A self-starting control chart for high-dimensional short-run processes

Yanting Li*, Yukun Liu, Changliang Zou, Wei Jiang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

A key challenge in using a traditional Hotellings chart with high-dimensionality measurements is that monitoring cannot begin until after the number of observations exceeds the dimensionality of the measurements, and the detection sensitivity to early shifts is reduced after that point until a substantial amount of observations has been accumulated. This is especially important with short-run processes where the measurements have high dimensionality. This article proposes a chart that allows monitoring with the second observation regardless of the dimensionality and reduces the average run length in detecting early shifts in high-dimensionality measurements. The proposed control chart can start monitoring quite early before considerable reference data are collected during the initial stage of production. A change point estimate is also available from our procedure, which is shown consistent for locating the correct change point. Both simulation results and an industry example show the effectiveness of the proposed control chart for monitoring short-run processes with high dimensionality.

Original languageEnglish
Pages (from-to)445-461
Number of pages17
JournalInternational Journal of Production Research
Volume52
Issue number2
DOIs
StatePublished - 17 Jan 2014

Keywords

  • average run length
  • control chart
  • high-dimensional observations
  • mean shift
  • short-run processes

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