Correlating volume and surface features in additively manufactured metal parts
Start: October 2019
Student: Afaf Remani
Supervisors: Richard Leach, Adam Thompson
Funding: University of Nottingham, Renishaw and Self
Metal additively manufactured (AM) parts, particularly those produced using laser-based powder bed fusion (L-PBF), lack sufficient quality assurance. In L-PBF notable barriers exist towards the adoption of AM technologies in industry, the most significant of which relates to requirements for further understanding of AM processes
In light of this issue, we adopt a qualify-as-you-build approach in which the L-PBF process is monitored layer by layer, throughout the fabrication of a part. The aim of the project is to gain a better understanding of the dynamics and phenomena that occur during the L-PBF process and categorise defects that are acceptable versus those whose presence is significantly detrimental to the final part. In this project, we will use fringe projection and other in-process monitoring systems to achieve layerwise topography monitoring. The main expected outcome of this work is to qualitatively and quantitatively discern the surface features present within and around the melt pool in each layer, in search for defects and process signatures. Using this information, we will render conclusive correlations between these aspects of the build and mechanical properties. Layerwise data will be compared to volumetric X-ray computed tomography data to check and validate obtained results. It is expected that, by the end of this project, a fully operational in situ topography monitoring system will be delivered for inclusion in a commercial L-PBF machine.