The DOI matches its Crossref record; 236 of the 236 references it cites were found in a registry or an index.
Laser powder bed fusion: a state-of-the-art review of the technology, materials, properties & defects, and numerical modelling
Open accessAbstract
Additive Manufacturing (AM) has revolutionized the manufacturing industry in several directions. Laser powder bed fusion (LPBF), a powder bed fusion AM process, has been dramatically accepted in various industries due to its versatility with several materials, including alloys. This comprehensive review article primarily explains the basic principle of the LPBF process, scientific and technological progress of several inter-related parameters, feedstock materials, produced properties/defects, and insights of numerical modelling to virtually understand the process behavior. Specific attention has been given to selective laser-meted (LPBFed) properties, driven through the microstructure formations and, thereby, concerning defects. The scope of the post-processing techniques to refine microstructure has also been discussed in this review paper. It has been identified that the defects are vital in LPBF process and are primarily governed by the process parameters. Therefore, a wisely chosen, optimized set of parameters can play a crucial role in minimizing defects considerably. Finally, the numerical modeling discussed in this review paper will help the researchers understand the LPBF process.
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Cites
Additive manufacturing of metallic components – Process, structure and properties
DebRoy, T., Wei, H. L., Zuback, J. S., Mukherjee, T., Elmer, J. W., Milewski, J. O., Beese, A. M., Wilson-Heid, A., De, A., & Zhang, W. (2018) · Progress in Materials Science · doi:10.1016/j.pmatsci.2017.10.001 · Cited by 8,805
Friction stir welding and processing
Mishra, R. S., & Ma, Z. Y. (2005) · Materials Science and Engineering: R: Reports · doi:10.1016/j.mser.2005.07.001 · Cited by 6,753
Metal Additive Manufacturing: A Review
Frazier, W. E. (2014) · Journal of Materials Engineering and Performance · doi:10.1007/s11665-014-0958-z · Cited by 5,984
Ti based biomaterials, the ultimate choice for orthopaedic implants – A review
Geetha, M., Singh, A. K., Asokamani, R., & Gogia, A. K. (2009) · Progress in Materials Science · doi:10.1016/j.pmatsci.2008.06.004 · Cited by 5,416
Additive manufacturing of metals
Herzog, D., Seyda, V., Wycisk, E., & Emmelmann, C. (2016) · Acta Materialia · doi:10.1016/j.actamat.2016.07.019 · Cited by 4,759
Mordike, B. L., & Ebert, T. (2001) · Materials Science and Engineering: A · doi:10.1016/s0921-5093(00)01351-4 · Cited by 4,537
Surface modification of titanium, titanium alloys, and related materials for biomedical applications
LIU, X., CHU, P., & DING, C. (2004) · Materials Science and Engineering: R: Reports · doi:10.1016/j.mser.2004.11.001 · Cited by 3,487
Laser additive manufacturing of metallic components: materials, processes and mechanisms
Gu, D. D., Meiners, W., Wissenbach, K., & Poprawe, R. (2012) · International Materials Reviews · doi:10.1179/1743280411y.0000000014 · Cited by 3,197
A study of the microstructural evolution during selective laser melting of Ti–6Al–4V
Thijs, L., Verhaeghe, F., Craeghs, T., Humbeeck, J. V., & Kruth, J.-P. (2010) · Acta Materialia · doi:10.1016/j.actamat.2010.02.004 · Cited by 2,929
The metallurgy and processing science of metal additive manufacturing
Sames, W. J., List, F. A., Pannala, S., Dehoff, R. R., & Babu, S. S. (2016) · International Materials Reviews · doi:10.1080/09506608.2015.1116649 · Cited by 2,529
Cited by
Cortis, D., Pilone, D., Grazzi, F., Broggiato, G., Campana, F., Orlandi, D., Shinohara, T., & Planell, O. S. (2025) · Progress in Additive Manufacturing · doi:10.1007/s40964-024-00761-3 · Cited by 13
Metadata
- Authors
- Chowdhury, S., Yadaiah, N., Prakash, C., Ramakrishna, S., Dixit, S., Gupta, L. R., & Buddhi, D.
- Venue
- Journal of Materials Research and Technology
- Publisher
- Elsevier BV
- Published
- 2022-09
- Volume
- 20
- Pages
- 2109-2172
- ISSN
- 2214-0697 (ISSN-L)
- 2238-7854
- OpenAlex
- W4292448523
- Cited by
- 784
- References
- 236
- FWCI
- 48.66
- Type
- journal article
- Language
- en
- Open access
- gold
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- The paper
- Chowdhury, S., Yadaiah, N., Prakash, C., Ramakrishna, S., Dixit, S., Gupta, L. R., & Buddhi, D. (2022). Laser powder bed fusion: a state-of-the-art review of the technology, materials, properties & defects, and numerical modelling. Journal of Materials Research and Technology. https://doi.org/10.1016/j.jmrt.2022.07.121
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.