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DD-plot for Detecting the Out-of-Control State in Multivariate Process

다변량공정에서 이상상태를 탐지하기 위한 DD-plot

  • Jang, Dae-Heung (Department of Statistics, Pukyong National University) ;
  • Yi, Seongbaek (Department of Statistics, Pukyong National University) ;
  • Kim, Youngil (Division of Management, Chung-Ang University)
  • Received : 2012.10.29
  • Accepted : 2013.03.20
  • Published : 2013.04.30

Abstract

It is well known that the DD-plot is a useful graphical tool for non-parametric classification. In this paper, we propose another use of DD-plot for detecting the out-of-control state in multivariate process. We suggested a dynamic version of DD-plot and its accompanying a quality index plot in such case.

DD-plot은 분류문제를 풀기 위한 유용한 비모수적 방법이다. 우리는 이러한 DD-plot을 다변량공정에서 이상상태를 탐지하기 위한 그래픽 방법으로 사용할 수 있다. 본 논문을 통하여 이상상태를 탐지하기 위한 그래픽 방법으로서 동적 DD-plot과 동적 품질지수그림을 제시하고자 한다.

Keywords

References

  1. Fuchs, C. and Kenett, R. (1998). Multivariate Quality Control with Industrial Applications, Marcel Dekker, New York.
  2. Li, J., Cuesta-Albertos, J. A. and Liu, R. (2012). DD-Classifier: Nonparametric classification procedure based on DD-plot, Journal of the American Statistical Association, 107, 737-753. https://doi.org/10.1080/01621459.2012.688462
  3. Liu, R. (1995). Control charts for multivariate processes, Journal of the American Statistical Association, 90, 1380-1387. https://doi.org/10.1080/01621459.1995.10476643
  4. Liu, R., Parelius, J. M. and Singh, K. (1999). Multivariate analysis by data depth: Descriptive statistics, graphics and inference, The Annals of Statistics, 27, 783-858.
  5. Liu, R. and Singh, K. (1993). A quality index based on data depth and multivariate rank tests, Journal of the American Statistical Association, 88, 252-260.
  6. Mason, R. L. and Young, J. C. (2002). Multivariate Statistical Process Control with Industrial Applications, ASA-SIAM, Philadelphia.
  7. Park, C. (2012). A resetting scheme for process parameters using the Mahalanobis-Taguchi system, The Korean Journal of Applied Statistics, 25, 589-603. https://doi.org/10.5351/KJAS.2012.25.4.589