DOI: 10.1017/pds.2026.10597 ISSN: 2732-527X

Evaluating large language models for technology-oriented searches in engineering design

Vasileios Koutsouvelis, Filippo Silipigni, Niccolò Becattini

ABSTRACT:

This study evaluates the efficacy of various freely available Large Language Models (LLMs) in conducting semi-automated purpose-oriented technology searches to support design activities as well as Technology Intelligence for innovation management, using a systematic manual search as a baseline for comparison. The case to run the comparison focuses on identifying water purification technologies suitable for mobile systems. The results show that LLMs can target more technologies than human-based searches, reducing time demands and providing wider entry points for additional technology analysis.

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