Monitoring Variability of Autocorrelated Processes using Standardized Time Series Variance Estimators

We consider the problem of monitoring variability of autocorrelated processes. This paper combines variance estimation techniques from the simulation literature with a statistical process control chart from statistical process control (SPC) literature. The proposed SPC method does not require any assumptions on the distribution of the underlying process and uses a variance estimate from each batch as a basic observation. The control limits of the chart are determined analytically. The proposed chart is tested using stationary processes with both normal and non-normal marginals