Batch-means control charts for autocorrelated data

George Runger, Thomas R. Willemain

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

Modern statistical process control must often cope with large quantities of highly autocorrelated data. Alwan and Radson (1992) proposed the monitoring of autocorrelated processes by plotting the averages of small batches of data separated by skipping observations. Using results for the AR(1) process, we show that generally better performance can be achieved with no skipping and much larger batch sizes. The resulting batch-means charts derive from methods used in simulation output analysis and can be implemented easily with common digital control systems.

Original languageEnglish (US)
Pages (from-to)483-487
Number of pages5
JournalIIE Transactions (Institute of Industrial Engineers)
Volume28
Issue number6
StatePublished - 1996
Externally publishedYes

Fingerprint

Digital control systems
Statistical process control
Monitoring
Control charts
Batch
Charts
Simulation
Batch size

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Management Science and Operations Research

Cite this

Batch-means control charts for autocorrelated data. / Runger, George; Willemain, Thomas R.

In: IIE Transactions (Institute of Industrial Engineers), Vol. 28, No. 6, 1996, p. 483-487.

Research output: Contribution to journalArticle

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