Early warning
for industrial
equipment.

Threshold alarms fire when a reading crosses a line. By then the failure mode is usually advanced, the intervention window narrow, and the diagnosis manual.

This system works from a different starting point. It learns what healthy operation looks like during commissioning. When behaviour departs from that baseline, the system classifies the departure: is it routine variation, something worth monitoring, or something requiring action?

The output is a three-state decision: ROUTINE, MONITOR, or ESCALATE. Not an anomaly score. A structured assessment of what is changing, how fast, and what kind of intervention it maps to.

A separate fault signature layer identifies what kind of departure is occurring, not from pattern matching against known failures, but from the pattern of physical signals in early departure. The system tells the operator not just that something is wrong, but what is wrong.

Every new machine class begins with physics. The system identifies the characteristic physical processes and their natural timescales, then selects signals that are physically sensitive to each one.

During commissioning, the system builds a baseline from healthy operation. Not months of data. Cycles. The departure classifier then runs continuously, comparing current behaviour against the commissioning baseline in a structured way that separates genuine degradation from operating condition variation.

When departure is detected, a staged confirmation structure separates early indicators from confirmed degradation, reducing false interventions without sacrificing lead time. The confirmation uses the same structure regardless of fault type, because the system was never trained on faults.

The setup procedure is the same for every new machine class: identify the physics, select the signals, commission healthy, detect departure. The architecture does not change.