M. Ruusunen, M. Paavola, Mika Pirttimaa, K. Leiviskä
{"title":"电子制造过程中三种变化检测算法的比较","authors":"M. Ruusunen, M. Paavola, Mika Pirttimaa, K. Leiviskä","doi":"10.1109/CIRA.2005.1554355","DOIUrl":null,"url":null,"abstract":"In a sequential manufacturing process, a product proceeds through different manufacturing stages. At these stages, sensors monitor the features of the product. In this paper, the information produced by the sensors is employed to detect abrupt changes in process variables. The developed algorithms contribute to an on-line application to a manufacturing system. A literature survey revealed the most common methods utilized in change detection. On-line applicability and transferability to new manufacturing lines are the most important features for real applications. During both on-line and off-line tests, some of the presented methods showed satisfactory results. Real-time, on-line manufacturing environment sets also its requirements for the applications. In the future, the possibility of combining expert knowledge with the aforementioned methods is the crucial point to study. The information thus received has usage in the preventive maintenance and quality control.","PeriodicalId":162553,"journal":{"name":"2005 International Symposium on Computational Intelligence in Robotics and Automation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Comparison of three change detection algorithms for an electronics manufacturing process\",\"authors\":\"M. Ruusunen, M. Paavola, Mika Pirttimaa, K. Leiviskä\",\"doi\":\"10.1109/CIRA.2005.1554355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a sequential manufacturing process, a product proceeds through different manufacturing stages. At these stages, sensors monitor the features of the product. In this paper, the information produced by the sensors is employed to detect abrupt changes in process variables. The developed algorithms contribute to an on-line application to a manufacturing system. A literature survey revealed the most common methods utilized in change detection. On-line applicability and transferability to new manufacturing lines are the most important features for real applications. During both on-line and off-line tests, some of the presented methods showed satisfactory results. Real-time, on-line manufacturing environment sets also its requirements for the applications. In the future, the possibility of combining expert knowledge with the aforementioned methods is the crucial point to study. The information thus received has usage in the preventive maintenance and quality control.\",\"PeriodicalId\":162553,\"journal\":{\"name\":\"2005 International Symposium on Computational Intelligence in Robotics and Automation\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 International Symposium on Computational Intelligence in Robotics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIRA.2005.1554355\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 International Symposium on Computational Intelligence in Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIRA.2005.1554355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of three change detection algorithms for an electronics manufacturing process
In a sequential manufacturing process, a product proceeds through different manufacturing stages. At these stages, sensors monitor the features of the product. In this paper, the information produced by the sensors is employed to detect abrupt changes in process variables. The developed algorithms contribute to an on-line application to a manufacturing system. A literature survey revealed the most common methods utilized in change detection. On-line applicability and transferability to new manufacturing lines are the most important features for real applications. During both on-line and off-line tests, some of the presented methods showed satisfactory results. Real-time, on-line manufacturing environment sets also its requirements for the applications. In the future, the possibility of combining expert knowledge with the aforementioned methods is the crucial point to study. The information thus received has usage in the preventive maintenance and quality control.