The semiconductor industry is experiencing significant growth in production scale and investment, driven by rising demand for generative AI, high-performance computing (HPC), high-bandwidth memory (HBM), and high-performance/high-density chips. As a result, precision inspection and yield management at the wafer stage have become critical challenges. Probe cards, essential for verifying a chip's electrical performance, play a vital role in yield management. However, during repetitive inspection processes, probe cards absorb heat from the underlying chuck, leading to probe tip-pad alignment errors that degrade contact reliability and measurement accuracy. This situation necessitates a quantitative evaluation system based on thermo-structural coupled analysis. Additionally, the modeling process for multiple interposers and interposer housings, along with the preprocessing of contact conditions, adds complexity due to the increasing number of contact surfaces. This complexity can result in convergence issues and reduced accuracy. To address these challenges, this study employs Ansys Parametric Design Language (APDL) to enhance interposer and housing modeling, as well as contact problem resolution. It introduces a novel meshing method that positions nodes at target coordinates using point clouds, providing an effective analysis approach applicable to large, high-density probe cards and thermo-structural problems involving numerous contacts.

Among chemical coating methods, deposition using electrostatic spraying is commonly employed in coating processes to control the deposition rate, thickness, and properties of the formed materials. In this study, we considered the following variables: ring electrode, ring diameter (RD), ring voltage (RV), and nozzle-ring distance (NTR). Through experiments, we determined the atomization mode applied voltage, Sauter mean diameter (SMD), and SMD standard deviation of the nozzle. Additionally, we derived the voltage intensity and electric field along the axial direction using ANSYS maxwell to identify the optimal ring electrode atomization conditions.

The input shaft of gearbox usually bears a cyclic variation of torque, which may lead to the risk of experiencing a fatigue fracture. To evaluate the fatigue life accurately and identify the weak parts, the ANSYS is used to simulate the torsional fatigue of the input shaft for the gearbox, and the fatigue life of the weak part is obtained, which is then tested and verified by the torsional fatigue testing in the MTS torsional fatigue test rig. The test results show that the maximum difference is 14% between the calculated life and the testing results, indicating that the simulation value can reflect the actual fatigue life accurately. Notably, the cracks appear in the large oil holes, and its life is mainly concentrated in the crack initiation stage, accounting for 99.2% of the total life. The analysis results show that the fatigue life of the software simulation has the guiding significance for the life evaluation. The fatigue life of the shaft can be quickly calculated by the simulation to reduce the number of fatigue tests and achieve cost-effectiveness.