Improving the fine-pitch stencil printing capability using the Taguchi method and Taguchi fuzzy-based model

TLDR: In this paper, a fine-pitch stencil printing process (SPP) based on the DMAIC framework and using Taguchi-based methodologies is proposed to continuously improve SPP capability, and a taguchi fuzzy-based model is developed to optimize the SPP with the MCPI property.

Abstract: This paper presents industrial applications for improving the capability of the fine-pitch stencil printing process (SPP) based on the DMAIC framework and using Taguchi-based methodologies. SPP is widely recognized as the main contributor of soldering defects in a surface mount assembly (SMA). An inadequate volume of solder paste deposition or poor printing quality can cause soldering defects and lead to significant reworking and repairing costs. In practice, both the desired amount of solder paste volume (quantitative index) and printing quality (qualitative index) are preferably used to monitor the SPP for the reduction of soldering defects during the statistical control process (SPC), particularly for a fine-pitch solder paste printing operation. To continuously improve SPP capability, the DMAIC framework is followed and Taguchi-based methodologies are proposed under the considerations of single characteristic performance index (SCPI) and multiple characteristic performance indices (MCPI). The SCPI is optimized using the conventional Taguchi method. Then, a Taguchi fuzzy-based model is developed to optimize the SPP with the MCPI property. Optimizing a multi-response problem by the Taguchi method involves the engineer's judgment which tends to increase the degree of uncertainty. The performance of these two approaches is compared through the process capability metric, and the material and factors significantly affecting the fine-pitch SPP performance are reported.