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Reliable Powerdown for Industrial Drives
Modern manufacturing relies heavily on electric drives and power converters to run production machinery.
When these systems shut down unexpectedly during idle periods or restart after a pause, unseen component failures can cause severe operational damage or costly downtime.
The R-PODID project addresses this challenge by developing automated, cloudless fault-prediction technology integrated directly into power converters.
By utilizing on-device artificial intelligence, the system creates a short-term prediction horizon of 12 to 24 hours to foresee impending electrical and mechanical failures before they occur.
This early warning capability allows industrial operations to safely shut down machines during idle times without risking failures during the next startup.
Additionally, the project enhances overall reliability by effectively mitigating dangerous faults in advanced semiconductor applications, such as silicon carbide and gallium nitride power devices.
Almende will lead the development of decentralized multi-agent algorithms for on-device AI monitoring.
We focus on building lightweight, cloudless intelligence that operates directly within power converters.
By enabling smart, local data processing, our software detects subtle operational anomalies without relying on continuous internet connectivity.
Through this work, we contribute to real-time fault prediction and help create more resilient industrial hardware setups.
The project will deliver fully tested, embedded AI software that integrates directly into power converter hardware.
This results in a reliable early warning system for maintenance teams, allowing for safe equipment shutdowns during idle times.
Ultimately, this reduces energy waste and prevents catastrophic hardware failures across industrial facilities.
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