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
자주 묻는 질문
DFS는 OPC UA, BACnet, REST API 등 표준 프로토콜로 기존 시스템에 연결됩니다.