optimize machine operation quality.

Unscheduled maintenance and machine breakdown are significant costs during a system’s life cycle. While preventive maintenance can be costly, breakdowns and downtime are often more expensive, affect customer satisfaction and imply risks due to machine failures.


  • Optimizing up-time of your device with time series analysis techniques
  • Anomaly detection to detect irregular behavior of your device
  • Optimal performance of your device during runtime with autocalibration

optimal balance between preventive and reactive maintenance.

We optimize your machine operation quality by monitoring your machine’s health and the application of smart algorithms for predictive maintenance. Predictive maintenance is a balance between preventive and reactive maintenance which optimizes costs against the safer and optimal error-free operation of the device.

bring your system's life cycle to the next level.

Optimizing machine operation quality goes further than just predictive maintenance, and can also involve the use of smart (auto) calibration of your system’s components.  With machine learning techniques like time series analysis and anomaly detection, we are able to continuously monitor your system’s health, ensuring optimal operation of the device, and decrease in the cost of ownership and customer satisfaction.


David Rijlaarsdam

+31 (0)88 - 115 20 00

contact us

starting from a concrete use-case is a success factor for applying AI.

products & services

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synthetic data

Generate near-infinite permutations of complex, domain-specific, 3D environments

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time series analysis

Increase functionality by actionable knowledge extraction

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machine vision

More robust machine vision applications

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reinforcement learning based control

Optimize control and machine performance

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