Abstract
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 language | English |
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Pages (from-to) | 107-120 |
Number of pages | 14 |
Journal | IIE Transactions (Institute of Industrial Engineers) |
Volume | 42 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2010 Feb |
Keywords
- Data mining
- Hotelling's T
- Multivariate process
- One-class classification method
- Statistical process control
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering