Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Multivariate Control Charts for Autocorrelated Process

  • Cho, Gyo-Young (Department of Statistics, Kyungpook National University) ;
  • Park, Mi-Ra (Department of Statistics, Kyungpook National University)
  • Published : 2003.05.31
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Abstract

In this paper, we propose Shewhart control chart and EWMA control chart using the autocorrelated data which are common in chemical and process industries and lead to increase the number of false alarms when conventional control charts are applied. The effect of autocorrelated data is modeled as a autoregressive process, and canonical analysis is used to reduce the dimensionality of the data set and find the canonical variables that explain as much of the data variation as possible. Charting statistics are constructed based on the residual vectors from the canonical variables which are uncorrelated over time, and the control charts for these statistics can attenuate the autocorrelation in the process data. The charting procedures are illustrated with a numerical example and simulation is conducted to investigate the performances of the proposed control charts.

Keywords

References

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