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How would engineers use LLMs for assembly search if they could? – An empirical study for fostering generative AI-driven design reuse in the future

Fastabend, Jonas (1); Agovic, Irfan (1); Roth, Daniel (1); Neumann, Roman (2); Hammer, Christoph (2); Kreimeyer, Matthias (1)


Type:
Year:
2026
Editor:
Štorga, M.; Škec, S.; Martinec, T.; Marjanović, D.; Pavković, N.
Author:
Series:
DESIGN
Institution:
1: University of Stuttgart, Germany; 2: Robert Bosch Manufacturing Solutions GmbH, Germany
Page(s):
2293-2302
DOI number:
ISSN:
2732-527X (Online)
Abstract:
This study examines how engineers formulate natural language prompts for searching existing assemblies in mechanical design. A survey with 48 engineers produced 169 prompts for different assemblies. Results show that prompts are mostly written as bullet points with an average of three and up to seven requirements. The engineers describe assemblies mainly through implicit functional descriptions and geometric or physical parameters. These findings form an empirical basis for developing generative AI-driven, prompt-based systems to foster design reuse.
Keywords:

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