Hear the bearing whine before anyone else does.
The predictor studies vibration, temperature and run-hour data alongside your own breakdown history. When a machine starts to drift towards a pattern that ended in failure before, it warns the maintenance head with the evidence, a suggested action and a window to do it in.
Vibration up 38% over 10 days, temperature up 6 °C. Similar pattern preceded last year's 14 h breakdown. Suggest: replace bearing in Sunday planned stop. Spare in stock: 1.
Inside AI Breakdown Predictor
Trend watch
Tracks vibration velocity, bearing temperature, current draw and run hours, and notices slow drifts a person would miss across 3 shifts.
Learns from your history
Matches today's readings against the lead-up to your own past breakdowns, not a generic textbook curve.
Works without sensors
With only checklists and breakdown history, it still flags machines with rising failure frequency and overdue wear parts.
Action window
Every warning suggests what to do and the latest safe time to do it, aligned to your next planned stop.
Shows its evidence
Each warning lists the readings, the matched past event and the confidence, so the maintenance head can judge.
Feedback that sharpens it
Mark a warning as right, early or false. The model adjusts for that machine.
How it runs on your floor
- Step 1Collect
Sensor gateways, PLC tags, checklists and breakdown history flow in.
- Step 2Compare
Readings are compared with each machine's normal and its past failure lead-ups.
- Step 3Warn
Maintenance head gets a warning with evidence and an action window.
- Step 4Decide
A person decides: schedule, watch or dismiss. Work order raised in one tap.
How the predictor behaves
- AI only warns. It never controls, starts or stops a machine and has no write access to any PLC.
- Every prediction shows the data behind it so the maintenance head can judge it.
- A person always decides whether to act, schedule or dismiss.
- Plant data is encrypted in transit and at rest and is never sold or shared.
About AI Breakdown Predictor
Do we need sensors?
No. Without sensors it works from checklists and breakdown history. With vibration and temperature sensors on critical machines, warnings come earlier and sharper.
Does the AI shut machines down?
Never. It is read only. It warns people; people decide.
How long before warnings are useful?
Trend warnings start within 2 to 3 weeks of sensor data. History matching improves as more breakdowns are closed with cause codes.
The rest of the panel
Turn the key. Run the line.
Try Hungpang free for 30 days on up to 50 machines. Tag your first machine today and your operators can report a breakdown before the shift ends.
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