Why cloud latency is too slow for the shop floor
Cloud computing is excellent for analytics, reporting, and business logic. It is terrible for real-time manufacturing control. A round trip to the cloud takes 50-200 milliseconds. A vision inspection camera needs to make accept/reject decisions in under 10 milliseconds. A safety interlock must respond in microseconds. The cloud cannot meet these requirements.
What edge computing solves
- Vision inspection — AI inference at the camera, decisions in <10ms
- Safety interlocks — emergency stops processed locally, never dependent on network
- Data aggregation — compress 1,000 readings/second into meaningful metrics before sending to the platform
- Offline resilience — edge devices continue operating during network outages
- Bandwidth reduction — send summaries, not raw data; reduce network load by 90%+
Edge-to-platform architecture
The ideal architecture processes time-critical decisions at the edge and sends aggregated data to the platform for business context. The edge device handles real-time control. The platform handles analytics, reporting, and cross-functional visibility. Both work together, each doing what it does best.
Not all data needs the cloud. Not all decisions can wait. Edge computing puts intelligence where the action is.