A missing component — a screw, a gasket, a clip, an electronic sub-assembly — is a defect that's easy to miss visually at high line speed, even though it is obvious in a calm, still image. That gap between operator pace and inspection pace is exactly why assembly completeness is usually one of the first candidates for automation.
In AIVQC Trainer, the model learns to recognise a complete, correct assembly from representative OK images, then detects the deviation from that pattern — a missing element at a specific point in the assembly. Controlled product positioning matters most here: the more repeatable the position in frame, the more reliable the detection.
The OK/NOK decision is made locally at the AIVQC Production station, in step with the line, and passed on to the process over Modbus TCP — with no image sent externally.