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A maturity assessment model for metal additive manufacturing: additive manufacturing readiness levels
Terrenoir, Laurent Laguna Salvadó, Laura Lartigau, Julie Merlo, Christophe
Terrenoir, Laurent
Laguna Salvadó, Laura
Lartigau, Julie
Merlo, Christophe
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2025-10-15
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Abstract
Despite many promises, metal additive manufacturing (MAM) adoption is still limited within the industry. To effectively and successfully implement MAM, companies need to assess their maturity status quo, combined with the MAM technology maturity, at both organisational and operational levels. However, existing maturity models (MMs) are either only dedicated to just one of these levels or are not adapted to MAM. Thus, this paper proposes an original and tailored MM: the Additive Manufacturing Readiness Levels (AMRL), a multicriteria MM to evaluate the maturity of a MAM technology coupled with a use case, offering a context-aware approach that bridges technological capability and operational applicability. The model features 8 dimensions, divided into 22 sub-items to be assessed, referring to Industry 5.0 pillars, including environmental and social considerations. To develop and validate the proposal, an iterative methodology is followed where the AMRL is applied to compare the maturity of three Directed Energy Deposition technologies coupled with nine use cases in the context of a French Technology Transfer Centre. Direct interviews with experts and measures of agreement granted validation. AMRL aims to contribute to the adoption of MAM by assisting decision makers. Future research could investigate its use in different industry sectors and decision configurations.
Citation
Terrenoir, L., Laguna Salvadó, L., Lartigau, J., Arjunan, A. and Merlo, C. (2025) A maturity assessment model for metal additive manufacturing: additive manufacturing readiness levels. International Journal of Production Research. DOI: 10.1080/00207543.2025.2571203
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Journal article
Language
en
Description
This is an author's accepted manuscript of an article published by Taylor & Francis on 25/10/2025, available online: https://doi.org/10.1080/00207543.2025.2571203
The accepted mansucript may differ from the final published version.
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0020-7543
EISSN
1366-588X
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Sponsors
This research was conducted with support from ESTIA, France, the University of Wolverhampton, UK. This research project was undertaken with the assistance of resources and services from the ADDIMADOUR platform, Additive Manufacturing Solutions.