Marcy’s Musings: Additive Processes, Signal Consequences
It’s Only Common Sense: Build Your Business on Reputation, Not Neglect
The Marketing Minute: If Your Marketing Budget Gets Cut in Half, Then What?
PCB manufacturing is approaching a pivotal moment across the global electronics supply chain. For decades, the industry grew by adding equipment, expanding capacity, and relying on the accumulated experience of seasoned engineers. Today, the landscape is shaped by rising product complexity, increasingly sensitive material systems, tighter delivery expectations, and a worldwide shortage of technical talent. The traditional model is nearing its limits.
This is precisely why artificial intelligence (AI) and machine learning (ML) are entering the mainstream conversation—not as abstract concepts or futuristic visions, but as practical capabilities that address the most pressing challenges PCB fabs now face: predictability, stability, cross-process understanding, and the ability to manage complexity at a scale humans alone can no longer handle.
Why PCB Fabs Are ‘Needy’ for AI/ML
PCB fabrication is a long, interdependent chain of processes. Lamination affects drilling, drilling influences plating, plating affects imaging, and so on. Small deviations cause ripples in ways that even experienced engineers may not fully anticipate. As product requirements rise, decision-making based solely on individual experience becomes increasingly fragile.
At the same time, the industry faces a structural shift: fewer young professionals are choosing factory careers, and knowledge is becoming more concentrated than ever and is becoming increasingly difficult to transfer. The result is a growing gap between what fabs need and what traditional engineering models can supply.
To continue reading this article, which originally appeared in the December 2025 editon of PCB007 Magazine, click here.
