A comparison of multivariate moving average control charts for the process mean

Abstract

Two alternatives to the multivariate exponentially weighted moving average (EWMA) chart are considered. One of these alternatives is an arithmetic moving average control chart which is the arithmetic average of the sample means for the last k periods. The other alternative is a truncated version of the EWMA which truncates the EWMA after a fairly short period of time so that more emphasis is placed on the most current observation. Simulated average run length (ARL) results indicate that for some situations these alternatives charts outperform the multivariate EWMA chart. Some suggestions are made for designing charts to detect a specific shift and comparing the alternative charts. Some authors have noted that past in-control data may diminish the chart's ability to detect a shift in the process mean. To examine this, the scenario will be discussed when the process is in-control initially but goes out-of-control at some random time period. This is more like a realistic manufacturing setting, where the process is in-control initially, but after some time the process mean shifts to a new mean and in this paper it will be shown which control charts detect a shift faster using this scenario.