A concept for AI supported knowledge extraction in design for additive manufacturing
ABSTRACT: This paper presents a concept for an AI-supported DfAM framework aimed at supporting knowledge extraction, focusing on early design phases. The concept is derived from a set of objectives and integrates, in addition to the user, an agile DfAM process model, an AI copilot based on a large language model, and a structured knowledge base. A configured GPT is used as a prototype to demonstrate the feasibility of selected required functions. With regard to a full-scale framework, findings from this prototyping process and remaining open questions are discussed.
Authors
- Pascal Schmitt
- Kilian Gericke (ORCID: https://orcid.org/0000-0001-9949-2217)
- Stefan Zorn (ORCID: https://orcid.org/0000-0002-3920-097X)
Institutions
- University of Rostock (DE)
Publication Details
- Journal
- Proceedings of the Design Society
- Published
- 2026-07-02
- DOI
- https://doi.org/10.1017/pds.2026.10567
- Primary Topic
- Design Education and Practice
- Type
- article
- Field-Weighted Citation Impact
- 0.00