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.

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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
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article

A concept for AI supported knowledge extraction in design for additive manufacturing

Pascal Schmitt, Kilian Gericke, Stefan Zorn
Proceedings of the Design Society
Design Education and Practice
article

A concept for AI supported knowledge extraction in design for additive manufacturing

Pascal Schmitt, Kilian Gericke, Stefan Zorn
article en

Abstract

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.

Proceedings of the Design SocietyVol. 6
University of Rostock (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
Design Education and Practice
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