The system grades shape, color, size, and surface defects. When a parameter drifts out of tolerance, STAQ doesn't just reject the piece — it runs trend analysis: what specifically drifted, and when the drift started. The operator gets an actionable recommendation to correct the line before reject rates climb.
What that means on the floor: lower scrap, consistent quality for demanding retail-chain customers, and objective data replacing a human inspector's subjective grade.
Deploying AI quality control starts with the foundation — equipment that actually produces a consistent output. If proof-cabinet humidity is drifting and mix-water temperature is all over the map, no amount of AI will save the process. Step one toward a smart plant is reliable equipment with tight parameter control.