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62 SMT007 MAGAZINE I OCTOBER 2023 vibrations—which can influence PCBA qual- ity. Research demonstrates that AI-based methods can enhance product quality by up to 35% and reduce scrap rates compared to tra- ditional approaches. is suggests data-driven intelligent process control can advance PCBA significantly. Intelligent Inspection Modules e goal of smart PCBA is to maintain opti- mized settings both offline and online. AI and data analytics solutions can optimize PCBA process parameters before production (offline control) and during production (online con- trol). A printing advisor module uses sophis- ticated data-driven methodologies to improve the printed circuit board quality and increase process robustness. Reinforcement learning approaches developed a printing optimization module to achieve intelligent control of print- ing parameters. Also, a printing diagnosis mod- ule will reduce the operational costs and poten- tial failures by identifying and preventing the root causes. Using deep learning models like convo- lutional neural network and recurrent neu- ral network, we can detect a potential anom- aly in the PCBA to ensure high operation reliability and smart process control. Yet, beyond print process advancements, collabo- ration is helping drive component mounting improvements. Testing is underway on mod- ules designed to identify optimal component placement positions by predicting post-reflow positions based on data collected by SPI, pre- AOI, and post-AOI machines, as well as offer- ing adaptive placement adjustments during production. Preliminary results show an 18% reduction in misalignments compared to con- ventional placement methods. Moreover, the module uses operational and AOI inspection data to trace the root causes of mounter defects and prevent future failures, achieving an 84.5% accuracy in finding known root causes. ese efforts not only save time and labor but also enhance the automated PCBA process. e innovative electronic manufacturing solu- tions from this project will promote the sus- tainable success of the electronics manufac- turing and improve the competitive advan- tage with efficient manufacturing decision mak ing , improved product qualit y, and increased profitability, while advancing Indus- try 4.0 development for PCBA. Summary and Conclusion e increasing complexity of PCBA, driven by the demand for small-scale electronics prod- ucts, requires innovative solutions. With AI and big data harnessed from various inspection operations, PCBA can become intelligent and adaptable in response to dynamic environmen- tal conditions. By maintaining the ideal process parameters throughout the processes, AI-pow- ered tools can help manufacturers improve quality and yield without sacrificing produc- tion speed. Automated, smart systems open the door to the next level of electronics manufac- turing by utilizing data from end-users to facil- itate customized product manufacturing with enhanced efficiency for high-mix/low-volume production. is not only expands the possibil- ities for design variations but also accelerates delivery times, ushering in a new era for elec- tronics manufacturing. SMT007 Brent A. Fischthal is head of global marketing at Koh Young Technology. Additional Resources The Printed Circuit Assembler's Guide to... SMT Inspection: Today, Tomorrow, and Beyond The Companion Guide to… SMT Inspection: Today, Tomorrow, and Beyond