关键词: 电子封装, 异质互连, 随机有限元, 数据驱动

Abstract: Heterogeneous interconnect structures in electronic packaging are crucial technologies for chip miniaturization and functional integration. The numerical computation involves multi-source uncertainties, material and geometric nonlinearities, and multi-physics coupling. In recent years, stochastic finite element method (SFEM) numerical simulation has been widely used in electronic packaging, providing an effective tool for uncertainty quantification and reliability assessment. The modeling theory and numerical implementation methods of heterogeneous interconnect structures in electronic packaging under three types of uncertainties—geometric, material, and boundary conditions—are reviewed. To address multi-source stochasticity from structural dimensional deviations, morphological warpage, material property fluctuations, and operational perturbations, an integrated analysis framework combining multi-field coupled SFEM, data-driven SFEM, and Kriging surrogate modeling has been established. By integrating random variables and random fields into the thermo-mechanical-electrical coupling model, high-dimensional uncertainty propagation and statistical reliability assessment are realized, facilitating the transition from deterministic simulation to probabilistic analysis. The data-driven SFEM framework integrates experimental, standard, and simulation data to achieve regularization and distribution identification of multi-source uncertainty variables. The Kriging surrogate model simultaneously addresses prediction and uncertainty quantification in high-dimensional nonlinear responses. The research provides a scalable theoretical foundation and numerical support for the reliability design, lifetime prediction, and digital twin development of complex electronic packaging systems.

Key words: electronic packaging, heterogeneous interconnect, stochastic finite element method, data-driven