As a typical laser additive manufacturing technology, laser powder bed fusion (LPBF) has achieved demonstration applications in aerospace, biomedical and other fields. However, how to select process parameters quickly and reasonably is still the main concern of LPBF production. In order to quantitatively analyze the influence of different process parameters (laser power, scanning speed, hatch space and layer thickness) on the LPBF process, the multilayer and multipath forming process of LPBF was predicted based on the opensource discrete element method framework Yade and the opensource finite volume method framework OpenFOAM. Based on the design of experiments method, a fourfactor threelevel 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 influence of laser power and scanning speed on surface roughness showed a trend of decreasing first and then increasing, while the influence of scanning distance and layer thickness on surface roughness showed a monotonous increasing trend. The order of the influence of each process parameter on porosity was:
As a typical laser additive manufacturing technology, laser powder bed fusion (LPBF) has gradually been used for direct forming of complex metal parts, and has achieved exemplary applications in aerospace, biomedical and other fields [
Regarding the influence of process parameters on the LPBF process, scholars have carried out a large number of experimental studies. Among them, the process parameters mainly include laser power [
The core of the LPBF process is that the metal particles gradually melt after being heated by the laser, and then solidify to form a solidified track. This process is a typical high temperature and high transient physical process, where the highest temperature can reach 4000
This paper was based on the opensource discrete element method (DEM) framework Yade and the opensource finite volume method (FVM) framework OpenFOAM to predict the multilayer multipath process of LPBF. In order to quantitatively analyze the effects of different process parameters (laser power, scanning speed, hatch space and layer thickness) on the porosity and surface roughness, based on the design of experiments (DOE) method, a fourfactor threelevel orthogonal test scheme was designed, and the calculated results were compared with the experimental results. This paper is expected to provide a basis for process control in actual LPBF production.
The premise of describing the LPBF process based on the mesoscopic scale is to obtain the particle distribution of the powder bed. As a numerical calculation method for solving and analyzing the motion law and mechanical characteristics of complex discrete systems, DEM can be used to characterize collision and friction behaviors in particle systems [
The way the laser energy is applied is very important to describe the LPBF process based on the mesoscopic scale. In order to ensure the reasonable application of laser energy and high calculation efficiency, the multireflection absorption effect was ignored and the “metal phasegas phase” interface was traced firstly in real time, then the elements directly acted by the laser were determined according to the laser spot center and radius. Using the elements directly acted by the laser as the starting points, the elements within a certain distance along the direction of gravity were found and marked as the elements indirectly acted by the laser, and finally the laser energy was applied in the form of a body heat source.
where,
where,
The opensource DEM framework Yade was used to calculate the spreading powder process, and the opensource FVM framework OpenFOAM was used to predict the LPBF multilayer multipath process.
The metal powder used here was 316L stainless steel, and its alloy composition (mass percentage) is: Fe 65.395%–Cr 17.0%–Ni 12.0%Mo 2.5%–Mn 2.0%–Si 1.0%–P 0.045%–C 0.03%–S 0.03%.
Parameter  Value  Unit 

Density of metal  7270  kg/m^{3} 
Specific heat of metal  790  J/(kg 
Thermal conductivity of metal  24.55  W/(m 
Solidus temperature  1658  K 
Liquidus temperature  1723  K 
Evaporation temperature  3090  K 
Latent heat of melting  J/kg  
Latent heat of gasification  J/kg  
Viscosity of liquid metal  0.00345  
Surface tension  1.6  N/m 
Temperature coefficient of surface tension  N/( 

Molecular mass  kg  
Ambient pressure  101325  Pa 
Boltzmann constant  J/K  
Emissivity  0.26  
StefanBoltzmann constant  W/(m 

Density of air  1  kg/m^{3} 
Specific heat of air  718  J/( 
Thermal conductivity of air  0.02346  W/( 
Viscosity of air 
The focus of this paper is to analyze the influence of process parameters on the LPBF multilayer multipath process based on the mesoscopic scale, and the considered process parameters include laser power, scanning speed, hatch space and layer thickness. In order to analyze the sensitivity of each process parameter, the orthogonal experiment method for the design of experiments was adopted, and
Factor level  Laser power (W)  Scanning speed (m/s)  Hatch space ( 
Layer thickness ( 

1  150  1  50  30 
2  200  1.5  60  40 
3  250  2  70  50 
Calculation scheme  Laser power  Scanning speed  Hatch space  Layer thickness 

1  level 1  level 1  level 1  level 1 
2  level 1  level 2  level 2  level 2 
3  level 1  level 3  level 3  level 3 
4  level 2  level 1  level 2  level 3 
5  level 2  level 2  level 3  level 1 
6  level 2  level 3  level 1  level 2 
7  level 3  level 1  level 3  level 2 
8  level 3  level 2  level 1  level 3 
9  level 3  level 3  level 2  level 1 
Firstly, the simulation results were illustrated. Here, calculation Scheme 1 was taken as an example.
The porosity and surface roughness of the parts are the main quality indicators of concern in actual production, so the porosity and surface roughness were token here as the extraction information of the simulation results. Taking calculation Scheme 1 as an example,
where,
Calculation scheme  Porosity (%)  Surface roughness ( 

1  4.56  2.414 
2  13.64  2.932 
3  19.43  5.830 
4  9.59  3.191 
5  8.72  3.651 
6  12.77  2.322 
7  6.41  4.591 
8  10.85  2.763 
9  7.75  2.820 
For the extraction of surface roughness data, a partial surface area (
where,
Based on the porosity and surface roughness data of each calculation scheme in
With reference to the above data analysis strategy,
Then, the degree of influence of each process parameter on porosity and surface roughness was analyzed, that is, comparing each process parameter horizontally, and ranking the influence of each process parameter on porosity and surface roughness. Taking the influence of laser power on porosity as an example, according to the data analysis strategy in the orthogonal experiment method, the range (the difference between the maximum value and the minimum value) in
Based on the opensource DEM framework Yade and the opensource FVM framework OpenFOAM, the multilayer multipath forming process of LPBF was predicted herein. In order to quantitatively analyze the influence of different process parameters (laser power, scanning speed, hatch space and layer thickness) on the LPBF process, based on the DOE method, a fourfactor threelevel 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 influence of laser power and scanning speed on surface roughness showed a trend of decreasing first and then increasing, while the influence of hatch space and layer thickness on surface roughness showed a monotonous increasing trend.
The order of the influence of each process parameter on porosity is: