Model-based and model-free control of autocorrelated processes

George Runger, Thomas R. Willemain

Research output: Contribution to journalArticle

81 Citations (Scopus)

Abstract

Advances in automated sampling technology have made autocorrelated data commonplace. Positive autocorrelation degrades control charts designed by classical methods. If a correct time-series model of the autocorrelated process is available, many have advocated the use of control charts on the residuals from the model. Using the average run length criterion in an AR(1) model, we show that plotting averages of batches of the raw data can be an effective alternative to plotting residuals. We consider both weighted averages and the simple, model-free approach of arithmetic averages. We compare these statistics to residuals in both Shewhart and cumulative sum (CUSUM) control charts.

Original languageEnglish (US)
Pages (from-to)283-292
Number of pages10
JournalJournal of Quality Technology
Volume27
Issue number4
StatePublished - Oct 1995
Externally publishedYes

Fingerprint

Control Charts
Model-based
Average Run Length
Cumulative Sum
Weighted Average
Time Series Models
Autocorrelation
Batch
Model
Statistics
Time series
Alternatives
Sampling
Control charts

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Statistics and Probability

Cite this

Model-based and model-free control of autocorrelated processes. / Runger, George; Willemain, Thomas R.

In: Journal of Quality Technology, Vol. 27, No. 4, 10.1995, p. 283-292.

Research output: Contribution to journalArticle

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