Aerospace-X - Our Vision

"Building a digital ecosystem for an efficient and sustainable Aerospace Supply Chain."

The aim of Aerospace-X is to drive forward the digitalisation of supply chains in the aviation industry. The core of the project is a jointly designed range of federated services and data standards for the aviation industry in Germany and Europe, which enables the participating companies and organisations to realise transparent data and resource usage, increase the efficiency of various value-added processes and make them usable across industries according to open source principles.

With the aim of creating a collaborative data network for the aviation industry, Aerospace-X is driving the development of the building blocks for an open and sovereign data ecosystem for the sector.

In this data ecosystem, standardised processes, harmonised data models and transparent access mechanisms are intended to simplify collaboration between all players in the supply chain - OEMs, large suppliers, SMEs, logistics companies and raw material suppliers - and thus increase efficiency more quickly. Among other things, depending on the use case, it should be possible to authorise visibility beyond the Tier 1 level in order to increase reactivity in the supply chain in both directions.

The use cases focus on the topics of sustainability and supply chain resilience. 

The use cases ‘Circular Economy’ and ‘Product Carbon Footprint’ are addressed in the ‘Sustainability’ focus area. The aim here is to develop solutions to manage the rapidly increasing amount of data and the necessary exchange of information that goes hand in hand with the growing regulatory and legal requirements. The data for the entire product life cycle can be stored in a ‘digital product passport’ and released, read and edited depending on the application.

The focus area ‘Supply chain resilience’ includes ‘Demand and capacity management’ and ‘End-to-end non-quality management’. The aim is to develop data models and applications that record production and delivery capacities as well as quality data from the production steps preventively and aggregate them across several levels of the supply chain. This should make it possible, for example, to change production rates at short notice and better anticipate bottlenecks. It should also make it easier to find the causes of delivery or quality problems and mitigate them collaboratively.