One-class classification-based control charts for multivariate process monitoring

Thuntee Sukchotrat, Seoung Bum Kim, Fugee Tsung

Research output: Contribution to journalArticlepeer-review

87 Citations (Scopus)


One-class classification problems have attracted a great deal of attention from various disciplines. In the present study, attempts are made to extend the scope of application of the one-class classification technique to Statistical Process Control (SPC) problems. New multivariate control charts that apply the effectiveness of one-class classification to improvement of Phase I and Phase II analysis in SPC are proposed. These charts use a monitoring statistic to represent the degree of being an outlier as obtained through one-class classification. The control limits of the proposed charts are established based on the empirical level of significance on the percentile, estimated by the bootstrap method. A simulation study is conducted to illustrate the limitations of current one-class classification control charts and demonstrate the effectiveness of the proposed control charts.

Original languageEnglish
Pages (from-to)107-120
Number of pages14
JournalIIE Transactions (Institute of Industrial Engineers)
Issue number2
Publication statusPublished - 2010 Feb


  • Data mining
  • Hotelling's T
  • Multivariate process
  • One-class classification method
  • Statistical process control

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering


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