{"title":"实时真空检漏技术计算干汽提真空检漏参数:EO:设备优化","authors":"J. Jeong, Taekyung Ha, Hyojeong Ji, S. J. Yoon","doi":"10.1109/asmc54647.2022.9792477","DOIUrl":null,"url":null,"abstract":"In semiconductor manufacturing, vacuum leakage occurring during wafer processing decreases productivity. Conventionally, the equipment is stopped to detect the vacuum leaks. However, this adversely affects productivity. We presents a real-time vacuum leak detection technique. We successfully identified vacuum leakage in real time by interpolating from the dry strip process parameters.","PeriodicalId":436890,"journal":{"name":"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-time vacuum leak detection technology to calculate vacuum leak parameters for dry stripping : EO: Equipment Optimization\",\"authors\":\"J. Jeong, Taekyung Ha, Hyojeong Ji, S. J. Yoon\",\"doi\":\"10.1109/asmc54647.2022.9792477\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In semiconductor manufacturing, vacuum leakage occurring during wafer processing decreases productivity. Conventionally, the equipment is stopped to detect the vacuum leaks. However, this adversely affects productivity. We presents a real-time vacuum leak detection technique. We successfully identified vacuum leakage in real time by interpolating from the dry strip process parameters.\",\"PeriodicalId\":436890,\"journal\":{\"name\":\"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/asmc54647.2022.9792477\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/asmc54647.2022.9792477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time vacuum leak detection technology to calculate vacuum leak parameters for dry stripping : EO: Equipment Optimization
In semiconductor manufacturing, vacuum leakage occurring during wafer processing decreases productivity. Conventionally, the equipment is stopped to detect the vacuum leaks. However, this adversely affects productivity. We presents a real-time vacuum leak detection technique. We successfully identified vacuum leakage in real time by interpolating from the dry strip process parameters.