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In-situ sensing, process monitoring and machine control in Laser Powder Bed Fusion: a review

McCann, Ronán orcid logoORCID: 0000-0002-2071-0785, Ahmed Obeidi, Muhannad orcid logoORCID: 0000-0003-2733-3828, Hughes, Cian orcid logoORCID: 0000-0002-4863-733X, McCarthy, Éanna, Egan, Darragh orcid logoORCID: 0000-0003-2786-7379, Vijayaraghavan, Rajani K. orcid logoORCID: 0000-0003-1096-448X, Joshi, Ajey orcid logoORCID: 0000-0003-3120-886X, Acinas Garzon, Victor, Dowling, Denis P. orcid logoORCID: 0000-0001-7853-2478, McNally, Patrick J. orcid logoORCID: 0000-0003-2798-5121 and Brabazon, Dermot orcid logoORCID: 0000-0003-3214-6381 (2021) In-situ sensing, process monitoring and machine control in Laser Powder Bed Fusion: a review. Additive Manufacturing, 45 . ISSN 2214-8604

Process monitoring and sensing is widely used across many industries for quality assurance, and for increasing machine uptime and reliability. Though still in the emergent stages, process monitoring is beginning to see strong adoption in the additive manufacturing community through the use of process sensors recording a wide range of optical, acoustic and thermal signals. The ability to acquire these signals in a holistic manner, coupled with intelligence-based machine control has the potential to make additive manufacturing a robust and competitive alternative to conventional fabrication techniques. This paper presents an overview of the state-of the art of in-situ process monitoring in laser powder bed fusion processes and highlights some current limitations and areas for advancement. Also presented is an overview of real-time process control requirements, which when combined with the emergent process monitoring tools, will eventually allow for in-depth process control of the powder bed fusion process, which is essential for wide-scale industrial credibility and adoption of this technology.
Item Type:Article (Published)
Additional Information:Article number: 102058
Uncontrolled Keywords:Additive manufacturing; Powder bed fusion; Process sensing; Machine control; Smart manufacturing; Selective laser melting; Electron beam melting; Industry 4.0; In-situ monitoring
Subjects:Computer Science > Image processing
Computer Science > Machine learning
Engineering > Acoustical engineering
Engineering > Control theory
Engineering > Imaging systems
Engineering > Materials
Engineering > Mechanical engineering
Engineering > Signal processing
Engineering > Systems engineering
Physical Sciences > Laser plasmas
Physical Sciences > Lasers
Physical Sciences > Photonics
Physical Sciences > Physics
Physical Sciences > Plasmas
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Mechanical and Manufacturing Engineering
Research Institutes and Centres > National Centre for Plasma Science and Technology (NCPST)
Research Institutes and Centres > Advanced Processing Technology Research Centre (APTRC)
Research Institutes and Centres > I-Form
Official URL:https://dx.doi.org/10.1016/j.addma.2021.102058
Copyright Information:© 2021 The Authors. Open Access (CC-BY-4.0)
Funders:Science Foundation Ireland (16/RC/3872), European Union’s Horizon 2020 Research and Innovation Programme (862000)
ID Code:25994
Deposited On:11 Jun 2021 10:58 by Ronan Mccann . Last Modified 20 May 2022 16:34

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