Electron Beam Melting (EBM) is an Additive Manufacturing technique to produce functional components. Because of the high temperature during the EBM process, the surface texture of the as-built parts is extremely complex and unique. This distinctiveness of the surface depends on many factors and needs to be well understood to predict final surface properties accurately. Chief among these factors is the surface design. A proper surface design makes it possible to tailor a surface with specific properties such as biomimetics. However, predictive models are difficult to determine especially for downskin surfaces. To properly tailor a surface, a full factorial Design Of Experiment (DOE) was designed, and 2D and 3D roughness profiles were collected on an ad-hoc artefact using a profilometer and a confocal profilometer. This reference part comprises several surfaces to investigate the effect on surface roughness of different sloping angles, including upskin and downskin surfaces and cavities. The data are analysed using descriptive and inferential statistical tools, also by distinguishing the role of roughness and waviness in the overall surface texture. A deep investigation of the causes of surface roughness made it possible to obtain analytical predictive models. These models are robust and consistent with respect to the experimental observations. Finally, the accurate design of the artefact allows highlighting the relationship between the roughness and the surface slope.

Surface roughness prediction model for Electron Beam Melting ({EBM}) processing Ti6Al4V / Galati, Manuela; Rizza, Giovanni; Defanti, Silvio; Denti, Lucia. - In: PRECISION ENGINEERING. - ISSN 0141-6359. - ELETTRONICO. - 69:(2021), pp. 19-28. [10.1016/j.precisioneng.2021.01.002]

Surface roughness prediction model for Electron Beam Melting ({EBM}) processing Ti6Al4V

Manuela Galati;Giovanni Rizza;
2021

Abstract

Electron Beam Melting (EBM) is an Additive Manufacturing technique to produce functional components. Because of the high temperature during the EBM process, the surface texture of the as-built parts is extremely complex and unique. This distinctiveness of the surface depends on many factors and needs to be well understood to predict final surface properties accurately. Chief among these factors is the surface design. A proper surface design makes it possible to tailor a surface with specific properties such as biomimetics. However, predictive models are difficult to determine especially for downskin surfaces. To properly tailor a surface, a full factorial Design Of Experiment (DOE) was designed, and 2D and 3D roughness profiles were collected on an ad-hoc artefact using a profilometer and a confocal profilometer. This reference part comprises several surfaces to investigate the effect on surface roughness of different sloping angles, including upskin and downskin surfaces and cavities. The data are analysed using descriptive and inferential statistical tools, also by distinguishing the role of roughness and waviness in the overall surface texture. A deep investigation of the causes of surface roughness made it possible to obtain analytical predictive models. These models are robust and consistent with respect to the experimental observations. Finally, the accurate design of the artefact allows highlighting the relationship between the roughness and the surface slope.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2869506