{"title":"基于片上应力传感器的QFN封装板级剩余使用寿命预测","authors":"Daniel Riegel, P. Gromala, B. Han, S. Rzepka","doi":"10.1109/ECTC32696.2021.00150","DOIUrl":null,"url":null,"abstract":"Miniaturization of components and higher operating loads lead to reduced lifetimes. Prognostics and Health Management (PHM) enables predictive maintenance of components whose lifetime is shorter than that of the system they are part of. The key to PHM lies in sensor data that correlates with component degradation. In this study, run-to-failure data sets have been generated using in-situ measurements of on-chip stress sensors. Physical failure analysis has provided the link between the data and remaining useful life.","PeriodicalId":351817,"journal":{"name":"2021 IEEE 71st Electronic Components and Technology Conference (ECTC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Data-Driven Remaining Useful Life Prediction of QFN Packages on Board Level with On-Chip Stress Sensors\",\"authors\":\"Daniel Riegel, P. Gromala, B. Han, S. Rzepka\",\"doi\":\"10.1109/ECTC32696.2021.00150\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Miniaturization of components and higher operating loads lead to reduced lifetimes. Prognostics and Health Management (PHM) enables predictive maintenance of components whose lifetime is shorter than that of the system they are part of. The key to PHM lies in sensor data that correlates with component degradation. In this study, run-to-failure data sets have been generated using in-situ measurements of on-chip stress sensors. Physical failure analysis has provided the link between the data and remaining useful life.\",\"PeriodicalId\":351817,\"journal\":{\"name\":\"2021 IEEE 71st Electronic Components and Technology Conference (ECTC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 71st Electronic Components and Technology Conference (ECTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECTC32696.2021.00150\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 71st Electronic Components and Technology Conference (ECTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECTC32696.2021.00150","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data-Driven Remaining Useful Life Prediction of QFN Packages on Board Level with On-Chip Stress Sensors
Miniaturization of components and higher operating loads lead to reduced lifetimes. Prognostics and Health Management (PHM) enables predictive maintenance of components whose lifetime is shorter than that of the system they are part of. The key to PHM lies in sensor data that correlates with component degradation. In this study, run-to-failure data sets have been generated using in-situ measurements of on-chip stress sensors. Physical failure analysis has provided the link between the data and remaining useful life.
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