{"title":"泊松计数综合控制图","authors":"Christian H. Weiß","doi":"10.1016/j.cie.2024.110615","DOIUrl":null,"url":null,"abstract":"<div><div>Traditional control charts for Poisson counts are tailor-made for detecting changes in the process mean while assuming that the Poisson assumption is not violated. But if the mean changes together with the distribution family, the performance of these charts may deviate considerably from the expected out-of-control behavior. In this research, omnibus control charts for Poisson counts are developed, which are sensitive to a broad variety of process changes (“all-rounders”). This is achieved by adapting common omnibus goodness-of-fit (GoF) tests to process monitoring. More precisely, different GoF-tests based on the probability generating function (pgf) are combined with an exponentially weighted moving-average (EWMA) approach in various ways. A comprehensive simulation study leads to clear design recommendations on how to achieve the desired omnibus property. The practical benefits of the proposed omnibus EWMA charts are demonstrated with several real-world data examples.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110615"},"PeriodicalIF":6.7000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Omnibus control charts for Poisson counts\",\"authors\":\"Christian H. Weiß\",\"doi\":\"10.1016/j.cie.2024.110615\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Traditional control charts for Poisson counts are tailor-made for detecting changes in the process mean while assuming that the Poisson assumption is not violated. But if the mean changes together with the distribution family, the performance of these charts may deviate considerably from the expected out-of-control behavior. In this research, omnibus control charts for Poisson counts are developed, which are sensitive to a broad variety of process changes (“all-rounders”). This is achieved by adapting common omnibus goodness-of-fit (GoF) tests to process monitoring. More precisely, different GoF-tests based on the probability generating function (pgf) are combined with an exponentially weighted moving-average (EWMA) approach in various ways. A comprehensive simulation study leads to clear design recommendations on how to achieve the desired omnibus property. The practical benefits of the proposed omnibus EWMA charts are demonstrated with several real-world data examples.</div></div>\",\"PeriodicalId\":55220,\"journal\":{\"name\":\"Computers & Industrial Engineering\",\"volume\":\"198 \",\"pages\":\"Article 110615\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2024-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Industrial Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S036083522400737X\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Industrial Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S036083522400737X","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Traditional control charts for Poisson counts are tailor-made for detecting changes in the process mean while assuming that the Poisson assumption is not violated. But if the mean changes together with the distribution family, the performance of these charts may deviate considerably from the expected out-of-control behavior. In this research, omnibus control charts for Poisson counts are developed, which are sensitive to a broad variety of process changes (“all-rounders”). This is achieved by adapting common omnibus goodness-of-fit (GoF) tests to process monitoring. More precisely, different GoF-tests based on the probability generating function (pgf) are combined with an exponentially weighted moving-average (EWMA) approach in various ways. A comprehensive simulation study leads to clear design recommendations on how to achieve the desired omnibus property. The practical benefits of the proposed omnibus EWMA charts are demonstrated with several real-world data examples.
期刊介绍:
Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.