One-class classification-based control charts for multivariate process monitoring
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sukchotrat, Thuntee | - |
dc.contributor.author | Kim, Seoung Bum | - |
dc.contributor.author | Tsung, Fugee | - |
dc.date.accessioned | 2021-09-08T10:25:44Z | - |
dc.date.available | 2021-09-08T10:25:44Z | - |
dc.date.created | 2021-06-11 | - |
dc.date.issued | 2010 | - |
dc.identifier.issn | 0740-817X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/118668 | - |
dc.description.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. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | TAYLOR & FRANCIS INC | - |
dc.subject | SHIFTS | - |
dc.title | One-class classification-based control charts for multivariate process monitoring | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Seoung Bum | - |
dc.identifier.doi | 10.1080/07408170903019150 | - |
dc.identifier.scopusid | 2-s2.0-77649328220 | - |
dc.identifier.wosid | 000273919400002 | - |
dc.identifier.bibliographicCitation | IIE TRANSACTIONS, v.42, no.2, pp.107 - 120 | - |
dc.relation.isPartOf | IIE TRANSACTIONS | - |
dc.citation.title | IIE TRANSACTIONS | - |
dc.citation.volume | 42 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 107 | - |
dc.citation.endPage | 120 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Operations Research & Management Science | - |
dc.relation.journalWebOfScienceCategory | Engineering, Industrial | - |
dc.relation.journalWebOfScienceCategory | Operations Research & Management Science | - |
dc.subject.keywordPlus | SHIFTS | - |
dc.subject.keywordAuthor | Data mining | - |
dc.subject.keywordAuthor | Hotelling&apos | - |
dc.subject.keywordAuthor | s T-2 | - |
dc.subject.keywordAuthor | multivariate process | - |
dc.subject.keywordAuthor | one-class classification method | - |
dc.subject.keywordAuthor | statistical process control | - |
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