Panasonic Connect: AI's real value in factories is supporting workers, not replacing them

What happened

Scott Zerkle, associate director of technical operations at Panasonic Connect North America, says the greatest practical value of AI in electronics manufacturing today is predictive maintenance and defect detection using machine data—not autonomous factory operation. He argues that expectations run ahead of reality when people assume factories can be run by AI alone, because AI is only as good as the data it receives, and most plants still run legacy systems that don't talk to each other.

Why it matters

As electronics become smaller and more complex—modern vehicles now rely on 60 to 100 or more sensors, with some exceeding 200—manufacturers face tighter placement tolerances and must catch defects before they escalate. Zerkle's view reframes automation not as a threat to workers but as a tool to handle repetitive analysis so operators can focus on complex decisions that require human expertise. This matters for manufacturers balancing quality, throughput, and workforce challenges.

What to watch

Over the next five years, Zerkle expects two key shifts on SMT lines: first, automation will handle more verification before changeovers (checking feeders and settings rather than relying on operator memory), and second, process data from skilled operators will train new hires and tune machines themselves. The biggest competitive advantage over the next decade will come not from adding more AI tools but from connecting AI, sensing, and automation to the same data so factories learn and improve from their own production history.