Every leader has experienced it.
Yesterday, production was on track. Today, yield is down and no one can explain why.
This sudden drop is frustrating. Reports highlight the numbers, but they rarely reveal the hidden causes. Without clear insights, teams waste hours chasing guesses instead of fixing what truly matters.
Yield loss is often subtle and hard to trace:
The outcome is predictable: wasted time, wasted resources, and mounting frustration.
AI systems like Frizb look where humans don’t—and catch what humans can’t. By analyzing video and operational data, they make the invisible visible:
On a packaging line, yield suddenly drops overnight. Machine uptime looks normal. Processes seem unchanged.
Frizb’s inspection uncovers the real issue: during cleaning, a slight misalignment was introduced in a conveyor segment. It’s a spot where no deviation should ever occur, yet video analysis flagged unusual stillness at that exact location.
What went unnoticed to the human eye was a continuous misalignment, quietly creating jams downstream. Teams had been spending hours trying to fix symptoms instead of the root cause. With AI supervision, the cause was visible, precise, and quickly corrected.
Yield returned to normal within hours, not days.
Catching hidden causes of yield loss transforms operations:
Yield drops are costly, but the real risk is invisible problems hiding in plain sight.
By watching the entire pipeline at a macro level while noticing the smallest deviations Frizb AI supervision ensures that what slips past the human eye is still caught, flagged, and fixed.
In manufacturing, every percentage point of yield matters. Seeing what was once unseen is the edge that keeps production steady, efficient, and competitive.
