Average run lengths for CUSUM control charts applied to residuals

George Runger, Thomas R. Willemain, Sharad Prabhu

Research output: Contribution to journalArticlepeer-review

75 Scopus citations


A common approach to building control charts for autocorrelated data is to apply classical SPC to the residuals from a time series model of the process. However, Shewhart charts and even CUSUM charts are less sensitive to small shifts in the process mean when applied to residuals than when applied to independent data. Using an approximate analytical model, we show that the average run length of a CUSUM chart for residuals can be reduced substantially by modifying traditional chart design guidelines to account for the degree of autocorrelation in the data.

Original languageEnglish (US)
Pages (from-to)273-282
Number of pages10
JournalCommunications in Statistics - Theory and Methods
Issue number1
StatePublished - Jan 1 1995
Externally publishedYes


  • ARMA models
  • autocorrelation
  • control charts
  • residuals
  • statistical process control

ASJC Scopus subject areas

  • Statistics and Probability


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