Sensing for directed energy deposition and powder bed fusion additive manufacturing at Penn State University

Abdalla R. Nassar, Edward W. Reutzel, Stephen W. Brown, John P. Morgan, Jacob P. Morgan, Donald J. Natale, Rick L. Tutwiler, David P. Feck, Jeffery C. Banks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationLaser 3D Manufacturing III
EditorsAlberto Pique, Bo Gu, Henry Helvajian
PublisherSPIE
ISBN (Electronic)9781628419733
DOIs
StatePublished - 2016
EventLaser 3D Manufacturing III - San Francisco, United States
Duration: Feb 15 2016Feb 18 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9738
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

OtherLaser 3D Manufacturing III
Country/TerritoryUnited States
CitySan Francisco
Period2/15/162/18/16

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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