Empirical nonparametric control charts for high-quality processes

Willem Albers*

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    6 Citations (Scopus)
    4 Downloads (Pure)


    For attribute data with (very) small failure rates often control charts are used which decide whether to stop or to continue each time r failures have occurred, for some r$\geq$1. Because of the small probabilities involved, such charts are very sensitive to estimation effects. This is true in particular if the underlying failure rate varies and hence the distributions involved are not geometric. Such a situation calls for a nonparametric approach, but this may require far more Phase I observations than are typically available in practice. In the present paper it is shown how this obstacle can be effectively overcome by looking not at the sum but rather at the maximum of each group of size r.
    Original languageEnglish
    Pages (from-to)3151-3159
    Number of pages12
    JournalJournal of statistical planning and inference
    Issue number9
    Publication statusPublished - Sept 2011


    • Statistical process control
    • Order statistics
    • MSC-62C05
    • MSC-62G15
    • Estimated parameters
    • Average run length
    • Geometric charts
    • Health care monitoring
    • MSC-62P10


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