Manufacturing & Heavy Industry
Sensor Intelligence ingests process telemetry from PLCs, SCADA, and historians, and surfaces the drift signatures that precede unplanned downtime.
Built for manufacturing and heavy-industry operators who would rather see a failure six weeks before it happens than write up a postmortem.
PLC and SCADA tags, OPC UA streams, vibration and acoustic sensors, energy consumption per line.
Which line will go down this shift. Which machine's bearing pattern matches a failure history. Which energy spike is a sensor lie, not a real event.
Predictive maintenance grounded in cross-signal physics, not single-channel thresholds. Causal filtering kills the alarm storm. A queue ranked by production impact.
Where it lands
Industrial telemetry is rich but operationally opaque. Statistical thresholds miss the slow drifts. Vendor-specific tools don't talk to each other. The team most affected by unplanned downtime is the team least likely to have time to write a custom analytics layer.
Read-only ingest from OPC UA, Modbus, and PLC-vendor APIs. Cross-signal physics constraints catch the failure modes single-channel thresholds can't see. The output is a queue of pre-failure tickets — not a wall of metrics — so the operations team can plan maintenance around the line, not around it.
Built for
Operations, reliability, and maintenance leadership at process manufacturers, discrete manufacturers, and heavy-industry operators.
What changes
Worked example
A pulp mill operator: a single bad pressure sensor had been the root cause of an alarm storm flagged daily for a year. Cross-signal incoherence detection caught it in 11 days. The team saved 6 hours/week previously spent triaging cascading alarms.
Regulatory & compliance notes
OPC UA, Modbus, and PLC-vendor protocols. Read-only by default.
20-minute demo, scoped to manufacturing & heavy industry. Senior engineer on the call.