Robust control charts

Research output: Contribution to journalArticlepeer-review

97 Scopus citations


If the number of false alarms when the process is in control is held constant, the most sensitive procedures for detecting the out-of-control state are those that plot a subgroup statistic that is sensitive to outliers (e.g., mean or range) but determine the control limits in a resistant fashion. Ordinary charting procedures, such as the standard X̄ and R charts, perform less well, and the worst performance is turned in by procedures in which the subgroup statistics are themselves resistant (e.g., median charts). To illustrate the point that robustness depends not only on resistance of the statistical tools to outliers but also on the purpose of the analysis, robust cumulative sum charts are briefly discussed.

Original languageEnglish (US)
Pages (from-to)173-184
Number of pages12
Issue number2
StatePublished - May 1989

ASJC Scopus subject areas

  • Mathematics(all)
  • Statistics and Probability


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