Edge inference
Jetson-class GPUs at the machine keep the control loop under 10 ms — no cloud round-trip.
How it works
Perceive. Predict. Control. Learn.
Panevex turns an open-loop module line into a closed-loop system. Here is exactly how a wafer becomes a graded, defect-screened module under one continuously-learning policy.
4loop stages
1shared twin
∞compounding runs
The loop
Four stages, one continuous cycle
01
Perceive
Every cell and string is imaged in EL, PL, and RGB. Geometry, defects, and bond quality become live data.
02
Predict
Physics-aware models score crack-risk, cure state, and power impact before the module moves on.
03
Control
Set-points on the stringer, laminator, and handling are corrected in real time on the edge.
04
Learn
Outcomes feed the module twin, which improves the policy every agent runs tomorrow.
Step 1 — Perceive every cell
Elumnex ingests electroluminescence, photoluminescence, and RGB vision at line speed. It segments microcracks, broken fingers, solder defects, and cell shift down to sub-cell resolution — building a complete perception model of the module as it's built.
- Sub-cell defect segmentation
- EL + PL + RGB sensor fusion
- Live geometry and alignment tracking
Step 2 — Predict the consequence
Detection isn't enough. Panevex predicts what each defect will cost — crack-risk of propagation, power impact in watts, and 25-year degradation exposure — so the line can act on the defects that actually matter.
- Crack-propagation risk scoring
- Power impact quantified in watts
- Field-degradation exposure modeling
Step 3 — Control the machine
Lamira and Ribbix don't just flag problems — they fix the process. Cure temperature, vacuum, pressure, dwell, bond thermal profile, and alignment are all corrected in closed loop, per material lot and stack-up.
- Closed-loop cure control
- Real-time bond correction
- Per-lot, per-recipe adaptation
Step 4 — Learn and compound
Every module's outcome is written back to Twinvex, the module digital twin. Tomorrow's policy is better than today's — and it transfers across lines and fabs. This is the flywheel that competitors can't copy without the data.
- Outcomes train the next policy
- Policy transfers across lines
- The moat compounds with volume
Under the hood
Edge for control, cloud for cognition
Cloud training
DGX/HGX clusters train and re-train perception and policy models on fleet-wide data.
Digital twin
OVX/RTX simulation validates every recipe and control policy before it touches a real module.
| Stage | Input | Decision | Action |
|---|---|---|---|
| Perceive | EL / PL / RGB per cell | Defect + geometry model | Write to module twin |
| Predict | Defect model + physics | Crack-risk + power impact | Flag or route |
| Control | Live station telemetry | Optimal set-points | Actuate machine |
| Learn | Module outcomes | Policy update | Deploy to fleet |
Do we have to replace our existing stringers and laminators?
No. Panevex adds perception and closed-loop control to the machines you already run. We integrate through your existing PLCs, SCADA, and MES.
How long before the loop is closed?
Most lines start in observe-only shadow mode within weeks, then enable closed-loop control station by station once baselines and guardrails are agreed.
What happens if the AI is unsure?
Every actuator has human-set guardrails. When confidence is low, Panevex holds within safe bounds and escalates with the evidence.
Watch the loop close on your line
We'll run a shadow-mode pilot and show you the escapes and recovered watts before you commit to closed-loop control.