BLIND FAILURE PREDICTION

DiagFit

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DiagFit is a blind failure prediction software for industrial equipment. This means that the software builds a predictive model from the healthy data of a piece of equipment. It can then detect any deviation from "normality" without the need for a prior failure history. This unsupervised approach allows for a quick implementation of the solution.

What makes us unique

What makes us unique

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Blind mode

Works without historical failure data

No-code

No data science skills required

Agnostic

Sensor and equipment agnostic

Quick

Models built in hours/days instead of weeks/months

Accurate

Reduced false alarm rate

Citation

“Prediction is very difficult, especially if it's about the future''

Niels Bohr, Nobel Prize in Physics 1922

Competitions

Competitions

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Use Cases

Use Cases

Failure prediction on an anonymised ship system

Using anonymised health data acquired over a year on the ship, DiagFit was used to create a unique model within hours that captures correlations between sensor data and produces a health status for each sensor

Quality prediction and normative maintenance for plastic presses

Using the data from the variable speed drive on the press and the quality measurements at the output of the press, DiagFit analyses the deviation of the specifications used to derive a virtual quality sensor.

Pipe crack detection

Based on the eddy current data used to monitor the surface of pipelines, DiagFit can classify healthy and unhealthy pipe sections

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Customers

Customers

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