BLIND FAILURE PREDICTION
DiagFit
Request a demoDiagFit 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
Request a demoBlind 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
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
Customers
Customers
Partners
Partners
