Additively manufactured (AM) metallic sheet-based Triply Periodic Minimal Surface Structures (TPMSS) meet several requirements in both bio-medical and engineering fields: Tunable mechanical properties, low sensitivity to manufacturing defects, mechanical stability, and high energy absorption. However, they also present some challenges related to quality control. In fact, the optimization of both the AM process and the properties of TPMSS is impossible without considering structural characteristics as manufacturing accuracy, internal defects, and as well as surface topography and roughness. In this study, the quantitative non-destructive analysis of TPMSS manufactured from Ti-6Al-4V alloy by electron beam melting was performed by means of laboratory X-ray computed tomography (XCT).

Two types of gyroid TPMSS (with constant and with functionally graded porosity) were investigated. All specimens were manufactured from a Ti-6Al-4V alloy using an EBM machine by ARCAM (Mölnlycke, Sweden). XCT was performed on a microfocus X-ray tube XWT-225-SE (X-RAY WorX, Garbsen, Germany) and an XRD1620 detector (CsI scintillator, from PerkinElmer Inc.).

Several advanced image analysis workflows are presented to evaluate the effect of build orientation on wall thicknesses distribution, wall degradation, and surface roughness reduction due to chemical etching. It is shown that the manufacturing accuracy differs for the structural elements printed parallel and orthogonal to the manufactured layers. Different strategies for chemical etching show different powder removal capabilities and both lead to loss of material (i.e. gradients of the wall thickness). This affects the mechanical performance under compression (reduction of the yield stress). A positive effect of the chemical etching is the reduction of the surface roughness, which can potentially improve the fatigue properties of the components. Finally, XCT was used to correlate the amount of retained powder with the pore size of the functionally graded TPMSS, to further improve the manufacturing process.