Human-Centered & Neuro-Symbolic Decision Support in Circular Product Engineering (HUMAN-DECISION)

• Applicants: Professor Dr. Sören Auer; Dr.-Ing. Felix Engel; Professor Dr.-Ing. Robert Heinrich Schmitt
• Subject Area: Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics ; Engineering Design, Machine Elements, Product Development
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 543081196

The process of product creation cannot be viewed in isolation. The current socio-economic situation, which is based on the assumption that natural resources are infinitely available, makes the integration of concepts of the Circular Economy (CE) an indispensable factor right from the planning phase of a product. From a political perspective, the EU-wide implementation of a digital product passport is forcing companies to consider CE in product development, generate data, and ban the destruction of usable goods. Therefore, disassembly and the capability of the assembly system to conduct it must in the future be taken into account in the early phases of the product development process as specified in VDI202. The consideration of product sustainability and the circular economy confronts engineers and product designers with a multitude of options that have to be made based on a complex interplay of existing products, processes, reusability and economic framework conditions. As computerized systems increasingly support humans in decision-making during product development, many urgent and fundamental questions arise that affect the performance of the system and relate to very different challenges, such as: 1.) During the product development process and/or after the end of the product life cycle, how can the necessary reconfigurations of existing assembly systems be optimized resource-efficiently for the integration of a new product or product changes, considering disassembly in the same system? 2.) How can contextual user knowledge (acquisition/decommissioning of machines, availability of materials, supply chains, etc.) become part of the digital twin? 3.) How should a decision support system be designed to support the engineer with highly uncertain decisions and return knowledge for continuous improvement? The aim of this project is to research solutions for the above challenges, to support engineers in decision-making processes using human-centered hybrid neural-symbolic Decision Support Systems.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2443: Hybrid decision support in product creation