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Self‐adapting control charts

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  • Willem Albers
  • Wilbert C. M. Kallenberg

Abstract

When the distributional form of the observations differs from normality, standard control charts are often prone to serious errors. Such model errors can be avoided by using (modified) nonparametric control charts. Unfortunately, these control charts suffer from large stochastic errors caused by estimation. In between these two types are the so‐called parametric control charts. All three of them, as well as a combined chart, which chooses one of the three control charts according to the appropriate model assumption on the underlying distribution are discussed in this paper. The data indicate which of the three control charts to select. Readymade 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.

Suggested Citation

  • Willem Albers & Wilbert C. M. Kallenberg, 2006. "Self‐adapting control charts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(3), pages 292-308, August.
    • Handle: RePEc:bla:stanee:v:60:y:2006:i:3:p:292-308
    DOI: 10.1111/j.1467-9574.2006.00330.x
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    Cited by:

    1. Axel Gandy & Jan Terje Kvaløy, 2013. "Guaranteed Conditional Performance of Control Charts via Bootstrap Methods," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 647-668, December.
    2. Muhammad Riaz, 2008. "Monitoring process mean level using auxiliary information," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(4), pages 458-481, November.
    3. Rashid Mehmood & Muhammad Riaz & Ronald Does, 2013. "Efficient power computation for r out of m runs rules schemes," Computational Statistics, Springer, vol. 28(2), pages 667-681, April.
    4. Willem Albers & Wilbert C. M. Kallenberg, 2009. "Normal control charts with nonparametric safeguard," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(1), pages 63-81, February.
    5. Willem Albers & Wilbert C.M. Kallenberg, 2006. "Alternative Shewhart-type charts for grouped observations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 357-375.
    6. Muhammad Riaz & Ronald Does, 2009. "A process variability control chart," Computational Statistics, Springer, vol. 24(2), pages 345-368, May.

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