An attribute chart for monitoring the process mean and variance

Salah Haridy, Zhang Wu, Ka Man Lee, M. Abdur Rahim

Research output: Journal article publicationJournal articleAcademic researchpeer-review

24 Citations (Scopus)

Abstract

This article proposes an attribute chart for variables (AFV chart) that employs an attribute inspection (checking whether a unit is conforming or nonconforming) to monitor not only the mean but also the variance of a variable x. The salient feature of the AFV chart is its ability to determine the process status (i.e. in control or out of control) by applying the very simple attribute inspection to a single unit. By selecting its inspection limits appropriately, the AFV chart usually outperforms the joint X̄ & R and X̄ & S charts from an overall viewpoint under different circumstances. The AFV chart has the advantage of being extremely simple in design and implementation, and having a very low cost for operation. In particular, the AFV chart uses a single-attribute inspection for each sample, works as a leading indicator of trouble and allows operators to take the proper corrective action before any defective is actually produced. Since the AFV chart is simpler, more effective and less costly than the X̄ & R and X̄ & S charts, it may be highly preferred for many statistical process control applications, in which both the mean and variance of a variable need to be monitored.
Original languageEnglish
Pages (from-to)3366-3380
Number of pages15
JournalInternational Journal of Production Research
Volume52
Issue number11
DOIs
Publication statusPublished - 3 Jun 2014

Keywords

  • attribute inspection
  • control chart
  • loss function
  • statistical process control

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Management Science and Operations Research
  • Strategy and Management

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