An optimal filter design approach to statistical process control

Daniel W. Apley*, Chang Ho Chin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


Many control charts can be viewed as charting the output of a linear filter applied to process data, with an alarm sounded when the filter output falls outside a set of control limits. We generalize this concept by considering a linear filter in its most general time-invariant form. We provide a strategy for optimizing the filter coefficients in order to minimize the out-of-control ARL, while constraining the in-control ARL to some desired value. The optimal linear filters exhibit a number of interesting characteristics, in particular when the process data are autocorrelated. In many situations, they also substantially outperform an optimally designed exponentially weighted moving average (EWMA) control chart.

Original languageEnglish (US)
Pages (from-to)93-117
Number of pages25
JournalJournal of Quality Technology
Issue number2
StatePublished - 2007


  • Autocorrelation
  • Control charts
  • Linear filtering
  • Markov chain method
  • Statistical process control

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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