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

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

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
DOIs
StatePublished - Apr 2002

Keywords

  • Autoregressive processes
  • Stationary processes

ASJC Scopus subject areas

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

Fingerprint

Dive into the research topics of 'Assignable causes and autocorrelation: Control charts for observations or residuals?'. Together they form a unique fingerprint.

Cite this