What question did this study set out to answer?

The study aims to propose an AI-supported framework that enhances knowledge extraction during the initial design phases of additive manufacturing.

July 4, 2026Proceedings of the Design Society0 citationsOpen Access

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

PSPascal SchmittUniversity of Rostock SZStefan ZornUniversity of Rostock KGKilian GerickeUniversity of Rostock

Key Points

The study aims to propose an AI-supported framework that enhances knowledge extraction during the initial design phases of additive manufacturing.
Development of an AI copilot based on a large language model.
Integration of an agile design for additive manufacturing process model and structured knowledge base.
Prototyping using a configured GPT model to validate required functionalities.
Demonstrated feasibility of selected functions through prototyping.
Identified remaining questions regarding full-scale framework implementation.

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.

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