We are proud to announce that our proposal was accepted as part of an innovation contest by the Ministry of Economics BW. Together with WEISSER Group and Hahn-Schickard, we are developing a predictive maintenance solution for WEISSER turning machines.
The proposal “KIOWA” was submitted at the innovation contest “AI – Made in Baden-Württemberg”, which aims to boost research and development of AI solutions for small and medium-sized enterprises.
In the project, prenode’s Decentralized Machine Learning software mlx will use distributed data sources to predict maintenance events for WEISSER machines. The different ML models will learn from each other, so that failures can be predicted more precisely. We use federated learning to overcome the fact that usually only few failures can be observed per machine. This enables the development of machine learning models across machines, while keeping the data on-the-edge.
In the future, customers of WEISSER may benefit from the research project as they do not need to reveal their data in order for WEISSER to offer a predictive maintenance service. Further, the volume of the transmitted data is reduced and machines do not need to be online all the time.
We are looking forward to working with the teams from WEISSER and Hahn-Schickard-Gesellschaft!
More information on the project can be found on the website of Hahn-Schickard-Gesellschaft.
Read more about the contest “AI – Made in Baden-Württemberg” in the official announcement document in German here.