TY  - JOUR
AB  - Early product creation involves decision-making under uncertainty, driven by heterogeneous customer inputs, multidisciplinary dependencies, and iterative stakeholder coordination. Translating informal customer needs into precise system definitions remains a significant challenge. This paper proposes an AI- and data science (DS)-driven automation framework that integrates customer-interactive, human-in-the-loop requirements engineering with automated system concept development and evaluation. The approach is validated using an unmanned aerial vehicle use case in an industrial-grade digital engineering environment. The results demonstrate how integrated AI- and DS-supported workflows can improve efficiency, decision-making quality, coordination, and traceability in early product creation.
AU  - Tatschl, Michael
AU  - Schalk, Gerolf
AU  - Hick, Hannes
DO  - 10.17619/UNIPB/1-2647
PB  - Universitätsbibliothek
DP  - Universität Paderborn
LA  - eng
PY  - 2026
SP  - 1 Online-Ressource (Seite 179-188) : Illustrationen, Diagramme
T2  - 1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University
TI  - AI- and data science-driven decision support: transforming early product creation and collaboration in product development
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:466:2-58843
Y2  - 2026-10-07T00:42:28
ER  -