Assessment of optical emission analysis for in-process monitoring of powder bed fusion additive manufacturing

Alexander J. Dunbar, Abdalla Ramadan Nassar

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Developing methods which allow real-time monitoring of powder bed fusion (PBF) additive manufacturing (AM) processes is key to enabling in situ assessments of build quality (e.g. lack of fusion and porosity). Here, we investigate the use of optical emission spectroscopy and high-speed (100 kHz) measurement of select wavelength emissions, based on a line-to-continuum approach, to determine if a correlation between PBF AM process inputs, sensor outputs, and build quality exists. Using an open protocol system interfaced with a 3D Systems ProX 200 machine, sensor data were synchronised with the scanner position and the laser state during the buildup of Inconel-718 components under varying powers, scan speeds, and hatch spacing parameters. Sensor measurements were then compared against post-build computed tomography scans. We show evidence that sensor data, when combined with appropriate analyses, are related to both processing conditions and build quality.

Original languageEnglish (US)
Pages (from-to)14-19
Number of pages6
JournalVirtual and Physical Prototyping
Volume13
Issue number1
DOIs
StatePublished - Jan 2 2018

Fingerprint

3D printers
Process Monitoring
Process monitoring
Powder
Fusion
Fusion reactions
Manufacturing
Powders
Sensor
Sensors
Hatches
Optical emission spectroscopy
Computed Tomography
Scanner
Porosity
Spacing
Tomography
Spectroscopy
Continuum
High Speed

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Modeling and Simulation
  • Computer Graphics and Computer-Aided Design
  • Industrial and Manufacturing Engineering

Cite this

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Assessment of optical emission analysis for in-process monitoring of powder bed fusion additive manufacturing. / Dunbar, Alexander J.; Nassar, Abdalla Ramadan.

In: Virtual and Physical Prototyping, Vol. 13, No. 1, 02.01.2018, p. 14-19.

Research output: Contribution to journalArticle

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