Optimization of machining processes through AI - Fraunhofer-IPT and Datamatters

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Central cloud services certainly have their pitfalls

So far, companies have relied on central cloud services for the development of their AI-supported quality control to avoid expensive initial investments for local digital infrastructure, as researchers further note. However, the large amount of production data stored in the cloud is outside the company's own control and is thus exposed to greater data privacy and security risks. Additionally, the ongoing, service-dependent fees of cloud services could become too expensive for companies in the long term. However, the machine learning method of Federated Learning allows small and medium-sized enterprises to benefit from AI for their quality control while ensuring the privacy and security of their sensitive production data. This is because the data remains securely on local servers while being used for the decentralized, collaborative training of even more powerful AI models. Across multiple company locations, the AI model is trained in a network of local devices and company servers without the manufacturing data leaving the local databases. Only the model parameters are sent to a central server, where they are aggregated and merged into a global model, ensuring that data sovereignty remains with the companies.

Machinists can choose their data storage location

Trauth makes it clear: "Real World AI comprises three components—data collection via sensors, gathering information in a protected data space, and subsequent evaluation or training of AI algorithms." As it continues, Datamatters usually takes care of data collection in projects and provides the necessary technically secured and legally compliant data spaces. The customer can then decide whether to perform the AI evaluation in these data spaces or on their own servers.

Incidentally, "intelligent machining" is part of the research project "FL.IN.NRW", which is funded by the European Union and the state of North Rhine-Westphalia within the framework of the EFRE/JTF program NRW 2021-2027 (European Regional Development Fund ERDF and Just Transition Fund JTF). The project runs until 2027.

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Date: 08.12.2025

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AI in practice