Design of exponentially weighted moving average control charts for autocorrelated processes with model uncertainty

Daniel W. Apley*, Hyun Cheol Lee

*Corresponding author for this work

Research output: Contribution to specialist publicationArticle

64 Scopus citations

Abstract

Residual-based control charts are popular methods for statistical process control of autocorrelated processes. To implement these methods, a time series model of the process is required. The model must be estimated from data, in practice, and model estimation errors can cause the actual in-control average run length to differ substantially from the desired value. This article develops a method for designing residual-based exponentially weighted moving average (EWMA) charts under consideration of the uncertainty in the estimated model parameters. The resulting EWMA control limits are widened by an amount that depends on a number of factors, including the level of model uncertainty.

Original languageEnglish
Pages187-198
Number of pages12
Volume45
No3
Specialist publicationTechnometrics
StatePublished - Aug 2003

Keywords

  • Autoregressive moving average model
  • Exponentially weighted moving average chart
  • Mean shift detection
  • Residual-based control chart

ASJC Scopus subject areas

  • Mathematics(all)
  • Statistics and Probability

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