TY - JOUR
T1 - A comprehensive study on meltpool depth in laser-based powder bed fusion of Inconel 718
AU - Khorasani, Mahyar
AU - Ghasemi, Amir Hossein
AU - Leary, Martin
AU - Cordova, Laura
AU - Sharabian, Elmira
AU - Farabi, Ehsan
AU - Gibson, Ian
AU - Brandt, Milan
AU - Rolfe, Bernard
N1 - Funding Information:
The authors acknowledge Dr. Luke Scime for his supports and help on experimental verifications. All the authors have read and approved the presented materials in the paper and acknowledged the received supports.
Publisher Copyright:
© 2022, The Author(s).
Financial transaction number:
342215086
PY - 2022/5
Y1 - 2022/5
N2 - One problematic task in the laser-based powder bed fusion (LB-PBF) process is the estimation of meltpool depth, which is a function of the process parameters and thermophysical properties of the materials. In this research, the effective factors that drive the meltpool depth such as optical penetration depth, angle of incidence, the ratio of laser power to scan speed, surface properties and plasma formation are discussed. The model is useful to estimate the meltpool depth for various manufacturing conditions. A proposed methodology is based on the simulation of a set of process parameters to obtain the variation of meltpool depth and temperature, followed by validation with reference to experimental test data. Numerical simulation of the LB-PBF process was performed using the computational scientific tool “Flow3D Version 11.2” to obtain the meltpool features. The simulation data was then developed into a predictive analytical model for meltpool depth and temperature based on the thermophysical powder properties and associated parameters. The novelty and contribution of this research are characterising the fundamental governing factors on meltpool depth and developing an analytical model based on process parameters and powder properties. The predictor model helps to accurately estimate the meltpool depth which is important and has to be sufficient to effectively fuse the powder to the build plate or the previously solidified layers ensuring proper bonding quality. Results showed that the developed analytical model has a high accuracy to predict the meltpool depth. The model is useful to rapidly estimate the optimal process window before setting up the manufacturing tasks and can therefore save on lead-time and cost. This methodology is generally applied to Inconel 718 processing and is generalisable for any powder of interest. The discussions identified how the effective physical factors govern the induced heat versus meltpool depth which can affect the bonding and the quality of LB-PBF components.
AB - One problematic task in the laser-based powder bed fusion (LB-PBF) process is the estimation of meltpool depth, which is a function of the process parameters and thermophysical properties of the materials. In this research, the effective factors that drive the meltpool depth such as optical penetration depth, angle of incidence, the ratio of laser power to scan speed, surface properties and plasma formation are discussed. The model is useful to estimate the meltpool depth for various manufacturing conditions. A proposed methodology is based on the simulation of a set of process parameters to obtain the variation of meltpool depth and temperature, followed by validation with reference to experimental test data. Numerical simulation of the LB-PBF process was performed using the computational scientific tool “Flow3D Version 11.2” to obtain the meltpool features. The simulation data was then developed into a predictive analytical model for meltpool depth and temperature based on the thermophysical powder properties and associated parameters. The novelty and contribution of this research are characterising the fundamental governing factors on meltpool depth and developing an analytical model based on process parameters and powder properties. The predictor model helps to accurately estimate the meltpool depth which is important and has to be sufficient to effectively fuse the powder to the build plate or the previously solidified layers ensuring proper bonding quality. Results showed that the developed analytical model has a high accuracy to predict the meltpool depth. The model is useful to rapidly estimate the optimal process window before setting up the manufacturing tasks and can therefore save on lead-time and cost. This methodology is generally applied to Inconel 718 processing and is generalisable for any powder of interest. The discussions identified how the effective physical factors govern the induced heat versus meltpool depth which can affect the bonding and the quality of LB-PBF components.
KW - Additive manufacturing
KW - Laser irradiation
KW - Laser-based powder bed fusion
KW - Meltpool depth
KW - Wavelength
UR - http://www.scopus.com/inward/record.url?scp=85124991461&partnerID=8YFLogxK
U2 - 10.1007/s00170-021-08618-7
DO - 10.1007/s00170-021-08618-7
M3 - Article
AN - SCOPUS:85124991461
SN - 0268-3768
VL - 120
SP - 2345
EP - 2362
JO - International journal of advanced manufacturing technology
JF - International journal of advanced manufacturing technology
IS - 3-4
ER -
