Revolutionizing Predictive Maintenance for WEISSER Precision Turning Machines with prenode Decentralized Machine Learning Solution

In Zusammenarbeit mit der WEISSER Gruppe und der Hahn-Schickard-Gesellschaft haben wir eine bahnbrechende Predictive-Maintenance-Lösung für WEISSER Präzisionsdrehmaschinen entwickelt. Unser Kooperationsprojekt "KIOWA" zielte darauf ab, die dezentrale Machine Learning Software (mlx) von prenode zu nutzen, um Wartungsereignisse vorherzusagen und die Leistung von WEISSER-Maschinen zu optimieren.

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Traditional predictive maintenance solutions require companies to share their sensitive machine data, often compromising their privacy and security. Additionally, gathering sufficient data from a single machine alone may not generate accurate predictions.

WEISSER faced these challenges when seeking to implement an effective predictive maintenance service for their customers.

To address these issues, we employed federated learning, a cutting-edge approach in the field of artificial intelligence. With prenode mlx, we can make use of multiple data sources and create robust machine learning models. Moreover, it allows the ML models on each machine to continuously learn from each other, enhancing their predictive capabilities over time.

Our solution ensures privacy, security, and accurate predictions by sharing knowledge across multiple machines while keeping the data on edge at individual sites.