Optimization of Vibration-Shock Responses of BGA Solder Joints under Complex Dynamic Loads

TIAN Zhengyang, ZHONG Yuan, ZHU Yixin, SU Yutai

Equipment Environmental Engineering ›› 2026, Vol. 23 ›› Issue (7) : 11-21.

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Equipment Environmental Engineering ›› 2026, Vol. 23 ›› Issue (7) : 11-21. DOI: 10.7643/issn.1672-9242.2026.07.002
Special Topic——Research on Application of Complex Dynamic Environment Analysis and Fine Adaptability Verification Technique for Precise Mother-Daughter UAV System

Optimization of Vibration-Shock Responses of BGA Solder Joints under Complex Dynamic Loads

  • TIAN Zhengyang1a, ZHONG Yuan2, ZHU Yixin1b, SU Yutai1a,*
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Abstract

The work aims to propose a vibration-shock response prediction and optimization method for BGA solder joint arrays to reduce the integrated critical response of the solder joint array under typical dynamic load cases, so as to address the problems of random-vibration-induced Mises stress concentration and shock-induced plastic strain accumulation in BGA solder joints of aircraft electronic assemblies under complex dynamic load environments. Driven by two load cases, random vibration and shock, a parametric model consisting of a PCB a 15×15 BGA solder joint array, and surrounding components was established. PCB thickness, solder joint stand-off height, solder joint diameter, pad diameter, and the x- and y-direction offsets of the BGA solder pad array were selected as design variables. A total of 300 samples were generated using Latin hypercube sampling. Random Mises stress was adopted for the random vibration case, while equivalent plastic strain was used to characterize the plastic response of solder joints under shock loading. A U-Net surrogate model for array responses was further constructed to rapidly predict the 15×15 solder joint array response field from structural parameters. Based on a reference design, the maximum random Mises stress under random vibration and the maximum equivalent plastic strain under shock loading were normalized, and a vibration-shock integrated objective function with equal weighting was formulated. The adaptive opposition-based spiral search algorithm was then employed for optimization. The finite element validation results showed that, after optimization, the maximum equivalent plastic strain of the BGA solder joint array under shock loading was reduced by 40.31%, the maximum random Mises stress under random vibration was reduced by 67.82%, and the integrated objective function was reduced by 54.07%. These results indicated that the optimized design could effectively improve the response level of the solder joint array under the two dynamic load cases. The proposed method enables rapid prediction and parameter optimization of vibration-shock responses of BGA solder joint arrays with limited simulation samples. It can effectively reduce the critical responses of solder joints under two typical dynamic load cases and provide a reference for environmental worthiness design and reliability analysis of aircraft electronic assemblies under complex dynamic load environments.

Key words

complex dynamic load / BGA solder joint / random vibration / shock response / equivalent Mises stress / equivalent plastic strain / U-Net surrogate model / response optimization

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TIAN Zhengyang, ZHONG Yuan, ZHU Yixin, SU Yutai. Optimization of Vibration-Shock Responses of BGA Solder Joints under Complex Dynamic Loads[J]. Equipment Environmental Engineering. 2026, 23(7): 11-21 https://doi.org/10.7643/issn.1672-9242.2026.07.002

