6 April 2016 Sensing for directed energy deposition and powder bed fusion additive manufacturing at Penn State University
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Proceedings Volume 9738, Laser 3D Manufacturing III; 97380R (2016) https://doi.org/10.1117/12.2217855
Event: SPIE LASE, 2016, San Francisco, California, United States
Abstract
Additive manufacturing of metal components through directed energy deposition or powder bed fusion is a complex undertaking, often involving hundreds or thousands of individual laser deposits. During processing, conditions may fluctuate, e.g. material feed rate, beam power, surrounding gas composition, local and global temperature, build geometry, etc., leading to unintended variations in final part geometry, microstructure and properties. To assess or control as-deposited quality, researchers have used a variety of methods, including those based on sensing of melt pool and plume emission characteristics, characteristics of powder application, and layer-wise imaging.

Here, a summary of ongoing process monitoring activities at Penn State is provided, along with a discussion of recent advancements in the area of layer-wise image acquisition and analysis during powder bed fusion processing. Specifically, methods that enable direct comparisons of CAD model, build images, and 3D micro-tomographic scan data will be covered, along with thoughts on how such analyses can be related to overall process quality.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Abdalla R. Nassar, Abdalla R. Nassar, Edward W. Reutzel, Edward W. Reutzel, Stephen W. Brown, Stephen W. Brown, John P. Morgan, John P. Morgan, Jacob P. Morgan, Jacob P. Morgan, Donald J. Natale, Donald J. Natale, Rick L. Tutwiler, Rick L. Tutwiler, David P. Feck, David P. Feck, Jeffery C. Banks, Jeffery C. Banks, "Sensing for directed energy deposition and powder bed fusion additive manufacturing at Penn State University", Proc. SPIE 9738, Laser 3D Manufacturing III, 97380R (6 April 2016); doi: 10.1117/12.2217855; https://doi.org/10.1117/12.2217855
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