SMTA International Conference Proceedings


THERMO-MECHANICAL RELIABILITY MANAGEMENT MODELS FOR AREA-ARRAY PACKAGES ON CU-CORE AND NO-CORE ASSEMBLIES

Authors: Pradeep Lall, Milan Shah, Luke Drake, Timothy Moore, Jeff Suhling
Company: Auburn University and Northrop Grumman Corporation
Date Published: 10/11/2007   Conference: SMTA International


Abstract: In this work, thermo-mechanical models for reliability prediction of BGA package interconnects mounted on integral copper-core (CU-CORE) and no integral copper core (NO-CORE) printed circuit assemblies in harsh environments have been developed. The models have been developed based on thermo-mechanical reliability data acquired on CU-CORE and NO-CORE assemblies in four different thermal cycling conditions. Solder alloys examined include SnPb and SAC alloys. The models presented in this paper provide decision 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 (MLR), 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 paper, 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 FEAbased model sensitivities with experimental data has been demonstrated. Validation of model predictions with accelerated test data is presented.

Keywords: Ball grid array (BGA), design guidelines, solder joint fatigue, statistical model, thermal reliability prediction, Finite element models.



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