Abstract
<title>Abstract</title> <p>Geometric inspection of parts produced by metal additive manufacturing is of paramount importance, as temperature differences during the manufacturing process can cause internal residual stresses, global deformation, and local shape deviations. In this study, two optical 3D scanning approaches based on different acquisition principles were compared: an automated robot-assisted structured-light system and a handheld blue-laser scanning system. The aim was to examine their applicability and practical limitations in identifying and quantifying the geometric characteristics of a deformed metal additively manufactured component. The dataset acquired by the automated structured-light system was used as the comparison reference. A twin-cantilever test specimen made of 1.2709-grade tool steel was investigated after one side had been partially separated from the base plate using wire electrical discharge machining. The datasets were aligned using a local best-fit procedure based on three planar surfaces of the base plate, followed by full-surface and local deviation analyses. The automated structured-light measurement comprised 1,733,820 surface points, whereas the handheld laser measurement comprised 617,913 surface points. Both approaches represented the global deformation pattern similarly, and the flatness of the upper surface was 0.51 mm and 0.52 mm, respectively. The largest deviations were concentrated around edges, corners, and small geometric details. The handheld laser scanning approach was suitable for identifying global deformation patterns, while the automated structured-light system provided a denser and more detailed representation of fine local features.</p>