Demerit-GWMA control chart for Demerit statistics
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kang, Hae-woon | - |
dc.contributor.author | Kang,Changwook | - |
dc.contributor.author | Baik,Jae-won | - |
dc.contributor.author | Nam,Sungho | - |
dc.date.accessioned | 2021-06-23T12:03:49Z | - |
dc.date.available | 2021-06-23T12:03:49Z | - |
dc.date.created | 2021-01-22 | - |
dc.date.issued | 2011-11 | - |
dc.identifier.issn | 1022-6680 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/39096 | - |
dc.description.abstract | A classical Demerit control chart is used to monitor the process through which various types of defects in complex products, such as automobiles, computers, mobile phones, etc. are found in general. As a technique for rapidly detecting small shifts of the process mean in the control chart, the EWMA(exponentially weighted moving average) technique is very effective. This study suggested the Demerit-GWMA control chart, combining the GWMA(generally weighted moving average) technique, which shows better performance than EWMA technique in detecting small shifts of process mean, into the classical Demerit control chart, and evaluated its performance. Through the evaluation of its performance, it was found that the Demerit-GWMA control chart is more sensitive than both the classical Demerit control chart and the Demerit-EWMA control chart in detecting small shifts of process mean. © (2011) Trans Tech Publications. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Trans Tech | - |
dc.title | Demerit-GWMA control chart for Demerit statistics | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang,Changwook | - |
dc.identifier.doi | 10.4028/www.scientific.net/AMR.156-157.413 | - |
dc.identifier.scopusid | 2-s2.0-78650843208 | - |
dc.identifier.bibliographicCitation | Advanced Materials Research, v.156-157, pp.413 - 421 | - |
dc.relation.isPartOf | Advanced Materials Research | - |
dc.citation.title | Advanced Materials Research | - |
dc.citation.volume | 156-157 | - |
dc.citation.startPage | 413 | - |
dc.citation.endPage | 421 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 3 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | other | - |
dc.subject.keywordPlus | Control charts | - |
dc.subject.keywordPlus | Demerit | - |
dc.subject.keywordPlus | Exponentially weighted moving average | - |
dc.subject.keywordPlus | Moving averages | - |
dc.subject.keywordPlus | Statistical process control(SPC) | - |
dc.subject.keywordPlus | Flowcharting | - |
dc.subject.keywordPlus | Process monitoring | - |
dc.subject.keywordPlus | Quality control | - |
dc.subject.keywordPlus | Telecommunication equipment | - |
dc.subject.keywordPlus | Statistical process control | - |
dc.subject.keywordAuthor | Control chart | - |
dc.subject.keywordAuthor | Demerit | - |
dc.subject.keywordAuthor | Exponentially weighted moving average | - |
dc.subject.keywordAuthor | Generally weighted moving average | - |
dc.subject.keywordAuthor | Statistical process control(SPC) | - |
dc.identifier.url | https://www.scientific.net/AMR.156-157.413 | - |
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