Condition monitoring across a six-machine fleet over Sparkplug B, with the bearing prognosis computed on the Edge.
Condition monitoring across a fleet of six rotating machines: 6 devices and 90 tags published over Sparkplug B to an MQTT broker that Litmus Edge subscribes to as a host application.
One twin model serves every machine, which is the horizontal argument in practice: the same tag map and the same Analytics groups apply to pumps, fans and compressors alike, so adding a machine is configuration rather than engineering.
It shows the impulse that appears before any trend does, a bearing prognosis produced on the Edge itself, and one model generalised across a mixed fleet.
Note: this solution runs as two containers, because Sparkplug B needs a broker beside the simulator and a Litmus Edge does not broker MQTT. Deploy it with its compose file rather than as a single container.
An electric arc furnace and a caster in one material flow over OPC UA, where a slag foam collapse sets the month billed demand charge.
A 110/20 kV substation with six feeders on IEC 60870-5-104: transformer thermal margin, tap changer wear, and a full recloser sequence.
Nine lift stations and a treatment works on DNP3, deliberately split across two Litmus Edges managed from one Litmus Edge Manager.
