Computational modeling of heat transfer and sintering behavior during direct metal laser sintering of AlSi10Mg alloy powder

Abstract

Direct Metal Laser Sintering (DMLS) is one of the leading additive manufacturing processes, which produces complex metallic parts directly from the powder. One of the major problems of this rapid manufacturing process is an inhomogeneous temperature distribution, which leads to residual stress in the build part. Thus, temperature analyses must be performed, to better understand the temperature distribution and sintering behavior of the powder bed with a different laser recipe. In this study, a comprehensive three-dimensional numerical model was developed to understand the temperature distribution during direct metal laser sintering of AlSi10Mg alloy powder. The computer simulation was carried out in ANSYS 17.0 platform. Further, the effect of process parameters such as laser power and scan speed on the temperature distribution and sintering behavior were studied. From the simulation results, it was found that, when the laser power increased from 70 W to 190 W, the maximum temperature of the molten pool increased from 731 • C to 2672 • C, and the molten pool length changed from 0.286 mm to 2.167 mm. A reverse phenomenon was observed with an increase in scan speed. The sintering depth of the powder layer increases significantly from 0.061 mm to 0.872 mm with increasing the applied laser power, but decreased from 0.973 mm to 0.209 mm as a higher scan speed was applied. The developed model helps to optimize the powder layer thickness and minimize the wastage of excess powders during the sintering process.

Modeling residual thermal stresses in layer-by-layer formation of direct metal laser sintering process for different scanning patterns for 316L stainless steel

“…The powder bed is assumed to be a continuous medium because of the small size (approximately 20 mm) of the metal powder, and thus, the effect of the porosity of the metal powder on thermal properties is assumed to be negligible because of its particle size. Other studies have used this approximation (Nazami et al, 2021;Panda and Sahoo, 2018;Samantaray et al, 2018) and this has been experimentally corroborated in Koh and Fortini (1973), which observed that for materials with high thermal conductivities, the ratio of powder to solid conductivity remains unaffected by temperature. The thermophysical properties of the metal powder used for this study, SS 316 L (Valencia and Quested, 2008), are listed in Table 1.…”

Processing and characterization of aluminium alloy 6061 graphene composite printed by direct metal laser sintering

“…Reason for 200 mm/s and 30 lm shows highest hardness is due to two different conditions one is that is get reinforced by Graphene (2 wt%) and other is scanning speed of printing [8,[15][16][17]. DMLS process at higher scanning speed, the time for recrystallization of the grains is observed to be less and thus the solidification occurred at very quickly which leads to creation of very small grain size [16][17][18]. From Fig.…”

“…From the graph of both Rockwell as well as Vickers hardness graph sample of 200 mm/s and 30 lm shows higher hardness than the two other while sample 200 mm/s and 30 lm comes in between the other two. Reason for 200 mm/s and 30 lm shows highest hardness is due to two different conditions one is that is get reinforced by Graphene (2 wt%) and other is scanning speed of printing [8,[15][16][17]. DMLS process at higher scanning speed, the time for recrystallization of the grains is observed to be less and thus the solidification occurred at very quickly which leads to creation of very small grain size [16][17][18].…”

Computational modelling of process–structure–property–performance relationships in metal additive manufacturing: a review

“…Post-processing is required for secondary purposes because using low-power lasers to bind powder particles only melts the surface of the powder particles. AM process parameters such as laser power [108], scan speed [108], scan length [109], powder function [110], geometry [111], and distribution [112] are the 'inputs' that primarily determine the rate of energy delivered to the surface of the powder and how that energy interacts with the material. Process effects significantly influence final product qualities.…”