Process-dependent deviations in surface and geometric measurements of additively manufactured and machined parts
Abstract
Accurate surface and geometric characterization of additively manufactured (AM) components remains challenging due to process-induced surface complexity. This study examines the influence of measurement technique on the evaluation of geometric deviations in Laser Powder Bed Fusion (LPBF) parts, compared with conventionally machined components. Three measurement approaches-optical scanning (OPT), X-ray computed tomography (XCT), and tactile coordinate measuring machine (CMM)-were applied to identical benchmark features, including cylindricity and flatness. The results show that measured deviations strongly depend on both the manufacturing process and the measurement method. While good agreement is observed for machined samples across all techniques, AM parts exhibit significantly larger and method-dependent deviations. Optical measurements consistently report higher form errors, mainly due to sensitivity to surface irregularities. XCT enables full-field evaluation of complex geometries, but the results are influenced by reconstruction and surface determination procedures. In contrast, CMM measurements tend to yield lower deviations, reflecting the inherent filtering effect of discrete probing. For AM features, deviation values are several times higher than those obtained from machined counterparts, with the most pronounced differences observed in cylindricity assessments. Spatial deviation maps further reveal systematic discrepancies between measurement techniques, particularly in regions characterized by pronounced surface variations. These findings demonstrate that measurement results cannot be interpreted independently of surface topography and measurement principles. The study highlights the importance of selecting appropriate metrology strategies for AM components, as the choice of measurement method directly affects the assessed geometric accuracy and its interpretation in quality control and functional performance.