The effect of solder paste volume on solder joint shape and self-alignment of passive components

In this study, an energy-based three-dimensional (3D) model is created using Surface Evolver to predict the passive components solder joint shape after reflow soldering. The developed model considers the surface tension and hydrostatic forces on the molten solder and the gravitational force on the capacitor and solder paste. By optimizing solder paste volumes for different types of surface-mount components, the model achieves the desired solder joint geometry. Surface mount capacitors (C1005, C0603, C0402) with solder paste SAC305 and copper pads with an electroless nickel immersion gold (ENIG) surface finish are used as examples. Capacitor solder joint shapes with various solder paste volumes are summarized and presented. A large number of capacitor samples have been cross-sectioned and inspected to validate the solder joint shape results predicted by the modeling. Furthermore, the effect of solder paste volume on passive component self-alignment is investigated with simulations and experiments. The results show that if the solder paste volumes at the two terminations of the component are consistent, the component will self-align very well. A relatively larger solder paste volume can improve the component self-alignment performance because of the bigger restoring force generated by the molten solder. Moreover, the results show that the self-alignment performance is better in the component-width direction (direction) than the component-length direction (x direction). An extensive number of experimental studies are performed to develop a data-driven prediction model to reduce the manufacturing cost at the design stage. The surface mount capacitors are placed with some initial offsets intentionally and their positions are measured before and after the reflow process. A wide range of surface mount assembly imperfections is considered in this work to achieve a powerful datasheet and better convergence. The simulation results are then compared with the experimental data for validation.