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ORCID: https://orcid.org/0009-0002-0193-8183, Nørgaard, Morten
ORCID: https://orcid.org/0009-0006-4254-3486, Christensen, Carsten Keinicke Fjord
ORCID: https://orcid.org/0000-0003-2909-9940, Mortensen, Niels Henrik
ORCID: https://orcid.org/0000-0002-1886-5358 and Urueña López, Alberto
ORCID: https://orcid.org/0000-0001-8866-882X
(2025).
Why the quantification of modularity effects remains an issue for modular product families.
"Production Engineering", v. 20
(n. 27);
ISSN 18637353.
https://doi.org/10.1007/s11740-025-01412-4.
| Título: | Why the quantification of modularity effects remains an issue for modular product families |
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| Autor/es: |
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| Tipo de Documento: | Artículo |
| Título de Revista/Publicación: | Production Engineering |
| Fecha: | 29 Diciembre 2025 |
| ISSN: | 18637353 |
| Volumen: | 20 |
| Número: | 27 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Commonality; Complexity; Data quality; Data-driven design; Decision support; Design; Impact; Life cycle analysis and design; Modularity; Performance; State; System; Time |
| Escuela: | E.T.S.I. Industriales (UPM) |
| Departamento: | Ingeniería de Organización, Administración de Empresas y Estadística |
| Licencias Creative Commons: | Reconocimiento |
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This study examines the challenges regarding the quantification of modularity effects, focusing on data quality, availability, and management practices within four industrial production companies in Denmark. While the literature identifies many effects of modularity, a substantial gap persists regarding data availability and quality for accurate and practical quantification. This study reveals that less than half of the modularity-related effects have sufficient data for analysis. Furthermore, critical data such as bill-of-material have observed frequent inconsistencies with far-reaching consequences that further undermine data reliability. Silo effects also hinder knowledge sharing and limit holistic assessments of modularity effects. Traditional cost accounting methods often overlook indirect costs, leading to underestimations of modularity's economic impact, while this study finds that even direct costs lack accuracy and consistency. The results in this paper imply that the Danish industry, and likely other sectors too, may benefit from more rigorous data practices, including tracking time expenditures in overhead departments, to facilitate modularity quantification. Future research may include how accounting systems impact data management, developing structured data management frameworks, including artificial intelligence, to enhance data quality, improve quantifiability, and encourage knowledge sharing within and across departments. Ultimately, these advancements would support informed, data-driven decisions regarding modular product development and support bridging the gap between research and successful industrial application.
| ID de Registro: | 93043 |
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| Identificador DC: | https://oa.upm.es/93043/ |
| Identificador OAI: | oai:oa.upm.es:93043 |
| URL Portal Científico: | https://portalcientifico.upm.es/es/ipublic/item/10429390 |
| Identificador DOI: | 10.1007/s11740-025-01412-4 |
| URL Oficial: | https://link.springer.com/article/10.1007/s11740-0... |
| Depositado por: | iMarina Portal Científico |
| Depositado el: | 19 Ene 2026 08:11 |
| Ultima Modificación: | 19 Ene 2026 08:11 |
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