Process Parameter Optimization of Solder Paste Deposition for SoC Using Taguchi–Grey and Entropy Approach

Abstract

The quality of solder paste deposition (SPD) mostly decides performance of solder joints between system on a chip and printed circuit board. In view of the complexity of this SPD process, identifying the key process parameters and optimizing them are very important to improve the quality of SPD. Based on different products maybe having different key process parameters, the cause-and-effect matrix tool was employed to identify the key parameters (squeegee pressure, squeegee speed, and separation speed) and multiresponse (volume, area, height, and offset) of this paper. The hybrid approach integrating Taguchi–Grey relational analysis and entropy was used to convert multiobjective quality characteristics of SPD into a single-objective grey relational grade. Entropy was used to measure importance weight of volume, area, height, and offset. With estimated grey relational grade, it was confirmed that the optimum parameter level combination were better than the production parameter settings. The analysis of variance indicated the parameter of separation speed was most significant, which implied that the release efficiency of solder paste needed increase. Therefore, a nanocoating stencil was proposed to further enhance quality of SPD, as the future improvement direction of experiment.