Thermal Fatigue Life and Reliability Evaluation of Die Attachment Layer of High-Power LED under Thermal Cycling Conditions

碩士 === 國立臺灣大學 === 機械工程學研究所 === 101 === Power conservation is a very important aspect of modern day technology, and with its long life and low energy consumption, the High Power Light Emitting Diode has become very popular for lighting purposes. Thermal management plays a key role in the reliability...

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Bibliographic Details
Main Authors: Shih-Lin Lai, 賴世霖
Other Authors: Wen-Fang Wu
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/76285349863979589743
Description
Summary:碩士 === 國立臺灣大學 === 機械工程學研究所 === 101 === Power conservation is a very important aspect of modern day technology, and with its long life and low energy consumption, the High Power Light Emitting Diode has become very popular for lighting purposes. Thermal management plays a key role in the reliability of high power LEDs, which is essential for all of its applications. The die-attach layer is a important component of an HP LED package, not only does it hold the chip in place, it also provides the main path for heat dissipation in the structure. However, it is also susceptible to thermal fatigue failure, affecting the reliability of the HP LED itself. Seldom people discuss this issue. This study uses Finite Element Method to simulate and analyze the mechanical behavior of an HP LED die-attach layer under thermal cycling conditions, using the numerical results as the input for the Coffin-Manson relationship the predict its fatigue life. It is worth noting that past studies are mostly limited to finding a fixed value for the fatigue life of the package, which cannot truly reflect the discrete qualities of real life testing. Furthermore, they cannot provide vital information such as MTTF and the Hazard Rate of the HP LED. With this in mind, this study consider uncertainties of both geometric dimension and material properties of the die attachment layer, regarding them as random variables, which can be simulated by the Monte-Carlo method. The sampled data is then applied to the FEM analysis to evaluate its fatigue life, which can lead to the probability distribution of fatigue life by using the Anderson-Darling Test and probability plot to find the relevant variables. We can then obtain information such as the MTTF and failure rate function using this distribution.