AI Solutions

Predictive Maintenance Engine: the AI layer under every asset.

Gear Brain's predictive maintenance platform reads vibration, thermal, acoustic, and electrical signatures from rotating and reciprocating equipment, then tells maintenance teams what's about to fail, and when — not just that something looks unusual.

Fleet Overview — Plant 3 Live
Compressor 2 — thermal drift rising
Confidence 87% · predicted failure in 26 days
Review
142
Assets monitored
6
Active flags
96.7%
Fleet health
How it works

From raw sensor signal to a scheduled work order.

The engine doesn't just watch one number drift outside a threshold — it models the full degradation curve for each asset class and cross-checks against your maintenance history.

1
Sensor fusion at the edge

Vibration, temperature, current, and acoustic sensors stream through an on-site edge unit for low-latency inference.

2
Failure-mode modelling

Separate models per asset class — pumps, motors, gearboxes, compressors — trained on real failure signatures, not generic anomaly detection.

3
Confidence-scored alerts

Each flag carries a failure mode, a confidence score, and a predicted window, so teams can triage instead of guess.

4
CMMS integration

Work orders route directly into your existing maintenance system with a recommended action and parts list attached.

Deployment

From site survey to live monitoring in four stages.

01

Asset survey

Our engineers catalogue critical equipment and existing sensor coverage on site.

02

Sensor & edge install

Vibration, thermal, and current sensors are fitted with an edge gateway for local inference.

03

Model calibration

Models run in shadow mode against your maintenance history to tune thresholds per asset.

04

Go live

Alerts route into your CMMS and dashboard, with our team monitoring alongside yours for the first 90 days.

Coverage

What the engine monitors.

Asset classSignals monitoredTypical lead timeCommon failure modes flagged
PumpsVibration, temperature, current2–4 weeksBearing wear, cavitation, misalignment
MotorsCurrent signature, temperature3–6 weeksWinding degradation, rotor bar faults
GearboxesVibration, acoustic, oil temperature2–5 weeksGear tooth wear, lubrication faults
CompressorsVibration, thermal, pressure3–5 weeksValve wear, thermal drift, seal failure
Robot manipulatorsJoint torque, vibration, cycle time1–3 weeksActuator wear, backlash, encoder drift

Run a 90-day predictive maintenance pilot.

Start on your highest-risk assets and expand once the model proves out against your maintenance history.