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Multiscale Data Treatment in Additive Manufacturing

The article assesses the impact of data treatment on the possibility of assessing the morphological features of additively manufactured spherical surfaces. Tests were carried out on specimens manufactured by PBF-LB/M additive technology, using titanium-powder-based material (Ti6Al4V). The surface to...

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Autor principal: Gogolewski, Damian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143087/
https://www.ncbi.nlm.nih.gov/pubmed/37110003
http://dx.doi.org/10.3390/ma16083168
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author Gogolewski, Damian
author_facet Gogolewski, Damian
author_sort Gogolewski, Damian
collection PubMed
description The article assesses the impact of data treatment on the possibility of assessing the morphological features of additively manufactured spherical surfaces. Tests were carried out on specimens manufactured by PBF-LB/M additive technology, using titanium-powder-based material (Ti6Al4V). The surface topography was assessed using one of the multiscale methods—wavelet transformation. The tests carried out on a wide spectrum of mother wavelet forms emphasized the occurrence of characteristic morphological features on the surface of the tested specimens. Moreover, the significance of the impact of specific metrology operations, measurement data processing and its parameters on the filtration result were noted. Comprehensive assessment of additively manufactured spherical surfaces with simultaneous analysis of the impact of measurement data processing is a novelty and fills a research gap relating to comprehensive surface diagnostics. The research contributes to the development of modern diagnostic systems allowing for a fast and comprehensive assessment of surface topography, taking into account the various stages of data analysis.
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spelling pubmed-101430872023-04-29 Multiscale Data Treatment in Additive Manufacturing Gogolewski, Damian Materials (Basel) Article The article assesses the impact of data treatment on the possibility of assessing the morphological features of additively manufactured spherical surfaces. Tests were carried out on specimens manufactured by PBF-LB/M additive technology, using titanium-powder-based material (Ti6Al4V). The surface topography was assessed using one of the multiscale methods—wavelet transformation. The tests carried out on a wide spectrum of mother wavelet forms emphasized the occurrence of characteristic morphological features on the surface of the tested specimens. Moreover, the significance of the impact of specific metrology operations, measurement data processing and its parameters on the filtration result were noted. Comprehensive assessment of additively manufactured spherical surfaces with simultaneous analysis of the impact of measurement data processing is a novelty and fills a research gap relating to comprehensive surface diagnostics. The research contributes to the development of modern diagnostic systems allowing for a fast and comprehensive assessment of surface topography, taking into account the various stages of data analysis. MDPI 2023-04-17 /pmc/articles/PMC10143087/ /pubmed/37110003 http://dx.doi.org/10.3390/ma16083168 Text en © 2023 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gogolewski, Damian
Multiscale Data Treatment in Additive Manufacturing
title Multiscale Data Treatment in Additive Manufacturing
title_full Multiscale Data Treatment in Additive Manufacturing
title_fullStr Multiscale Data Treatment in Additive Manufacturing
title_full_unstemmed Multiscale Data Treatment in Additive Manufacturing
title_short Multiscale Data Treatment in Additive Manufacturing
title_sort multiscale data treatment in additive manufacturing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143087/
https://www.ncbi.nlm.nih.gov/pubmed/37110003
http://dx.doi.org/10.3390/ma16083168
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