A study of multivariate pre-control charts

J. N. Pan

研究成果: Article同行評審

10 引文 斯高帕斯(Scopus)


The quality of the output of a production process is often measured by the joint level of several correlated characteristics. Through multivariate control charts, one will be able to detect a process change and prevent defects from occurring by identifying and eliminating assignable causes of variation. In contrast to the traditional control charts, pre-control charts focus on evaluating the process capability during the set-up stage and detecting the process change during the mass production stage. However, the set-up and monitoring rules as well as the sample size for multivariate pre-control charts have not been thoroughly studied (to our knowledge). The main purpose of this research is to develop these rules and compare the performances of detecting a process change using multivariate pre-control charts versus Hotelling T2 control charts when the quality characteristics follow a multivariate normal distribution. These objectives can be achieved by two statistical measures known as the in-control and out-of-control average run lengths (ARLs). The simulation results and a numerical example further demonstrate the usefulness of the new set-up and monitoring rules we proposed for multivariate pre-control charts.

頁(從 - 到)160-170
期刊International Journal of Production Economics
出版狀態Published - 2007 1月

All Science Journal Classification (ASJC) codes

  • 商業、管理和會計 (全部)
  • 經濟學與計量經濟學
  • 管理科學與經營研究
  • 工業與製造工程


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