events follow a gamma distribution. A one-sided Double Exponentially Moving Average control chart to monitor the TBE (regarded as DEWMA-TBE chart) is proposed in the present work. The design parameters of the proposed chart are provided and through a simulation study, it is seen that the DEWMA-TBE chart is more effective than the EWMA and Shewhart charts at detecting downward shifts.