Evaluating large language models for technology-oriented searches in engineering design
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.
Authors
- Vasileios Koutsouvelis
- Filippo Silipigni
- Niccolò Becattini (ORCID: https://orcid.org/0000-0002-1641-3796)
Institutions
- Fondazione Politecnico di Milano (IT)
- Politecnico di Milano (IT)
Publication Details
- Journal
- Proceedings of the Design Society
- Published
- 2026-07-02
- DOI
- https://doi.org/10.1017/pds.2026.10597
- Primary Topic
- Design Education and Practice
- Type
- article
- Field-Weighted Citation Impact
- 0.00