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Digitisation of metal AM for part microstructure and property control

Metal additive manufacturing, which uses a layer-by-layer approach to fabricate parts, has many potential advantages over conventional techniques, including the ability to produced complex geometries, fast new design part production, personalised production, have lower cost and produce less material...

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Autores principales: Dogu, Merve Nur, McCarthy, Eanna, McCann, Ronan, Mahato, Vivek, Caputo, Annalina, Bambach, Markus, Ahad, Inam Ul, Brabazon, Dermot
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Paris 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9015669/
https://www.ncbi.nlm.nih.gov/pubmed/35509322
http://dx.doi.org/10.1007/s12289-022-01686-4
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author Dogu, Merve Nur
McCarthy, Eanna
McCann, Ronan
Mahato, Vivek
Caputo, Annalina
Bambach, Markus
Ahad, Inam Ul
Brabazon, Dermot
author_facet Dogu, Merve Nur
McCarthy, Eanna
McCann, Ronan
Mahato, Vivek
Caputo, Annalina
Bambach, Markus
Ahad, Inam Ul
Brabazon, Dermot
author_sort Dogu, Merve Nur
collection PubMed
description Metal additive manufacturing, which uses a layer-by-layer approach to fabricate parts, has many potential advantages over conventional techniques, including the ability to produced complex geometries, fast new design part production, personalised production, have lower cost and produce less material waste. While these advantages make AM an attractive option for industry, determining process parameters which result in specific properties, such as the level of porosity and tensile strength, can be a long and costly endeavour. In this review, the state-of-the-art in the control of part properties in AM is examined, including the effect of microstructure on part properties. The simulation of microstructure formation via numerical simulation and machine learning is examined which can provide process quality control and has the potential to aid in rapid process optimisation via closed loop control. In-situ monitoring of the AM process, is also discussed as a route to enable first time right production in the AM process, along with the hybrid approach of AM fabrication with post-processing steps such as shock peening, heat treatment and rolling. At the end of the paper, an outlook is presented with a view towards potential avenues for further research required in the field of metal AM.
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spelling pubmed-90156692022-05-02 Digitisation of metal AM for part microstructure and property control Dogu, Merve Nur McCarthy, Eanna McCann, Ronan Mahato, Vivek Caputo, Annalina Bambach, Markus Ahad, Inam Ul Brabazon, Dermot Int J Mater Form ESAFORM 25 Years On Metal additive manufacturing, which uses a layer-by-layer approach to fabricate parts, has many potential advantages over conventional techniques, including the ability to produced complex geometries, fast new design part production, personalised production, have lower cost and produce less material waste. While these advantages make AM an attractive option for industry, determining process parameters which result in specific properties, such as the level of porosity and tensile strength, can be a long and costly endeavour. In this review, the state-of-the-art in the control of part properties in AM is examined, including the effect of microstructure on part properties. The simulation of microstructure formation via numerical simulation and machine learning is examined which can provide process quality control and has the potential to aid in rapid process optimisation via closed loop control. In-situ monitoring of the AM process, is also discussed as a route to enable first time right production in the AM process, along with the hybrid approach of AM fabrication with post-processing steps such as shock peening, heat treatment and rolling. At the end of the paper, an outlook is presented with a view towards potential avenues for further research required in the field of metal AM. Springer Paris 2022-04-05 2022 /pmc/articles/PMC9015669/ /pubmed/35509322 http://dx.doi.org/10.1007/s12289-022-01686-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle ESAFORM 25 Years On
Dogu, Merve Nur
McCarthy, Eanna
McCann, Ronan
Mahato, Vivek
Caputo, Annalina
Bambach, Markus
Ahad, Inam Ul
Brabazon, Dermot
Digitisation of metal AM for part microstructure and property control
title Digitisation of metal AM for part microstructure and property control
title_full Digitisation of metal AM for part microstructure and property control
title_fullStr Digitisation of metal AM for part microstructure and property control
title_full_unstemmed Digitisation of metal AM for part microstructure and property control
title_short Digitisation of metal AM for part microstructure and property control
title_sort digitisation of metal am for part microstructure and property control
topic ESAFORM 25 Years On
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9015669/
https://www.ncbi.nlm.nih.gov/pubmed/35509322
http://dx.doi.org/10.1007/s12289-022-01686-4
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