SPP 2443:  Hybrid decision support in product creation

• Subject Area: Mechanical and Industrial Engineering ; Computer Science, Systems and Electrical Engineering ; Social and Behavioural Sciences
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 521148212

The SPP will explore the fundamentals of how to use the potential of extreme data to overcome current performance limits in product creation. To this end, evidence must be gained, especially in the engineering and production of material products, in order to use hybrid decision support to realize complete material circularity. The aim is to bring together the disciplinary foundations and regional schools under the objective of hybrid decision support. The limitation to the early phases of the product's life cycle in terms of product and production, as well as the focus on material circularity and sustainability as a key complexity factor, form the basis for coherent research which require coordination efforts. Projects in the first funding period are based on data that are credibly available from experimental preparatory work, industrial projects or field trials at the respective applicant. Research addresses individual components or subsystems. In the second FP, an increase in the complexity of the products under consideration in the form of complete technical systems will be required. This is accompanied by additional requirements for the predictive capability of Data Science/Artificial Intelligence (DS/AI), for which future data situations must be designed (possibly synthetically). Main topics that are foreseen in the first funding period and that will be used for cross-project alignments are: - Alignment of approaches based on VDI/VDE 2206, - Alignment of approaches with regard to circular economy, for instance, based on the generic Product Life Cycle (gPLC) model, - Overall categorization of DS/AI approaches, - Alignment of concepts how to represent decision-making situations and evaluate performance and its increase in product creation. In addition, the setup of distributed databases is coordinated with regard to data from the product creation application domain (engineering artefacts, field data, training sets, etc.) as well as research data from the implementation of the projects. Three focus topics will first coordinate metadata models in a small group and then incorporate them into the overall SPP. In particular, different approaches to modelling data quality are coordinated. The management of federated data resources as well as compliance with NFDI4ing is ensured by coordination. This ensures that the individual projects can publish freely without data restrictions. To ensure cross-disciplinary and cross-site terminology, a glossary will be developed across projects and later made available to the scientific community. Its creation and maintenance during the project period will be carried out within the framework of the coordination project.

• DFG Programme: Priority Programmes

Projects

• coordination project (Applicant Gräßler, Iris )
• DeCap - Design for Capabilities - Data Science and Artificial Intelligence in Capability-Oriented Product Engineering for Sustainable Production (Applicants Gräßler, Iris ;  Nyhuis, Peter )
• Engineering assistance for hybrid decision support based on machine learning surrogate models (Applicants Gerhard, Detlef ;  Kuhlenkötter, Bernd )
• Human-Centered & Neuro-Symbolic Decision Support in Circular Product Engineering (HUMAN-DECISION) (Applicants Auer, Sören ;  Engel, Felix ;  Schmitt, Robert Heinrich )
• HYDRA – Hybrid Decision Support for Computer Aided Design (Applicants Hamker, Fred Henrik ;  Hasse, Alexander )
• INSPIRE: Intelligent Hybrid Decision Support Based on Multi-Modal AI for Product Creation (Applicants Lanza, Gisela ;  Stark, Rainer )
• XDP-Opt: Experience-Based Design Process Optimization for Industrial Manufacturing (Applicants Bergmann, Ralph ;  Ruskowski, Martin )

• Spokesperson: Professorin Dr.-Ing. Iris Gräßler