Auxiliary information based HEWMA chart using variable sampling interval

The use of auxiliary information concept (AIC) and variable sampling interval (VSI) feature in control charts is shown to enhance the sensitivity of the charts in out-of-control detection. In this paper, the VSI hybrid exponentially weighted moving average (HEWMA) chart based on auxiliary information (denoted as the VSI AIC-HEWMA) for the process mean is proposed, where two levels of sampling interval are considered, with test statistic that considers both information from the study and auxiliary characteristics. Monte-Carlo simulation is used to compute the average time to signal (ATS), standard deviation of the time to signal (SDTS) and expected ATS (EATS) of the chart. The VSI AIC-HEWMA chart is then compared with the auxiliary information based variable sampling interval exponentially weighted moving average (VSI AIC-EWMA) and AIC-HEWMA charts. Results show that the VSI AIC-HEWMA chart is more sensitive than the competing charts for all sizes of shift in out-of-control detection, by having the smallest out-of-control ATS and EATS values.