Mesoscopic-Scale Numerical Investigation Including the Inuence of Process Parameters on LPBFMulti-Layer Multi-Path Formation

Abstract

As a typical laser additive manufacturing technology, laser powder bed fusion (LPBF) has achieved demonstration applications in aerospace, biomedical and other elds. However, how to select process parameters quickly and reasonably is still the main concern of LPBF production. In order to quantitatively analyze the in uence of di erent process parameters (laser power, scanning speed, hatch space and layer thickness) on the LPBF process, the multilayer and multi-path forming process of LPBF was predicted based on the open-source discrete element method framework Yade and the open-source nite volume method framework OpenFOAM. Based on the design of experiments method, a four-factor three-level orthogonal test scheme was designed, and the porosity and surface roughness data of each calculation scheme were extracted. By analyzing the orthogonal test data, it was found that as the laser power increased, the porosity decreased, and as the scanning speed, hatch space, and layer thickness increased, the porosity increased. In addition, the in uence of laser power and scanning speed on surface roughness showed a trend of decreasing rst and then increasing, while the in uence of scanning distance and layer thickness on surface roughness showed a monotonous increasing trend. The order of the in uence of each process parameter on porosity was: scanning speed > laying thickness > laser power > hatch space, and the order of the in uence of each process parameter on surface roughness was: hatch space > layer thickness > laser power > scanning speed. So the porosity of the part is most sensitive to scanning speed, and the surface roughness is the most sensitive to hatch space. The above conclusions are expected to provide process control basis for actual LPBF production of the 316L stainless steel alloy.

Laser Powder Bed Fusion: Exploring Recent Technological Breakthroughs and Alloy Utilization

“…Laser power directly affects the energy input into the powder bed, influencing the melting and solidification process [16]. Higher laser power can lead to faster melting and deeper penetration into the powder bed [17][18][19][20]. Scanning speed determines the rate at which the laser moves over the powder bed, impacting the cooling rate and microstructural characteristics of the manufactured parts.…”

Additively manufactured metallic biomaterials

“…The process is implemented in an inert gas chamber, usually argon or nitrogen, to remove the condensate, reduce oxidation throughout the process, and prevent the potential explosion of powders due to high localized temperature. The AM quality can be tuned by the processing parameters including laser power, scanning speed, hatching spacing, layer thickness, post exposure, pre-exposure, and many more parameters [ 21 ] which entails an optimization process depending on the target application to obtain the desired mechanical properties, surface roughness, and geometrical accuracy [ 22 , 23 ]. The minimum geometrical feature size formed by the LPBF process ranges between 40 and 200 μm [ 24 ].…”

Introduction to the Special Issue on Design and Simulation in AdditiveManufacturing

“…SLM has achieved demonstration applications in some high-tech elds, but the optimization of process parameters is still the main concern of SLM production. Based on the open-source discrete element method (DEM) framework Yade and the open-source nite volume method (FVM) framework OpenFOAM, Cao [9] predicted the multi-layer multi-path process of SLM, and quantitatively analyzed the in uence of process parameters (including laser power, scanning speed, hatch space and layer thickness) on the porosity and surface roughness. This new forecasting method is expected to provide a basis for process control in actual SLM production.…”