Abstract
Electron beam based additive manufacturing (AM) with copper must consider the high intrinsic thermal conductivity of copper as well as the greater difference between the thermal properties of the AM article and the surrounding or underlying powder bed. Successful processing requires multi-step control of the beam-bed interactions driven by a combination of a priori calculations and real-time monitoring and feedback to achieve melt pool size stability and appropriate bed/article temperatures as thermal boundary conditions vary based on geometry. The objective of this work is to utilize electron imaging to rapidly assess the processing space for copper with a wide shift in thermal boundary conditions using samples with overhang features. A modified commercial Arcam EBM AM system and process parameter space are described that allow successful AM of copper for complex geometries.
| Original language | English |
|---|---|
| Pages (from-to) | 828-838 |
| Number of pages | 11 |
| Journal | Procedia Manufacturing |
| Volume | 48 |
| DOIs | |
| State | Published - 2020 |
| Externally published | Yes |
| Event | 48th SME North American Manufacturing Research Conference, NAMRC 48 - Cincinnati, United States Duration: Jun 22 2020 → Jun 26 2020 |
Funding
Funding: The experiments that were carried out in this study were partially enabled by funding provided by General Motors Corporation. nI -situ backscatter detection was developed under funding by Navy Sea System Command Contract Number N0025316P0261 . Part of this orkw was performed in part at the Analytical Instrumentation Facility (AI) F at North Carolina State University, which is supported by the State of North Carolina and the National Science oundF ation (award number ECCS -1542015). The AIF is a member of the N orth Carolina Research Triangle Nanotechnology Network (RTNN), a site in the National Nanotechnology Coordinated Infrastructure (NNCI). We also acknowledge the contributions of Dr. Diana Gamzina (SLAC, National Accelerator Laboratory) Pedro Frigola and Pa ul Carriere of adiabeamR Technologies, Mike Kirka, Ryan Dehoff (Oak Ridge National aboratoL ry Manufacturing Demonstration Facility) Harvey West and Mohammed Zikry of NC State University and Victoria Miller of Florida State University. The experiments that were carried out in this study were partially enabled by funding provided by General Motors Corporation. In-situ backscatter detection was developed under funding by Navy Sea System Command Contract Number N0025316P0261. Part of 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). We also acknowledge the contributions of Dr. Diana Gamzina (SLAC, National Accelerator Laboratory) Pedro Frigola and Paul Carriere of Radiabeam Technologies, Mike Kirka, Ryan Dehoff (Oak Ridge National Laboratory Manufacturing Demonstration Facility) Harvey West and Mohammed Zikry of NC State University and Victoria Miller of Florida State University.