References

[1] DEPIVER J A, MALLIK S, AMALU E H.Thermal Fatigue Life of Ball Grid Array (BGA) Solder Joints Made from Different Alloy Compositions[J]. Engineering Failure Analysis, 2021, 125: 105447.
[2] DEPIVER J A, MALLIK S, AMALU E H.Characterising Solder Materials from Random Vibration Response of Their Interconnects in BGA Packaging[J]. Journal of Electronic Materials, 2023, 52(7): 4655-4671.
[3] LEE J, JEONG H, JANG G.Optimization of the Boundary Conditions of a Board Level Reliability Test Board to Maximize the Fatigue Life of Ball Grid Array Solder Joints under Thermal Cycling and Random Vibration[J]. Materials, 2024, 17(3): 755.
[4] TIAN W C, LI F Y, HE M, et al.Reliability Analysis of Complex PCB Assemblies under Temperature Cycling and Random Vibration[J]. Micromachines, 2025, 16(2): 212.
[5] DEPIVER J A, MALLIK S, AMALU E H.Finite Element Comparative Study on Creep and Random Vibrations of Solder Joints in BGA Package[J]. Power Electronic Devices and Components, 2025, 11: 100085.
[6] XIAN J W, XU Y L, STOYANOV S, et al.The Role of Microstructure in the Thermal Fatigue of Solder Joints[J]. Nature Communications, 2024, 15: 4258.
[7] LI L, DU X Y, CHEN J B, et al.Thermal Fatigue Failure of Micro-Solder Joints in Electronic Packaging Devices: A Review[J]. Materials, 2024, 17(10): 2365.
[8] 何峥纬, 邵凤山, 华腾飞, 等. 基于Darveaux模型的BGA焊点寿命预测影响因素研究[J]. 微电子学与计算机, 2023, 40(11): 128-135.
HE Z W, SHAO F S, HUA T F, et al.Factors Influencing BGA Solder Joint Lifetime Prediction Based on the Darveaux Model[J]. Microelectronics & Computer, 2023, 40(11): 128-135.
[9] ABDEL RAZZAQ M, MEILUNAS M, CAO X A, et al.Thermal Fatigue Behaviors of BGA Packages with an Optimized Solder Joint Layout[J]. Electronics, 2025, 14(11): 2286.
[10] YUAN C, FAN X J, ZHANG G Q.Solder Joint Reliability Risk Estimation by AI-Assisted Simulation Framework with Genetic Algorithm to Optimize the Initial Parameters for AI Models[J]. Materials, 2021, 14(17): 4835.
[11] KUO H C, CHANG C Y, YUAN C, et al.Wafer-Level Packaging Solder Joint Reliability Lifecycle Prediction Using SVR-Based Machine Learning Algorithm[J]. Journal of Mechanics, 2023, 39(4): 183-190.
[12] SU Q H, YUAN C, CHIANG K N.A Small Database with an Adaptive Data Selection Method for Solder Joint Fatigue Life Prediction in Advanced Packaging[J]. Materials, 2024, 17(16): 4091.
[13] SU Q H, CHIANG K N.Multi-Algorithm Ensemble Learning Framework for Predicting the Solder Joint Reliability of Wafer-Level Packaging[J]. Materials, 2025, 18(17): 4074.
[14] AKHTAR M Z, SCHMID M, ELGER G.AI-Driven Point Cloud Framework for Predicting Solder Joint Reliability Using 3D FEA Data[J]. Scientific Reports, 2025, 15: 24340.
[15] QASAIMEH Q, LI H R, HAMASHA S, et al.A Machine Learning Framework with Shapley’s Additive Explanations to Assess Solder Joint Reliability for Electronic Packaging[J]. Journal of Electronic Materials, 2025, 54(9): 7586-7608.
[16] YANAMURTHY V N C, NATHI V K. A Machine Learning Approach for Evaluating Drop Impact Reliability of Solder Joints in BGA Packaging[J]. Applied Computer Science, 2025, 21(3): 59-71.
[17] REIHANISARANSARI R, SAMADIFAM F, SALA- MEH A A, et al. Reliability Characterization of Solder Joints in Electronic Systems through a Neural Network Aided Approach[J]. IEEE Access, 2022, 10: 123757-123768.
[18] YU Q L, NAWGHANE C, ZHANG Z H, et al.Application of Machine Learning Modeling for Predicting the Reliability of Solder Joints under Thermal Cycling[J]. Microelectronics Reliability, 2025, 174: 115900.
[19] ZIPPELIUS A, HANß A, SCHMID M, et al.Reliability Analysis and Condition Monitoring of SAC+ Solder Joints under High Thermomechanical Stress Conditions Using Neuronal Networks[J]. Microelectronics Reliability, 2022, 129: 114461.
[20] REBAI J, GHORBEL A, FEKI N, et al.Advanced Reliability Prediction of FBGA Solder Joints under Harmonic Vibration: Harnessing Supervised Machine Learning Models[J]. Journal of Electronic Materials, 2025, 54(11): 10386-10413.
[21] RONNEBERGER O, FISCHER P, BROX T.U-Net: Convolutional Networks for Biomedical Image Segmentation[C]//Medical Image Computing and Computer-Assisted Intervention. Cham: Springer, 2015: 234-241.
[22] TIZHOOSH H R.Opposition-Based Learning: A New Scheme for Machine Intelligence[C]//Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents. Vienna: IEEE, 2005.
[23] TAMURA K, YASUDA K.Spiral Dynamics Inspired Optimization[J]. Journal of Advanced Computational Intelligence and Intelligent Informatics, 2011, 15(8): 1116-1122.
[24] ZHANG B, LIU P K, DING H, et al.Modeling of Board-Level Package by Finite Element Analysis and Laser Interferometer Measurements[J]. Microelectronics Reliability, 2010, 50(7): 1021-1027.
[25] FEI Q, TONG A, NA C.Strain Rate Effect and Johnson-Cook Models of Lead-Free Solder Alloys[C]//Proceedings of 2008 International Conference on Electronic Packaging Technology & High Density Packaging. Shanghai: IEEE, 2008.

Funding

National Natural Science Foundation of China (52505158); Chuang Yuan High-level Innovation and Entrepreneurship Talent Project (QCYRCXM-2022-306); Xi'an Science and Technology Plan Project under the Key Core Technology Research Program (2026JH-GJHXG-0020)
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