On the Effect of Measurement Error with Linearly Increasing-Type Variance on Simultaneous Monitoring of Process Mean and Variability

In most quality control applications, the errors generated from measurement system can adversely affect the ability of control charts in detecting out‐of‐control conditions. In this paper, the effect of measurement error with linearly increasing‐type variance on the performance of maximum exponentially weighted moving average and mean‐squared deviation (MAX‐EWMAMS) control chart is studied. For this purpose, different out‐of‐control scenarios including mean shifts, variance shifts, and simultaneous shifts in both are considered, and the detecting performance of the proposed approach is investigated through simulation study. The results of simulation study in terms of three criteria including average run length, standard deviation of run lengths, and the empirical distribution of run lengths prove that the measurement error with linearly increasing‐type variance can adversely affect the performance of MAX‐EWMAMS control.