Purpose The purpose of this paper is to optimize the power cycling stress and return loss of stacked ball grid array (BGA) solder joints using the Non-dominated Sorting Genetic Algorithm II (NSGA-II algorithm). The optimized design is suitable for high-reliability and high-frequency applications such as advanced electronic packaging in computing, communication and consumer electronics. Design/methodology/approach A finite element simulation model for stacked BGA solder joints was developed to analyze the stress–strain distribution under power cycling loads. Experimental samples were fabricated, and a power cycling strain measurement platform was established to carry out strain tests, thereby validating the accuracy of the simulation results. The variation in return loss of the stacked BGA solder joints under different frequency conditions was also investigated. Using solder ball diameter, solder joint height and pad diameter as design variables, a multi-objective optimization of power cycling-induced stress and return loss was conducted for the stacked BGA solder joints based on the response surface methodology and the NSGA-II algorithm. Findings The maximum stress and strain in stacked BGA solder joints occur in the region where the BT substrate connects to the upper solder joint. Prolonged stress concentration in this area can lead to the early initiation of cracks. Under high-frequency conditions, the return loss of stacked BGA solder joints increases with frequency. Excessive return loss can cause signal distortion, leading to circuit malfunction. After the multi-objective optimization, the maximum stress in the stacked BGA solder joints was reduced by 3.5%, while the return loss decreased by 2.78%, achieving simultaneous optimization of power cycling stress and return loss. Originality/value This paper provides a novel, dual-perspective optimization framework for enhancing both reliability and signal transmission in stacked BGA solder joints. The integration of response surface methodology, NSGA-II and entropy-weighted decision analysis offers a practical and accurate method for guiding structural design in complex electronic packaging. The proposed approach is of high value for reliability-critical applications such as aerospace, automotive and high-performance computing systems.
Liu et al. (Mon,) studied this question.