FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385994645> ?p ?o ?g. }

• W4385994645 endingPage "17" @default.
• W4385994645 startingPage "1" @default.
• W4385994645 abstract "ABSTRACTConventional statistical process control tools monitor either continuous or count data but rarely both simultaneously. While process data are becoming increasingly complex, there will be more data points containing both continuous and count information. In the case of mixed continuous and count data with unknown distributions, the traditional parameter control chart cannot be used to monitor them. It is proposed in this paper a novel nonparametric EWMA control chart to monitor mixed continuous and count data. The mixed continuous and count data are first transformed into categorical data, and then a log-linear model is utilized to analyze correlations between variables, followed by the construction of an EWMA statistic that is used to monitor mixed continuous and count data. Next, the proposed control chart is compared with several improved control charts for monitoring mixed continuous and count data. Based on the numerical simulation results, the control chart presented in this paper provides a superior method of detecting alarm signals in the process compared to some improved control charts. Finally, the proposed control chart is demonstrated to be effective and applicable using the semiconductor manufacturing process dataset from the UC Irvine Machine Learning Repository.KEYWORDS: Statistical process controlcontinuous and count datamixed datalog-linear modelnonparametric control chart AcknowledgementThe authors are very grateful to the editor and reviewers for their valuable and constructive comments and suggestions, which greatly improved the final version of this paper.Disclosure statementNo potential conflict of interest was reported by the author(s).Correction StatementThis article has been corrected with minor changes. These changes do not impact the academic content of the article.Additional informationFundingThe work was supported by the National Natural Science Foundation of China Grant (No. 71701188, No. 71902138, No. 72261147706, No. 71871204, No. 72231005), Humanities and Social Sciences Research Program of the Ministry of Education of China Grant (No.21YJC630151), Natural Science Foundation of Henan Province under Grant (No. 232300420125), Scientific Research Team Plan of Zhengzhou University of Aeronautics (No. 23ZHTD01008), Graduate Education Innovation Program Foundation of Zhengzhou University of Aeronuatics under Grant(No.2022CX18).Notes on contributorsLi XueLi Xue is a full Professor and Associate Dean of the School of Management Engineering at the Zhengzhou University of Aeronautics, China. Her major research areas include quality control and management, and big data analytics. She has published over 40 papers in these areas, and her research has been well supported by grants from the National Science Foundation of China, Aeronautic Science Foundation of China, and other grant agencies.Qiuyu WangQiuyu Wang is a master's student of the School of Management Engineering at the Zhengzhou University of Aeronautics, China, currently studying in the School of Management Engineering. Her major research areas include quality control and management.Zhen HeZhen He is a full professor in the College of Management and Economics at Tianjin University, China. He received his PhD degree from Tianjin University in 2000. His research interests include quality engineering, six sigma, industrial engineering, and operations management. So far, he has published over 100 research papers, many of which appeared in top journals.Peihua QiuPeihua Qiu is Professor and Founding Chair of the Department of Biostatistics at the University of Florida. He is an elected fellow of the American Statistical Association, an elected fellow of the Institute of Mathematical Statistics, and an elected member of the International Statistical Institute. He was the editor of Technometrics and served as associate editor for a number of top journals, including the Journal of the American Statistical Association, Biometrics, and Technometrics. He has made substantial contributions in several research areas, including jump regression analysis, image processing, statistical process control, survival analysis, and disease screening and surveillance. So far, he has published over 125 research papers, many of which appeared in top journals." @default.
• W4385994645 created "2023-08-19" @default.
• W4385994645 creator A5033684035 @default.
• W4385994645 creator A5058863622 @default.
• W4385994645 creator A5067911307 @default.
• W4385994645 creator A5070630688 @default.
• W4385994645 date "2023-08-17" @default.
• W4385994645 modified "2023-10-05" @default.
• W4385994645 title "A nonparametric EWMA control chart for monitoring mixed continuous and count data" @default.
• W4385994645 cites W1965328677 @default.
• W4385994645 cites W1969474438 @default.
• W4385994645 cites W1984787157 @default.
• W4385994645 cites W2019110314 @default.
• W4385994645 cites W2028705130 @default.
• W4385994645 cites W2074013991 @default.
• W4385994645 cites W2076983043 @default.
• W4385994645 cites W2099186606 @default.
• W4385994645 cites W2114189440 @default.
• W4385994645 cites W2124573682 @default.
