Automated Image Mapping and Quantification of Microstructure Heterogeneity in Additive Manufactured Ti6Al4V

In Additive Manufacturing AM, each volume of material experiences a complex thermal history due to both short-range effects, from the repeated overlap of the thermal field from each heat source pass, and long-range variation in the thermal boundary conditions, related to the part geometry and build height. With an α + β alloy, like Ti64, this can lead to significant local variation in the transformation microstructure, which can contribute to heterogeneity in the mechanical properties of a component. In order to better understand the transformation microstructure variability in AM parts, an automated microstructure analysis tool has been developed, and tested against independently measured data, that can accurately map the inter-lamellar spacing of the α phase and spheroidicity of the β phase, at both high resolution and over large distances. The approach used was based on automated batch image analysis of thousands of image tiles obtained using a mapping function in a high-resolution SEM with a scanning stage. Within a practical operating range of drift in the microscope parameters (e.g. working distance, detector contrast) the errors in the measurements were found to be minimal (<3%). Results are discussed from applying the method to two example case studies from different ends of the AM spectrum; selective Electron Beam Melting (EBM) and Wire-Arc Additive Manufactured (WAAM). In the former case this revealed considerable drift in the microstructure with build height and geometry, but little short-range variation, whereas with the WAAM process more severe short range microstructural gradients associated with HAZ banding were fully quantified.