One-class classification techniques for improving phase I analysis in statistical process control

Thuntee Sukchotrat, Seoung Bum Kim

Research output: Contribution to conferencePaper

Abstract

We propose to use a one-class classification technique to improve phase I analysis in statistical process control. Phase I analysis attempts to isolate the in-control data from the historical data, usually unlabelled to construct the reliable control charts. A traditional phase I method recursively removes the observations, which exceed the control limits until no out-of-control observations are detected. This recursive method requires a distributional assumption because the control limits are determined based on a certain parametric distribution. The proposed oneclassification technique does not require such distributional assumption. The effectiveness of the proposed approach is demonstrated through the simulated data set.

Original languageEnglish
Pages846-850
Number of pages5
Publication statusPublished - 2008
EventIIE Annual Conference and Expo 2008 - Vancouver, BC, Canada
Duration: 2008 May 172008 May 21

Other

OtherIIE Annual Conference and Expo 2008
CountryCanada
CityVancouver, BC
Period08/5/1708/5/21

Keywords

  • Data mining
  • Multivariate statistical process control
  • One-class classification
  • Phase I analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Industrial and Manufacturing Engineering

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  • Cite this

    Sukchotrat, T., & Kim, S. B. (2008). One-class classification techniques for improving phase I analysis in statistical process control. 846-850. Paper presented at IIE Annual Conference and Expo 2008, Vancouver, BC, Canada.