Buchenau, T., Brüning, H., & Amkreutz, M. (2022). Post-processing of surface topography data for as-built metal additive surface texture characterization. Journal of Additive Manufacturing Technologies, 2(2), 697. https://doi.org/10.18416/JAMTECH.2212697
Buchenau, T., Brüning, H., & Amkreutz, M. (2022). Post-processing of surface topography data for as-built metal additive surface texture characterization. Journal of Additive Manufacturing Technologies, 2(2), 697. https://doi.org/10.18416/JAMTECH.2212697
Buchenau, T., Brüning, H., & Amkreutz, M. (2022). Post-processing of surface topography data for as-built metal additive surface texture characterization. Journal of Additive Manufacturing Technologies, 2(2), 697. https://doi.org/10.18416/JAMTECH.2212697
Buchenau, T., Brüning, H., & Amkreutz, M. (2022). Post-processing of surface topography data for as-built metal additive surface texture characterization. Journal of Additive Manufacturing Technologies, 2(2), 697. https://doi.org/10.18416/JAMTECH.2212697
Abstract
Surfaces of additively manufactured metal parts from powder-based processes typically show powder particle agglomerations and other features, resulting in high surface roughness. Proper characterization of those surfaces is necessary in order to assess part quality with respect to coatability, mechanical performance or corrosion resistance for use in aerospace, automotive, medical and more industrial applications. Optical surface texture measurement allows for collection of areal surface data, while the established contact stylus method only captures line profile data. When applying optical methods for surface topography measurements, proper data acquisition and post-processing in order to assess surface texture may be complex. A number of variables can be adjusted, such as different measurement settings, approaches to outlier removal, evaluated area size or form removal. This work shows the influence of selected z-range prior to measurement and the influence of choosing pre-defined outlier removal settings in MountainsMap 9.2 on selected ISO 25178-2:2022 parameters calculated from data obtained from confocal microscopy for as-built Ti6Al4V from laser powder bed fusion. The aim is to show the influence of variation in measurement and post-processing on calculated surface texture parameters and stress the importance of proper documentation in order to achieve reproducibility of data for quality management.
Keywords
Metal Additive Manufacturing; Laser Powder Bed Fusion; Surface Texture Characteri-zation; Optical Metrology; Confocal Microscopy
Subject
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
