Practical example and current challenges
- An ever-increasing number of variants, technological upheavals and the integration of more and more new suppliers into production networks characterize the digital transformation of the manufacturing industries.
- At the same time, the requirements for transparency and controllability of the supply chain up to the own company are increasing. Ensuring the supply of components is a major challenge, not only in times of international trade conflicts and increasing environmental influences. In the case of recall actions, too, it is crucial to know which component was used in which production batch and to be able to trace the supply chain. It is also important to improve the early detection of serial defects in the field (track and trace).
- The greatest challenge is the provision and linking of data from inhomogeneous IT systems of different players while at the same time maintaining data sovereignty along the entire production and supply chain. A complete data image is essential for the clear identification of faults.
- In industry-specific solutions, the cross-company exchange and linking of heterogeneous data has so far been primarily promoted on a bilateral level. Common regulations for participation in the ecosystem and cooperation could considerably reduce the costs and participation hurdles, especially for medium-sized companies. In this way, new business models can be created and synergies in the value-added network can be used even better.
- On the basis of a hybrid cloud solution – consisting of the company's own edge cloud data center and networked in a cloud system – critical data remains in company ownership and data required for supplier collaboration is available via the industry platform or via the intra factory track and trace service. For the first time, all data (each is generated in different systems) can be provided centrally in one place, i.e. from capacity planning and warehouse stocks to work in progress information in production, track and trace data from transport as well as product, process and machine-related data. In this way, a continuous history from a sale order down to the individual part (lot size 1) is created. This means that (quality and process) data is linked and processed in almost real time – data is generated about the order with the supplier, its capacities and stock levels, milestone achievement in production progress and transport status. This allows delays in the supply chain and quality problems to be quickly lo-calised. The effort is reduced to exception management.
What added value does the "GAIA-X project" offer?
- The project makes it easier to establish clear and understandable criteria for participation/ cooperation within the ecosystem and reducing the need for bilateral coordination between interested companies.
- Through the one-off ‘qualification’ of the edge cloud data center as a GAIA-X node, players can make their own database available to a potentially larger group of interested parties to improve the quality of their own products or to develop digital services.
- The project facilitates the selective transfer of data and thus strengthens data sovereignty
- Through standardisation requirements and unified semantics, data can be better linked to each other. Typical use cases, such as the traceability of primary products, can be better implemented – also in the course of uniform identity management. At the same time, the implementation effort of cross-company track and trace solutions can be reduced considerably.
- The project can serve as an integrator. An overarching, open ecosystem will be created that encourages data exchange and stimulates new business models.
Use Case Team
- Markus Quicken – SupplyOn
- Sebastian Ritz – German Edge Cloud
- Dieter Meuser – IoTOS
- Lars Nagel – IDS Association