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 language | English |
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Pages | 846-850 |
Number of pages | 5 |
Publication status | Published - 2008 |
Externally published | Yes |
Event | IIE Annual Conference and Expo 2008 - Vancouver, BC, Canada Duration: 2008 May 17 → 2008 May 21 |
Other
Other | IIE Annual Conference and Expo 2008 |
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Country/Territory | Canada |
City | Vancouver, BC |
Period | 08/5/17 → 08/5/21 |
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