The project IDEA aims to develop and implement a fully integrated Digital Engineering Workbench across the German Aerospace Center. Digital Engineering enables the development of complex systems using digital models as the primary source of truth, ensuring data consistency and seamless collaboration across engineering disciplines.
As engineering systems become more complex and interconnected, traditional development approaches relying on static documents and fragmented workflows struggle to keep pace with growing demands for efficiency, traceability, and collaboration. Digital Engineering addresses these challenges by shifting to a model-based paradigm, where digital system representations serve as the authoritative source of truth. This transition enables consistent data management, better integration of multidisciplinary expertise, and more agile decision-making throughout the entire development lifecycle. By implementing a unified Digital Engineering Workbench, this project seeks to enhance system development processes within the German Aerospace Center, ensuring that engineers and researchers can work more efficiently while maintaining a high level of accuracy, transparency, and adaptability.
The workbench will be accessible across all domains and built on a structured Digital Development Process adaptable to various applications. It will be based on open standards and interfaces, allowing integration with external partners. To support its adoption, a suite of tools, documentation, training materials, and a digital engineering guideline will be provided.
The workbench will support key systems engineering activities in the conceptual design phase, including requirements definition, system architecture development, system analysis, and multi-criteria decision-making. It will integrate multidisciplinary design analysis, optimization, and co-simulation capabilities to enable automated system architecture exploration.
To enhance decision-making, it will include data provenance tracking, artificial intelligence methods for process acceleration, and uncertainty quantification techniques. The Institute of Data Science will contribute by supporting the implementation of knowledge-based artificial intelligence applications and developing guidelines for effective use of the workbench. This is crucial in order to convert the complex data into usable insights and thus enable users of the workbench to make data-driven decisions throughout the entire development process.
