{"title":"随机振动环境下焊点疲劳寿命模型的全局不确定性分析","authors":"Ching-Yuan Kao, Mei-Ling Wu","doi":"10.1109/IMPACT.2011.6117285","DOIUrl":null,"url":null,"abstract":"The global model uncertainty analysis is to estimate the error due to input data approximations rather than sensitivities associated with finite element modeling. In this paper, estimates will be made on the amount of sensitivity in the global modeling which basically involves the sensitivity in the value of the material properties, input loadings, and geometries. Assume the model structure is corrected, how do we estimate a physics of failure (PoF) and predict time to failure or cycle to failure? Identifying an approach for quantifying the combination of input and uncertainty would enable the determination of more realistic confidence limits on Physics of Failure (PoF) predictions. The physics-of-failure (PoF) approach to reliability utilizes knowledge of the life-cycle load (thermal, vibration, mechanical, electrical, photonics, and so on) profile package architecture and material properties to identify potential failure mechanisms and to prevent operational failures through robust design and manufacturing practices. We can decompose the elements of any mathematical model into the physical parameters used in forming equations, such as material properties or geometric dimensions and the model structure, which results from simplifications, assumptions and approximations. Variability in the physical parameters can be addressed by existing stochastic methods, which are designed to propagate probability distributions on the parameters through a fixed model structure in order to estimate the statistics of interest on the model response quantities.","PeriodicalId":6360,"journal":{"name":"2011 6th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT)","volume":"38 1","pages":"482-484"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Global uncertainty analysis of solder joint fatigue life model in random vibration environment\",\"authors\":\"Ching-Yuan Kao, Mei-Ling Wu\",\"doi\":\"10.1109/IMPACT.2011.6117285\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The global model uncertainty analysis is to estimate the error due to input data approximations rather than sensitivities associated with finite element modeling. In this paper, estimates will be made on the amount of sensitivity in the global modeling which basically involves the sensitivity in the value of the material properties, input loadings, and geometries. Assume the model structure is corrected, how do we estimate a physics of failure (PoF) and predict time to failure or cycle to failure? Identifying an approach for quantifying the combination of input and uncertainty would enable the determination of more realistic confidence limits on Physics of Failure (PoF) predictions. The physics-of-failure (PoF) approach to reliability utilizes knowledge of the life-cycle load (thermal, vibration, mechanical, electrical, photonics, and so on) profile package architecture and material properties to identify potential failure mechanisms and to prevent operational failures through robust design and manufacturing practices. We can decompose the elements of any mathematical model into the physical parameters used in forming equations, such as material properties or geometric dimensions and the model structure, which results from simplifications, assumptions and approximations. Variability in the physical parameters can be addressed by existing stochastic methods, which are designed to propagate probability distributions on the parameters through a fixed model structure in order to estimate the statistics of interest on the model response quantities.\",\"PeriodicalId\":6360,\"journal\":{\"name\":\"2011 6th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT)\",\"volume\":\"38 1\",\"pages\":\"482-484\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 6th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMPACT.2011.6117285\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 6th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMPACT.2011.6117285","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Global uncertainty analysis of solder joint fatigue life model in random vibration environment
The global model uncertainty analysis is to estimate the error due to input data approximations rather than sensitivities associated with finite element modeling. In this paper, estimates will be made on the amount of sensitivity in the global modeling which basically involves the sensitivity in the value of the material properties, input loadings, and geometries. Assume the model structure is corrected, how do we estimate a physics of failure (PoF) and predict time to failure or cycle to failure? Identifying an approach for quantifying the combination of input and uncertainty would enable the determination of more realistic confidence limits on Physics of Failure (PoF) predictions. The physics-of-failure (PoF) approach to reliability utilizes knowledge of the life-cycle load (thermal, vibration, mechanical, electrical, photonics, and so on) profile package architecture and material properties to identify potential failure mechanisms and to prevent operational failures through robust design and manufacturing practices. We can decompose the elements of any mathematical model into the physical parameters used in forming equations, such as material properties or geometric dimensions and the model structure, which results from simplifications, assumptions and approximations. Variability in the physical parameters can be addressed by existing stochastic methods, which are designed to propagate probability distributions on the parameters through a fixed model structure in order to estimate the statistics of interest on the model response quantities.