In this paper, we discuss lifetime prediction for flip chips under temperature and vibration loading in terms of the failure mechanisms related to solder joint fatigue. Our approach does not need additional data from the experiment but can be used in the design stage. For lifetime prediction solder fatigue coefficients from the literature and results from Finite Element Analysis (FEA) are processed by a MATLAB-routine. The predictions are compared to range of in-house experiments on combined loading. In the experimental setup, a statistically relevant number of specimens with single bump in-situ resistance monitoring are used to address the statistical scatter of the lifetime. Therefore, statements on the statistical distribution of solder joint failure in combined loading tests can be formulated. A laser vibrometer is used to determine exact accelerations and deflections of the Printed Circuit Board (PCB). In the failure analysis, ion-etched cross sections of the faile d solder bumps are prepared. The features of microstructural transformation and crack-paths are discussed for temperature cycling-only, vibration-only, and combined load experiments. Finally, the model prediction is compared to the experimentally determined solder joint lifetimes and the ranges of good agreement are discussed as well as the range with less agreement
In this paper we discuss the lifetime prediction for Pb-free soldered flip chip components under combined temperature cycling (TC) and vibration loading in terms of the failure mechanisms related to solder joint fatigue. We show the results of several experiments including failure analysis and comparison of lifetime models. For this purpose Finite Element Analyses (FEA) of the thermal cycling and vibration load are carried out and the relevant damage parameters are extracted from these simulations. The results are used in the lifetime models to correlate experimental and predictive results. Shortcomings of the existing life prediction approaches are discussed and ways to improve lifetime prediction are suggested.
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