Icon 00

Practical example and current challenges

  • The paradigms of highly automated serial production and global supply chains with limited warehousing as well as the maximization of productivity through specialization, result in a flexibility deficit in the European industry. It results in a sudden disappearance of market demand for established products, supply bottlenecks and employee shortages. The situation is further complicated by the existing pressure from increased individualization of consumer goods.

  • The following central aspects of the use case are derived from this: How can (1) value chains be equipped with resilience to market changes and enabled for a high diversity of variants, (2) interdependencies between value creation stages be recognized and exploited to increase economic efficiency, (3) responsive and at the same time universal platforms for production systems be designed? The goal of the transnational use case "EuProGigant" is to demonstrate and scale a cross-location digitally networked production ecosystem with resilient, data-driven and sustainable value creation to regain and strengthen Europe's leading role in the manufacturing industry. With the self-sufficient organization of participants, data and services, this industrial ecosystem can mitigate threats from crisis situations.

  • In this use case, numerous stakeholders networked across countries, companies and locations (including machine manufacturers, suppliers, service providers, users, IT providers) demonstrate the data-based interaction. The functional solution is characterized by the integration and combination of the ecosystems’ products and expertise. Each ecosystem participant takes one or more roles and exchanges data or services with other players in the infrastructure ecosystem.

  • The EuProGiant use case looks at four functional areas and maps them in a value creation ecosystem using practical examples:(1) "Ideal component matching", (2) "Mobile processing machine", (3) "Validation platform", (4) "Carbon footprint in product development”. For these four topics, with reference to exemplary use cases of the corporate partners, new data and service-based business models are generated in relation to Gaia-X and made available to third parties in a transparent manner.
  • The implementation of EuProGiant promotes the establishment of a unified, standardized edge computing architecture for the decentralized, distributed processing of large volumes of data. It enables the flexible use of services and applications in the production process. In addition, intelligent data connectors allow communication links to be set up, creating strong, data-based supplier-user-end-customer interaction based on new digital business models in the value creation ecosystem. The collaborative use of infrastructure, such as test benches, as the basis for a validation platform also enables the reduction of non-value-adding processes.

Infografik: 00

What added value does the "Gaia-X project" offer?

  • Gaia-X provides the infrastructure for the EuProGiant use case. If Gaia-X is considered in the context of other important developments around Industry 4.0, a new form of Internet will emerge - the Giganet. It is characterized by high data volumes, highly networked corporate units, decentralized, secure and sovereign computing structures and a variety of services for data processing and communication.
  • With the support of Gaia-X, including the latest interface technologies, EuProGiant can provide customers with a new degree of analysis for their production processes.
  • Gaia-X offers the chance to combine existing technologies and to implement concrete use cases in production and to execute data-driven business models.
  • The implementation of the Gaia-X architecture needs to be simplified especially for SMEs. With this, EuProGigant creates the basis for autonomous and cost-effective management in manufacturing networks for SMEs. EuProGigant shows how SMEs can independently connect to the European data infrastructure via the Gaia-X Federation Services.

Use Case Team

  • Dr. Claudia Schickling – Technische Universität Wien
  • Prof. Dr.-Ing. Matthias Weigold – Technische Universität Darmstadt
  • Markus Lothar Weber – Technische Universität Darmstadt