Reliability prediction and design optimization of BGA solder joint based on multi-fidelity surrogate model

At present, the reliability prediction of solder joints is mostly based on the combination of finite element simulation and single precision surrogate model, which has some problems such as long simulation time, low efficiency and poor accuracy. Therefore, a reliability prediction method for BGA (ball grid array) solder joints based on multi-fidelity model is proposed. Firstly, the convergence of different meshing schemes was verified, and then the high and low precision sample points were designed respectively for finite element analysis (FEA). Secondly, the reliability of solder joints was predicted based on the Co-Kriging model based on multi fidelity FEA data. Finally, the prediction results were compared with the single precision surrogate model, Under the same cost constraints, the multi-fidelity model demonstrates significantly higher prediction accuracy. and NSGA(nondominated sorting genetic algorithm) was used to optimize the model to obtain the corresponding process parameters. The results show that with less simulation cost, the prediction result of multi-fidelity model is better. Under the same prediction accuracy, the number of high-precision sample points of the variable reliability model is only 1/4 of that of the single precision model. At the same time, compared with the neural network prediction model, it converges faster in the optimization process. This paper provides some reference for the research of reliability prediction of solder joint with multi-fidelity model.