Robust parameter design for the micro-BGA stencil printing process using a fuzzy logic-based Taguchi method

Solder paste is the main soldering material used to form strong solder joints between printed circuit boards (PCB) and surface mount devices in the surface mount assembly (SMA). On average 60% of endof-line soldering defects can be attributed to inadequate performance of solder paste stencil printing. Recently, lead-free solder paste has been adopted by electronics manufacturers in compliance with the RoHS directive. However, soldering defects in the ball grid array (BGA) packages used in lead-free SMA have become more prevalent and are difficult to detect. In this study, a fuzzy logic-based Taguchi method is proposed to optimize the fine-pitch stencil printing process with multiple quality characteristics for the micro ball grid array (micro-BGA) packages using a lead-free solder paste. A structured data set is first collected from an L18 (21 × 37) fractional factorial design experiment, followed by multi-response optimizations and analysis of variance (ANOVA) for identifying significant factors. The optimization perrinted circuit board eural network enetic algorithm formance gained by the proposed fuzzy logic-based Taguchi method is compared with the results of other two hybrid methods including a combination of neural networks and genetic algorithms, and the integration of the response surface methodology with a desirability function. The confirmation experiments show that the proposed fuzzy logic-based Taguchi method outperforms the other two methods in terms of the signal-to-noise ratios and process capability index. © 2016 Elsevier B.V. All rights reserved.