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Empirical estimation of metal powder bed fusion technological improvement rate

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Author(s)
Alves de Campos, António
•
Torres Ferreira, Bruna
•
Gonçalves, Afonso
•
Leite, Marco
•
Ribeiro, Inês
•
L. Magee, Christopher
•
Henriques, Elsa
Date Issued
October 22, 2024
Journal
Progress in Additive Manufacturing
Publisher
Springer International Publishing
Citation
Alves de Campos, A., Torres Ferreira, B., Gonçalves, A. et al. Empirical estimation of metal powder bed fusion technological improvement rate. Prog Addit Manuf (2024).
Version
Final published version
Abstract
This study empirically estimates the technological improvement rate (TIR) of metal powder bed fusion (PBF) technology, widely used in aerospace, automotive, and medical industries. PBF's continuous long-term adoption growth is driven by its ability to enhance manufacturing efficiency in terms of time and raw material use, as well as its capability to produce high-quality, high-strength, complex-shaped parts. Measuring the technological development of PBF is crucial as itis enlarging its application domain and is increasingly considered a viable alternative to traditional manufacturing technologies across a broader range of applications. We resorted to the literature to collect information and assess which technical parameters are most relevant to measure the capabilities of PBF. With those, we established an ideal functional performance metric (FPM) capable of comprehensively assessing PBF's technological performance improvement. Considering all available data sources and PBF machines ever made commercially available, a data set of technical parameters was constructed. This was followed by a data curation process focusing on data availability and reliability. The resultant practical FPM was used to estimate the TIR of PBF technology. By employing regression analysis, we estimate a yearly improvement of 26.8%. This empirical rate comes as a more accurate and reliable substitute to the previously indirectly estimated patent-derived rate of 33.3%. Our findings underscore PBF's capability of keeping pace with its growing significance and wider industrial applications. The results of this study provide a key metric for those in the industry and research, confirming the rapid performance growth and establishing a standard for future industrial uses.
MIT Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
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Creative Commons Attribution
https://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/157446
DOI of Published Version
https://doi.org/10.1007/s40964-024-00813-8
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