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Study of the spatter distribution on the powder bed during selective laser melting AITranslate

Nanyang Technological University; Nanyang Technological University
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Publisher: Elsevier
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Abstract AITranslate

In Selective Laser Melting (SLM), inert gas is pumped into the chamber to eliminate the deleterious by-products, which includes spatter. Despite this, traces of spatter on the powder bed have always been observed. Earlier research mainly focussed on the formation and characterization of spatter particles that were freshly ejected from the melt pool. However, in this study, the quantification of the spatter distribution on the powder bed was performed, following their transport by the inert gas flow which was varied at two gas pump settings (60 and 67%). Image processing for spatter detection based on contrast was first conducted. The sieved out spatter particles were quantified by precision weighing of mass. Optical microscopy was then utilised for size determination. The majority of spatter particles were originally distributed along the −x direction, as observed from the top down images taken. It was found that spatter was generally transported in the −x direction with the mass and size gradually decreasing with distance from the scanned regions. However, increasing the gas flow velocity did not correspond to a lesser mass distribution. Computations on the Stk number revealed that at the gas pump setting of 67%, spatter particles of greater size were deposited earlier on the powder bed, suggesting that increasing the gas flow velocity to a large extent would increase the likelihood of powder bed contamination. The forward extrapolation of the exponential Stk number trendlines also elucidated the reason for the limitations on the width of the powder bed in machines designed by SLM Solutions. Graphical abstract Download : Download high-res image (206KB) Download : Download full-size image

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DOI:https://doi.org/10.1016/j.addma.2018.04.036

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Citation Information:

In Selective Laser Melting (SLM), inert gas is pumped into the chamber to eliminate the deleterious by-products, which includes spatter. Despite this, traces of spatter on the powder bed have always been observed. Earlier research mainly focussed on the formation and characterization of spatter particles that were freshly ejected from the melt pool. However, in this study, the quantification of the spatter distribution on the powder bed was performed, following their transport by the inert gas flow which was varied at two gas pump settings (60 and 67%). Image processing for spatter detection based on contrast was first conducted. The sieved out spatter particles were quantified by precision weighing of mass. Optical microscopy was then utilised for size determination. The majority of spatter particles were originally distributed along the −x direction, as observed from the top down images taken. It was found that spatter was generally transported in the −x direction with the mass and size gradually decreasing with distance from the scanned regions. However, increasing the gas flow velocity did not correspond to a lesser mass distribution. Computations on the Stk number revealed that at the gas pump setting of 67%, spatter particles of greater size were deposited earlier on the powder bed, suggesting that increasing the gas flow velocity to a large extent would increase the likelihood of powder bed contamination. The forward extrapolation of the exponential Stk number trendlines also elucidated the reason for the limitations on the width of the powder bed in machines designed by SLM Solutions. Graphical abstract Download : Download high-res image (206KB) Download : Download full-size image

quote

GB/T 7714-2015 [1] Ahmad Bin Anwar, QuangCuong Pham. Additive Manufacturing, 2018(22). DOI:10.1016/j.addma.2018.04.036.
MLA [1] Ahmad Bin Anwar, and QuangCuong Pham. Additive Manufacturing, no. 22, 2018, https://doi.org/10.1016/j.addma.2018.04.036.
APA [1] Ahmad Bin Anwar, & QuangCuong Pham. (2018). Additive Manufacturing(22). https://doi.org/10.1016/j.addma.2018.04.036
IEEE [1] Ahmad Bin Anwar and QuangCuong Pham, Additive Manufacturing, no. 22, 2018, doi: 10.1016/j.addma.2018.04.036.