The Reverse Moving Average Control Chart for Monitoring Autocorrelated Processes

Abstract

Forecast-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.

• Autocorrelation
• Autoregressive Moving Average
• Exponentially Weighted Moving Average
• Forecasting Techniques
• Statistical Process Control

Additional information

Notes on contributors

John N. Dyer

Dr. Dyer is an Assistant Professor of Decision Sciences. He is a Member of ASQ. His email address is [email protected].

Benjamin M. Adams

Dr. Adams is an Associate Professor of Statistics. He is a Member of ASQ. His email address is [email protected].

Michael D. Conerly

Dr. Conerly is a Professor of Statistics. His email address is [email protected].