• W4385994645 cites W2128018347 @default.
• W4385994645 cites W2336182703 @default.
• W4385994645 cites W2550714578 @default.
• W4385994645 cites W2885093228 @default.
• W4385994645 cites W2894694938 @default.
• W4385994645 cites W2907729428 @default.
• W4385994645 cites W2913453442 @default.
• W4385994645 cites W2921245983 @default.
• W4385994645 cites W2926367560 @default.
• W4385994645 cites W2998396714 @default.
• W4385994645 cites W3008345529 @default.
• W4385994645 cites W3037530597 @default.
• W4385994645 cites W3174160774 @default.
• W4385994645 cites W3189332852 @default.
• W4385994645 cites W3196636555 @default.
• W4385994645 cites W3197093407 @default.
• W4385994645 cites W3197835565 @default.
• W4385994645 cites W4214624756 @default.
• W4385994645 cites W4220870362 @default.
• W4385994645 cites W4220971274 @default.
• W4385994645 cites W4225622461 @default.
• W4385994645 cites W4244024201 @default.
• W4385994645 cites W4254698769 @default.
• W4385994645 cites W4292623963 @default.
• W4385994645 doi "https://doi.org/10.1080/16843703.2023.2246765" @default.
• W4385994645 hasPublicationYear "2023" @default.
• W4385994645 type Work @default.
• W4385994645 citedByCount "0" @default.
• W4385994645 crossrefType "journal-article" @default.
• W4385994645 hasAuthorship W4385994645A5033684035 @default.
• W4385994645 hasAuthorship W4385994645A5058863622 @default.
• W4385994645 hasAuthorship W4385994645A5067911307 @default.
• W4385994645 hasAuthorship W4385994645A5070630688 @default.
• W4385994645 hasConcept C100906024 @default.
• W4385994645 hasConcept C105795698 @default.
• W4385994645 hasConcept C111919701 @default.
• W4385994645 hasConcept C113644684 @default.
• W4385994645 hasConcept C124101348 @default.
• W4385994645 hasConcept C159848633 @default.
• W4385994645 hasConcept C190812933 @default.
• W4385994645 hasConcept C196985124 @default.
• W4385994645 hasConcept C33643355 @default.
• W4385994645 hasConcept C33923547 @default.
• W4385994645 hasConcept C41008148 @default.
• W4385994645 hasConcept C5274069 @default.
• W4385994645 hasConcept C74746147 @default.
• W4385994645 hasConcept C98045186 @default.
• W4385994645 hasConceptScore W4385994645C100906024 @default.
• W4385994645 hasConceptScore W4385994645C105795698 @default.
• W4385994645 hasConceptScore W4385994645C111919701 @default.
• W4385994645 hasConceptScore W4385994645C113644684 @default.
• W4385994645 hasConceptScore W4385994645C124101348 @default.
• W4385994645 hasConceptScore W4385994645C159848633 @default.
• W4385994645 hasConceptScore W4385994645C190812933 @default.
• W4385994645 hasConceptScore W4385994645C196985124 @default.
• W4385994645 hasConceptScore W4385994645C33643355 @default.
• W4385994645 hasConceptScore W4385994645C33923547 @default.
• W4385994645 hasConceptScore W4385994645C41008148 @default.
• W4385994645 hasConceptScore W4385994645C5274069 @default.
• W4385994645 hasConceptScore W4385994645C74746147 @default.
• W4385994645 hasConceptScore W4385994645C98045186 @default.
• W4385994645 hasLocation W43859946451 @default.
• W4385994645 hasOpenAccess W4385994645 @default.
• W4385994645 hasPrimaryLocation W43859946451 @default.
• W4385994645 hasRelatedWork W1544415648 @default.
• W4385994645 hasRelatedWork W2037626511 @default.
• W4385994645 hasRelatedWork W2077448518 @default.
• W4385994645 hasRelatedWork W2213954818 @default.
• W4385994645 hasRelatedWork W2931607628 @default.
• W4385994645 hasRelatedWork W3200938883 @default.
• W4385994645 hasRelatedWork W3201688424 @default.
• W4385994645 hasRelatedWork W4214540154 @default.
• W4385994645 hasRelatedWork W4380027713 @default.
• W4385994645 hasRelatedWork W4381431108 @default.
• W4385994645 isParatext "false" @default.
• W4385994645 isRetracted "false" @default.
• W4385994645 workType "article" @default.