Micro-defects accumulate through firing; an inspector's eye tires of catching them.
Slip-cast and pressed ceramic lines stack small defects through every step — green ware to biscuit to glaze to firing. Each step is fast enough for the eye and slow enough for fatigue to set in. By end-of-shift the pinhole rate has climbed and the cohort has already shipped.
- 01Gaps in glaze coverage
- 02Pinholes after glaze firing
- 03Rim chipping during handling
- 04Warp at biscuit firing
What our Tableware-specific AI agents are pre-trained to detect out of the box.
- Microstop
- Material jam
- Faulty machine movement
- Faulty material infeed
- Incorrect spacing
- Flawed intake
- Stuck material
- Machine running empty
- Placement errors
- Buffer over/underflows
- Line blockage
- Misaligned product
- Tipped product
Automate your vision-based workflows in days, not months.
- 01
Define critical areas
Outline the zones that matter on each feed — the fill point, the exclusion area, the stacked output — so the agent watches exactly where loss and risk show up.
- 02
Define visual triggers
Start from our pre-trained trigger library or train your own. A single stream can run several triggers at once, each watching for a different event.
- 03
Define actions and escalations
Set how the agent responds — a dispatcher ping, a logged event, or a closed-loop stop — and chain those into escalation paths from first alert to full intervention.
Let's look at your line together.
We'll walk through a representative case from your industry on video. Specific answers to specific questions.