Improving the Performance of the Chi-square Control Chart via Runs Rules
Markos V. Koutras (),
Sotirios Bersimis () and
Demetrios L. Antzoulakos ()
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Markos V. Koutras: University of Piraeus
Sotirios Bersimis: University of Piraeus
Demetrios L. Antzoulakos: University of Piraeus
Methodology and Computing in Applied Probability, 2006, vol. 8, issue 3, 409-426
Abstract The most popular multivariate process monitoring and control procedure used in the industry is the chi-square control chart. As with most Shewhart-type control charts, the major disadvantage of the chi-square control chart, is that it only uses the information contained in the most recently inspected sample; as a consequence, it is not very efficient in detecting gradual or small shifts in the process mean vector. During the last decades, the performance improvement of the chi-square control chart has attracted continuous research interest. In this paper we introduce a simple modification of the chi-square control chart which makes use of the notion of runs to improve the sensitivity of the chart in the case of small and moderate process mean vector shifts.
Keywords: Multivariate statistical quality control; Chi-square control chart; Average run length; Runs rules; 62N10 (search for similar items in EconPapers)
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