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In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.

Entity matching for recurring engineering components: a bottom-up enabler for reference architecture reconstruction

Hanke, Fabian (1); Feld, Markus (1); von Heißen, Oliver (1); Tagscherer, Kenneth (1); Wyrwich, Fabian (1); Trienens, Malte (1); Hovemann, Aschot (1); Dumitrescu, Roman (2)

Type:
Papers
DS 145: Proceedings of the DESIGN2026 19th International Design Conference
Year:
2026
Editor:
Štorga, M.; Škec, S.; Martinec, T.; Marjanović, D.; Pavković, N.
Author:
Hanke, Fabian (1); Feld, Markus (1); von Heißen, Oliver (1); Tagscherer, Kenneth (1); Wyrwich, Fabian (1); Trienens, Malte (1); Hovemann, Aschot (1); Dumitrescu, Roman (2)
Series:
DESIGN
Institution:
1: Fraunhofer IEM, Germany; 2: Heinz Nixdorf Institute, Paderborn University, Germany
Page(s):
2323-2332
DOI number:
10.1017/pds.2026.10590
ISSN:
2732-527X (Online)
Abstract:
Engineering organisations increasingly aim to reuse historical BOM, CAD, and requirements data to identify recurring components. A key prerequisite is Entity Matching (EM), whose performance on heterogeneous engineering data is unclear. This paper evaluates classical models, zero-shot LLMs, and hybrid EM on Amazon–Google and a multimodal engineering dataset. Random Forest and XGBoost achieve near–state-of-the-art results; LLMs perform well but are costly, hybrids add little. EM transfers under controlled conditions and forms a foundation for reference architecture reconstruction.
Keywords:
artificial intelligence (AI), model-based systems engineering (MBSE), entity matching
DESIGN2026 - The 19th International Design Conference
Conferences

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