The Reverse Moving Average Control Chart for Monitoring Autocorrelated Processes

Abstract

AbstractForecast-based monitoring schemes have been researched extensively in regards to applying traditional control charts to forecast errors arising from various autocorrelated processes. The dynamic response and behavior of forecast errors after experiencing a shift in the process mean make it difficult to choose a suitable control chart. In this paper we propose the reverse moving average control chart as a new forecast-based monitoring scheme, compare the new control chart to traditional methods applied to various ARMA(1,1), AR(1), and MA(1) processes, and make recommendations concerning the most appropriate control chart to use in a variety of situations when charting autocorrelated processes.KeywordsAutocorrelationAutoregressive Moving AverageExponentially Weighted Moving AverageForecasting TechniquesStatistical Process Control Additional informationNotes on contributorsJohn N. DyerDr. Dyer is an Assistant Professor of Decision Sciences. He is a Member of ASQ. His email address is [e-mail] M. AdamsDr. Adams is an Associate Professor of Statistics. He is a Member of ASQ. His email address is [e-mail] D. ConerlyDr. Conerly is a Professor of Statistics. His email address is [e-mail].