AI Agent pour la Fabrication
Simuler. Prédire. Optimiser.
Solution DataMesh — Simuler. Prédire. Optimiser.
From dashboards to decisions
Manufacturing dashboards show what happened. Decisions require knowing what to do next. FactVerse AI Agent bridges this gap — combining production data with simulation and causal inference to answer "why did this happen?" and "what should we do about it?"
Yield isn't random
When yields drop, the typical response is to investigate everything. Causal inference narrows the search — identifying which process parameters and environmental conditions actually cause quality variation, not just correlate with it. This means targeted interventions instead of expensive shotgun approaches.
Simulation before commitment
Every line change, equipment upgrade, or scheduling modification can be simulated first. DES models capture the complex interactions between stations, buffers, changeover times, and operator patterns — predicting real-world impact before committing resources.
Why AI Agent for Manufacturing?
| Traditional Manufacturing Analytics | FactVerse AI Agent |
|---|---|
| SPC charts and dashboards | Causal inference + predictive analytics |
| Manual bottleneck identification | DES simulation with optimization |
| Correlation-based quality analysis | DoWhy causal inference (cause ≠ correlation) |
| Separate maintenance systems | Integrated PdM within the production twin |
| Static energy targets | Multi-objective energy-quality optimization |
Related
- FactVerse AI Agent — Full platform overview
- Manufacturing — Industry overview
- Process Simulation — Simulation solution
- Predictive Maintenance — Equipment health
Questions fréquentes
DFS se connecte via des protocoles standard (OPC UA, BACnet, REST API) aux systèmes existants.