|In this work, thermo-mechanical models for reliability prediction of BGA packages mounted on Cu-core printed circuit assemblies in harsh environments have been developed. The models have been developed based on thermo-mechanical reliability data acquired on copper-core assemblies in four different thermal cycling conditions. Solder alloys examined include SnPb and SAC alloys. The models presented in this paper provide decisions guidance for smart selection of component packaging technologies and perturbing product designs for minimal risk insertion of new packaging technologies. In addition, qualitative parameter interaction effects, which are often ignored in closed-form modeling, have been incorporated in this work.
Multivariate linear regression and non-linear finite element models have been developed for prediction of geometry and material effects. MLR approach uses the potentially important variables from stepwise regression. The statistics models are based on accelerated test data acquired as part of this thesis, in harsh environments, while finite-element models are based on damage mechanics and material constitutive behavior. Sensitivity relations for geometry, materials, and architectures based on statistical models, and FEA models have been developed. Convergence of statistical, failure mechanics, and FEA based model sensitivities with experimental data has been demonstrated. Validation of model predictions with accelerated test data has been presented.