Waqar Hafeez, Jianguo Du, Zameer Abbas, Hafiz Zafar Nazir
{"title":"一种改进的泊松EWMA控制图,用于监控不合格件","authors":"Waqar Hafeez, Jianguo Du, Zameer Abbas, Hafiz Zafar Nazir","doi":"10.1007/s40995-024-01732-7","DOIUrl":null,"url":null,"abstract":"<div><p>Poisson control charts are most frequently used to track the number of nonconformities per unit in industrial processes during the inspection. As the quality characteristic under examination is based on a nominal scale rather than a quantitative or measured scale, these charting structures are known as attribute control charts. To detect small changes quickly, a Poisson extended exponentially weighted moving average (PEEWMA) control chart is developed in this study and its performance in zero-state and steady-state conditions has been examined. Run-length (RL) profiles, such as the average RL, the standard deviation of RL, and several percentile points of the RL distribution, have been evaluated using Monte Carlo simulation. The RL profiles of the proposed PEEWMA chart have been compared with existing methods. The comparison shows that the suggested PEEWMA chart outperforms its competitors. The application of the proposed design from an artificial dataset has also been included.</p></div>","PeriodicalId":600,"journal":{"name":"Iranian Journal of Science and Technology, Transactions A: Science","volume":"49 2","pages":"427 - 438"},"PeriodicalIF":1.4000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Improved Poisson EWMA Control Chart for Monitoring Nonconformities Per Unit\",\"authors\":\"Waqar Hafeez, Jianguo Du, Zameer Abbas, Hafiz Zafar Nazir\",\"doi\":\"10.1007/s40995-024-01732-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Poisson control charts are most frequently used to track the number of nonconformities per unit in industrial processes during the inspection. As the quality characteristic under examination is based on a nominal scale rather than a quantitative or measured scale, these charting structures are known as attribute control charts. To detect small changes quickly, a Poisson extended exponentially weighted moving average (PEEWMA) control chart is developed in this study and its performance in zero-state and steady-state conditions has been examined. Run-length (RL) profiles, such as the average RL, the standard deviation of RL, and several percentile points of the RL distribution, have been evaluated using Monte Carlo simulation. The RL profiles of the proposed PEEWMA chart have been compared with existing methods. The comparison shows that the suggested PEEWMA chart outperforms its competitors. The application of the proposed design from an artificial dataset has also been included.</p></div>\",\"PeriodicalId\":600,\"journal\":{\"name\":\"Iranian Journal of Science and Technology, Transactions A: Science\",\"volume\":\"49 2\",\"pages\":\"427 - 438\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Iranian Journal of Science and Technology, Transactions A: Science\",\"FirstCategoryId\":\"4\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s40995-024-01732-7\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Science and Technology, Transactions A: Science","FirstCategoryId":"4","ListUrlMain":"https://link.springer.com/article/10.1007/s40995-024-01732-7","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
An Improved Poisson EWMA Control Chart for Monitoring Nonconformities Per Unit
Poisson control charts are most frequently used to track the number of nonconformities per unit in industrial processes during the inspection. As the quality characteristic under examination is based on a nominal scale rather than a quantitative or measured scale, these charting structures are known as attribute control charts. To detect small changes quickly, a Poisson extended exponentially weighted moving average (PEEWMA) control chart is developed in this study and its performance in zero-state and steady-state conditions has been examined. Run-length (RL) profiles, such as the average RL, the standard deviation of RL, and several percentile points of the RL distribution, have been evaluated using Monte Carlo simulation. The RL profiles of the proposed PEEWMA chart have been compared with existing methods. The comparison shows that the suggested PEEWMA chart outperforms its competitors. The application of the proposed design from an artificial dataset has also been included.
期刊介绍:
The aim of this journal is to foster the growth of scientific research among Iranian scientists and to provide a medium which brings the fruits of their research to the attention of the world’s scientific community. The journal publishes original research findings – which may be theoretical, experimental or both - reviews, techniques, and comments spanning all subjects in the field of basic sciences, including Physics, Chemistry, Mathematics, Statistics, Biology and Earth Sciences