Resources / Publications
Christopher Ledford (1), Mouda Tung (1), Chris Rock (1), Timothy Horn (1,2)
Additive Manufacturing, 34, June 2020. DOI: 10.1016/j.addma.2020.101365
Real-time control, Electron beam, In-situ monitoring, Defect detection, Backscatter
Real-time monitoring of electron emissions during the operable processing steps of electron beam powder bed fusion (EB-PBF), which typically include preheating, melting, and post-heating, provides a wealth of in-process data across multiple length scales. In this paper, we present a methodology for collecting both real-time beam positional data and electron emissions as a function of time for arbitrary component geometries and complex toolpaths. To demonstrate this, we collected these data during the melting steps of EB-PBF of pure copper and quantitatively compared electron images generated with this approach to both x-ray micro computed tomography (μCT) data and optical micrographs of the same specimens. These results show a strong mathematical correlation between the location of loss of signal events observed in electron images and observed defects in μCT. At the same time, the collection of beam positional information facilitates the calculation of beam velocities, and hence local energy inputs. We also demonstrate a to methodology visualize process data from a wide variety of sources and map these over the 3D geometries as a function of time and position and to link these spatiotemporal data to structure observed in the electron imaging and energy input maps. Ultimately, we have leveraged this new electron imaging approach to defect detection into a rudimentary control strategy to eliminate porosity in a copper sample.
Dragonfly was used for the 3D visualization of sample porosity.
(1) Center for Additive Manufacturing and Logistics, North Carolina State University, 126 Daniels Hall, Raleigh, NC 27695-7906, USA.
(2) Department of Mechanical and Aerospace Engineering, North Carolina State University, Campus Box 7910, Raleigh, NC 27695-7910, USA.
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