Predict machine failures from vibration and temperature

Maintenance predicts machine and equipment failures from sensor data such as vibration, temperature and noise, to avoid downtime

Needs setupAI Act: no extra obligationsMonitoring sensor and machine dataIndustry, Energy supply, Logistics & transport

Fits: Field service & trades · Production, engineering & maintenance

Bearing damage, imbalance and wear show up in vibration, temperature and noise weeks in advance. You replace parts during planned downtime instead of after a failure in the middle of a shift.

Is this for you?

  • A failure of certain machines, such as pumps, fans, drives or conveyor belts, brings production or supply to a halt or becomes expensive.
  • You already measure vibration or temperature, by hand on inspection rounds or with permanently installed sensors, or you can retrofit sensors.
  • Maintenance documents faults and repairs in a way that lets you link them to machines and data.
First step today

Export the vibration and temperature readings of three to five machines of the same type over a few months, for example from your inspection-round measurements. Have the table analysed with the template below and compare the result with what your maintenance team knows about these machines.

How to go about it

  1. Define critical machines and failure modes
  2. Retrofit sensors and collect readings
  3. Let the system learn normal operation for each machine
  4. Set warning and alarm levels
  5. Feed warnings into maintenance planning
  6. Report findings back after every replacement

Templates to copy

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Included in the training

The complete guide

  • 6 steps explaining exactly what to do
  • 3 proven templates to copy into your own AI
  • Safe use: data, checking, deciding, informing
  • Pitfalls, effort and how to recognise success

With the training you get all 430 guides for as long as your access runs.

See the trainingOne-off per person, no subscription

Same approach, other use cases

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G-IN-02 · Legal status 08.10.2026