The system is suitable for applications ranging from sub-contract machine shops to large production plants. Unlike other IIoT systems, the “edge-heavy” technology collects, keeps and processes production data on the shop floor, rather than in the cloud. It gives operators access to accurate real-time data and analytics.
For larger sites, the system can connect multiple cells, allowing manufacturers to make intelligent decisions that can help boost productivity.
The system “ensures a fast response to edge devices without the need for a cloud connection,” explains Fanuc’s European technical support manager, Craig Taylor. “This allows for better real-time processing and autonomy to move without the Internet, as well as reduced cloud communications costs and better data leak prevention.” However, if users want to store data for future analysis or combine the data from different sites, they can do so via the cloud.
“We are aiming to empower the engineer, not de-skill them,” Taylor adds. “Manufacturing is becoming increasingly digitised and we see the Field system as a tool that can amplify the knowledge of those running production, by taking a few key inputs and using them to improve the efficiency and output of their operations.”
The system is compatible with various applications available from Fanuc’s new App store. These include apps from third parties such as software houses, systems integrators, as well as end-users. For example, one third-party app from Open Data captures the OEE (Overall Efficiency of Equipment) of a production system in real-time and visualises the data on a dashboard.

Fanuc’s Field platform provides fast, centralised access to production data
Two of Fanuc’s own apps are:.
• Field PMA (production monitoring and analytics), which monitors the production and performance of all connected machines, and flags if any are not operating at intended capacity, as well as facilitating waveform failure analyses.
• Field ZDT (zero downtime), which monitors the health of machines continuously and can identify trends – such as torque changes or disturbances – and tell operators when maintenance is needed.