Abstract
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.
Original language | English |
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Article number | 101365 |
Journal | Additive Manufacturing |
Volume | 34 |
DOIs | |
State | Published - Aug 2020 |
Externally published | Yes |
Funding
Some of the samples shown in this study for demonstration were produced under, and partially funded by the Navy Sea Systems Command Contract Number N0025316P0261 Funding for this reseach was provided by the Center for Additive Manufacturing and Logistics, North Carolina State University.This work was performed in part at the Analytical Instrumentation Facility (AIF) at North Carolina State University, which is supported by the State of North Carolina and the National Science Foundation (award number ECCS-1542015). The AIF is a member of the North Carolina Research Triangle Nanotechnology Network (RTNN), a site in the National Nanotechnology Coordinated Infrastructure (NNCI). High speed videos were acquired with the assistance of Dr. Mark Pankow and the Ballistic Loading and Structural Testing Lab (BLAST), Department of Mechanical and Aerospace Engineering, NC State University. Some of the samples shown in this study for demonstration were produced under, and partially funded by the Navy Sea Systems Command Contract Number N0025316P0261 Funding for this reseach was provided by the C enter for Additive Manufacturing and Logistics, North Carolina State University . This work was performed in part at the Analytical Instrumentation Facility (AIF) at North Carolina State University, which is supported by the State of North Carolina and the National Science Foundation (award number ECCS-1542015). The AIF is a member of the North Carolina Research Triangle Nanotechnology Network (RTNN), a site in the National Nanotechnology Coordinated Infrastructure (NNCI). High speed videos were acquired with the assistance of Dr. Mark Pankow and the Ballistic Loading and Structural Testing Lab (BLAST), Department of Mechanical and Aerospace Engineering, NC State University.
Funders | Funder number |
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Ballistic Loading and Structural Testing Lab | |
C enter for Additive Manufacturing and Logistics | |
Center for Additive Manufacturing and Logistics | |
Department of Mechanical and Aerospace Engineering | |
National Science Foundation | ECCS-1542015 |
North Carolina State University | |
Naval Sea Systems Command |
Keywords
- Backscatter
- Defect detection
- Electron beam
- In-situ monitoring
- Real-time control