Optimizing Solder Paste Printing Process with AI/ML
Steve Lee - Biomedical Engineering Department, SJSU
Henry Nguyen
Technical Advisor:
In Surface Mount Technology (SMT), the quality of solder paste printing plays a pivotal role in the performance and reliability of surface mount assemblies, as it is instrumental in forming solder joints. Industry statistics reveal that between 60-90% of soldering defects are linked to issues in the solder paste printing process, including misalignment, insufficient or excessive solder paste application, and solder bridging. These defects significantly impact assembly quality. The adoption of Artificial Intelligence (AI) and Machine Learning (ML) for analyzing data patterns from solder paste inspections presents a significant opportunity for enhancing this process. AI/ML algorithms can facilitate the identification and troubleshooting of defects, empowering operators to independently resolve issues without requiring direct intervention from engineers. This targeted application of AI/ML not only aims to streamline defect resolution and minimize downtime but also significantly improve the overall efficiency and quality control of the production process.