Assignable causes and autocorrelation: Control charts for observations or residuals?

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

In many industrial processes, the disturbance generated by an assignable cause is affected by the same inertial elements as the observations from the common-cause system. In these cases, the manifestation of the assignable cause differs from that in many common models. A control chart based on the observations can be effective for statistical process control, but its success depends on the relationship of the time-series model produced by the inertial elements to the magnitude of the disturbance in the input. This characterization provides insight into the research that compares charts based on residuals to those based on the raw data. A simple example of a dynamic system is provided.

Original languageEnglish (US)
Pages (from-to)165-170
Number of pages6
JournalJournal of Quality Technology
Volume34
Issue number2
StatePublished - Apr 2002

Fingerprint

Control Charts
Autocorrelation
Disturbance
Statistical Process Control
Statistical process control
Time Series Models
Chart
Dynamic Systems
Time series
Dynamical systems
Observation
Control charts
Model
Relationships
Charts
Time series models
Dynamic systems

Keywords

  • Autoregressive processes
  • Stationary processes

ASJC Scopus subject areas

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

Cite this

Assignable causes and autocorrelation : Control charts for observations or residuals? / Runger, George.

In: Journal of Quality Technology, Vol. 34, No. 2, 04.2002, p. 165-170.

Research output: Contribution to journalArticle

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