Connected Factory AI Operations

Illustrative reference design: This is not a customer case study and does not represent a specific factory deployment.

Design goal

Connect production signals to monitoring and AI services without exposing machine networks directly to enterprise or internet-facing systems.

System flow

1. Protocol adapters at the industrial edge read only the machine signals approved for the use case.
2. The edge layer normalizes events and publishes them through authenticated MQTT channels.
3. Site-local services validate, buffer and store operational data so temporary upstream interruptions do not require direct access to machine controllers.
4. Governed data feeds production dashboards, workflow automation and model-assisted analysis.
5. Infrastructure and application telemetry remain distinct from machine-control commands and safety functions.

Network boundaries

Machine, edge, site-platform and enterprise zones are treated as separate trust boundaries. Connections are explicit, authenticated and observable, with no assumption that a monitoring or AI service may write directly to production control systems.

Operational model

Edge services can continue collecting approved signals during an upstream interruption. Central services handle longer-term storage, dashboards and model workloads, while the monitoring layer reports the health of gateways, message flow and platform services.