{"title":"多变量T2控制图中失控变量的AIC识别方法","authors":"Y. Takemoto, Rumi Tanaka, I. Arizono","doi":"10.1109/IWCIA.2013.6624780","DOIUrl":null,"url":null,"abstract":"The control chart is a primary tool of judging whether a manufacturing process is in-control or not. Especially, the T2 control chart is known as a multivariate control chart that monitors a mean vector of several related quality characteristics. It is an important issue to identify which quality characteristics are responsible for out-of-control signal when a multivariate control chart signals. This paper considers a method of identifying quality characteristics responsible for out-of-control signal on operating the T2 control chart.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Approach to identifying out-of-control variables in multivariate T2 control chart using AIC\",\"authors\":\"Y. Takemoto, Rumi Tanaka, I. Arizono\",\"doi\":\"10.1109/IWCIA.2013.6624780\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The control chart is a primary tool of judging whether a manufacturing process is in-control or not. Especially, the T2 control chart is known as a multivariate control chart that monitors a mean vector of several related quality characteristics. It is an important issue to identify which quality characteristics are responsible for out-of-control signal when a multivariate control chart signals. This paper considers a method of identifying quality characteristics responsible for out-of-control signal on operating the T2 control chart.\",\"PeriodicalId\":257474,\"journal\":{\"name\":\"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWCIA.2013.6624780\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWCIA.2013.6624780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Approach to identifying out-of-control variables in multivariate T2 control chart using AIC
The control chart is a primary tool of judging whether a manufacturing process is in-control or not. Especially, the T2 control chart is known as a multivariate control chart that monitors a mean vector of several related quality characteristics. It is an important issue to identify which quality characteristics are responsible for out-of-control signal when a multivariate control chart signals. This paper considers a method of identifying quality characteristics responsible for out-of-control signal on operating the T2 control chart.