In-situ optical emission spectroscopy of selective laser melting
The variances in local processing conditions during Selective Laser Melting (SLM), a powder bed Additive Manufacturing (AM) process, can cause defects that lead to part failure. The nature of SLM permits in-situ monitoring of radiometric signals emitted from the part surface during the process, incl...
Saved in:
Published in | Journal of manufacturing processes Vol. 53; pp. 336 - 341 |
---|---|
Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.05.2020
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | The variances in local processing conditions during Selective Laser Melting (SLM), a powder bed Additive Manufacturing (AM) process, can cause defects that lead to part failure. The nature of SLM permits in-situ monitoring of radiometric signals emitted from the part surface during the process, including optical emission from excited alloying elements. Using Optical Emission Spectroscopy (OES) to measure the spectral content of light emitted gives insight into the chemistry and relative intensities of excited species vaporized during SLM processing. The contribution from investigating the use of in-situ OES to gain information about local processing conditions during SLM is reported in this paper. A spectrometer is split into the SLM system laser beam path to measure visible light emitted from the melt pool and plume during the processing of 304L stainless steel. The in-line configuration allows signal collection regardless of the laser scan location. The spectroscopic information is correlated to the melt pool size and features of SLM samples for various build conditions (i.e., process parameters, build chamber atmosphere type, and pressure).The limitations that exist in OES implementation for certain build chamber conditions are discussed. The results in this paper are initial progress towards the use of OES in SLM part qualification and controls applications. |
---|---|
ISSN: | 1526-6125 2212-4616 |
DOI: | 10.1016/j.jmapro.2020.02.016 |