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Enabling federated learning services using OPC UA, linked data and GAIA-X in cognitive production

Friedrich Christian, Vogt Stefan, Rudolph Franziska, Patolla Paul, Grützmann Jossy Milagros, Hohmeier Orlando, Richter Martin, Wenzel Ken, Reichelt Dirk, Ihlenfeldt Steffen

Journal of Machine Engineering

2024

Vol. 24, No. 2

18--33

Value creation in production is based on collaboration of different stakeholders and requires the secure and sovereign exchange of knowledge. Today, knowledge has mostly been built up individually and is only exchanged in a proprietary manner. This paper presents an exemplary pipeline for federated services in cross-domain and cross-company value creation networks for cognitive production. On the example of collaboratively training of a federated machine learning model, machine tool lifetime is predicted in industrial manufacturing for high-end operating resources (high-quality cutting tools). From the shop floor to the cloud, all service relevant information is structured using existing digital twin standards and a linked data approach. In particular, the Industry 4.0 Asset Administration Shell (AAS) and OPC UA are used for collecting and referencing operational and engineering data. GAIA-X connectors transfer the service relevant data through a shared data space. The solution enables intelligent analysis and decision-making under the prioritization of data sovereignty and transparency and, therefore, acts as an enabler for future collaborative, data-driven manufacturing applications.

Towards the digital model of tool lifecycle management in sheet metal forming

Majstorovic Vidosav, Vukadinovic Vojin, Zivkovic Jovan

Journal of Machine Engineering

2023

Vol. 23, No. 3

141--166

Sheet metal forming is a critical process in the manufacturing industry, which involves shaping sheet metal into desired configurations and structures. The use of digital tools in the lifecycle management of sheet metal forming tools has become increasingly important to ensure the efficiency and effectiveness of the process. The digital model of tool lifecycle management (TLM) in sheet metal forming provides a complete approach to manage the entire lifecycle of tools used in sheet metal forming. It enables optimization of tool design, simulation of the tooling process, real-time monitoring of tool conditions, and retirement and replacement of tools. This approach improves efficiency, reduces costs, and ensures optimal performance in sheet metal forming. The paper presents an elaborate analysis of the development of TLM models concerning the progress in ICT modelling and its implementation in the field of sheet metal forming. Furthermore, the paper includes an exemplary TLM model for an industrial enterprise.