Additive manufacturing (AM) technologies show potential for the development of functionally integrated lightweight designs, biomimetic structures and material savings. Typically, as-built surfaces are characterized by powder particle agglomerations and re-entrant features, leading to a high initial surface roughness, which is associated with poor fatigue performance. In order to make use of the full range of advantages with special focus on aerospace applications, critical features for crack initiation when subjected to fatigue loading need to be identified and mitigated.

A first step toward achieving this goal is the surface texture characterization based on the quantification of surface features by means of newly defined surface feature parameters. The application of optical metrology systems to obtain areal measurements of the surfaces under consideration is beneficial as compared to the traditional stylus method, a.o. due to more representative statistital surface representation.

Selected areal parameters are evaluated for three different as-built surface conditions of aluminium alloy samples from laser powder bed fusion (LPBF).