Self adapting control charts

Willem Albers, Wilbert C.M. Kallenberg

    Research output: Contribution to journalArticleAcademicpeer-review

    14 Citations (Scopus)
    11 Downloads (Pure)

    Abstract

    When the distributional form of the observations differs from normality, standard control charts are often seriously in error. Such model errors can be avoided with (modified) nonparametric control charts. Unfortunately, these control charts suffer from large stochastic errors due to estimation. In between are so called parametric control charts. All three of them are discussed in this paper as well as a combined chart, which chooses one of the three control charts according to the appropriate model assumption on the underlying distribution. The data themselves tell us which of the three control charts to select. Ready-made formulas for the several control charts are presented accompanied by an application on real data. Apart from bias removal, criteria based on exceedance probability and semi-variance are investigated.
    Original languageEnglish
    Pages (from-to)292-308
    Number of pages17
    JournalStatistica Neerlandica
    Volume60
    Issue number2
    DOIs
    Publication statusPublished - 2006

    Keywords

    • Exceedance probability
    • Model error
    • Model selection
    • Nonparametric
    • Normal power family
    • Phase II control limits
    • Statistical process control
    • unbiasedness
    • semi-variance
    • MSC-62G32
    • MSC-62P30
    • MSC-65C05

    Fingerprint

    Dive into the research topics of 'Self adapting control charts'. Together they form a unique fingerprint.
    • Self adapting control charts

      Albers, W. & Kallenberg, W. C. M., 2004, Enschede: University of Twente. 15 p. (Memorandum; no. 1713)

      Research output: Book/ReportReportProfessional

      Open Access
      File

    Cite this