{"title":"介绍了用于半导体湿清洗设备优化和实时故障检测的设备级FDC系统","authors":"Namjin Kim, Hojin Choi, J. Chun, Jongpil Jeong","doi":"10.1109/asmc54647.2022.9792476","DOIUrl":null,"url":null,"abstract":"The proposed paper presents an equipment level FDC system for the optimization and anomaly detection of semiconductor equipment. Through the equipment level FDC(Fault Detection and Classification) system, various data in the equipment can be converted into meaningful and accurate analysis data through context mapping to facilitate analysis of the management and condition of the equipment. In addition, it is possible to proactively identify and respond to problems at the equipment level before identifying and responding to problems on the host by processing data of diverse equipment in real time.","PeriodicalId":436890,"journal":{"name":"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)","volume":"17 S20","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Introduction of equipment level FDC system for semiconductor wet-cleaning equipment optimization and real-time fault detection\",\"authors\":\"Namjin Kim, Hojin Choi, J. Chun, Jongpil Jeong\",\"doi\":\"10.1109/asmc54647.2022.9792476\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proposed paper presents an equipment level FDC system for the optimization and anomaly detection of semiconductor equipment. Through the equipment level FDC(Fault Detection and Classification) system, various data in the equipment can be converted into meaningful and accurate analysis data through context mapping to facilitate analysis of the management and condition of the equipment. In addition, it is possible to proactively identify and respond to problems at the equipment level before identifying and responding to problems on the host by processing data of diverse equipment in real time.\",\"PeriodicalId\":436890,\"journal\":{\"name\":\"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)\",\"volume\":\"17 S20\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/asmc54647.2022.9792476\",\"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/asmc54647.2022.9792476","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
提出了一种用于半导体设备优化和异常检测的设备级FDC系统。通过设备级FDC(Fault Detection and Classification,故障检测与分类)系统,可以将设备中的各种数据通过上下文映射转换为有意义、准确的分析数据,便于对设备的管理和状态进行分析。此外,通过实时处理各种设备的数据,可以在主机上发现问题并做出响应之前,在设备层面主动发现问题并做出响应。
Introduction of equipment level FDC system for semiconductor wet-cleaning equipment optimization and real-time fault detection
The proposed paper presents an equipment level FDC system for the optimization and anomaly detection of semiconductor equipment. Through the equipment level FDC(Fault Detection and Classification) system, various data in the equipment can be converted into meaningful and accurate analysis data through context mapping to facilitate analysis of the management and condition of the equipment. In addition, it is possible to proactively identify and respond to problems at the equipment level before identifying and responding to problems on the host by processing data of diverse equipment in real time.