Nodal Dynamics

In most plants a breakdown is still discovered the moment it happens. A pump that loses a bearing stops a line, the part turns out to be weeks away, and what should have been a two-hour job becomes a stoppage measured in days. The signal was usually there long before — vibration creeping up, a motor drawing more current, a bearing running warmer each week — but it lived in a controller nobody was watching, or in the head of a mechanic who has since retired.

Nodal Dynamics builds a live model of the equipment from the data the plant already produces. It reads PLCs, drives and SCADA over open industrial protocols — OPC UA, Modbus, MQTT and Sparkplug B, SNMP, BACnet, EtherNet/IP — and imports years of history from PI, InfluxDB and SQL historians, adding sensors only where data is missing. Every machine, line and site gets a live status in 3D and on a plant map; a line is red if any one of its machines is.

From there it works forward. Trends in vibration, temperature and current are projected to estimate when a threshold will be crossed, and with what confidence. A warning becomes a work order with a checklist on a technician's phone; the part is recommended for ordering before the failure, allowing for the supplier's lead time, with a purchase draft for 1C or SAP PM. A root-cause agent explains why an alarm fired by walking the graph of what feeds what — and when the job is closed, the technician's verdict is recorded against the diagnosis, so the plant learns which predictions were right.

It is built for small and mid-sized manufacturers with rotating and thermal equipment — pumps, compressors, motors, conveyors, furnaces — where one stopped machine stops a line. It runs on the plant's own server, including fully isolated networks, or in the cloud; and every number it shows can be traced back to the readings it came from. Nodal Dynamics stands on Symbiosis Core, so its audit trail and evidence signing are the same contracts the rest of the portfolio uses.