scholarly journals Elucidating the effect of preheating temperature on melt pool morphology variation in Inconel 718 laser powder bed fusion via simulation and experiment

2020 ◽  
pp. 101642
Author(s):  
Qian Chen ◽  
Yunhao Zhao ◽  
Seth Strayer ◽  
Yufan Zhao ◽  
Kenta Aoyagi ◽  
...  
Keyword(s):  
Inconel 718 ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Preheating Temperature ◽  
Simulation And Experiment

scholarly journals Microstructure and Residual Stress Evolution of Laser Powder Bed Fused Inconel 718 under Heat Treatments

2020 ◽  
Author(s):  
Giulio Marchese ◽  
Eleonora Atzeni ◽  
Alessandro Salmi ◽  
Sara Biamino
Keyword(s):  
Residual Stresses ◽  
Inconel 718 ◽  
Heat Treatments ◽  
Powder Bed Fusion ◽  
Stress Evolution ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Sintering Mechanisms ◽  
Dendritic Structures

AbstractThe current work aimed to study the influence of various heat treatments on the microstructure, hardness, and residual stresses of Inconel 718 processed by laser powder bed fusion process. The reduction in residual stresses is crucial to avoid the deformation of the component during its removal from the building platform. Among the different heat treatments, 800 °C kept almost unaltered the original microstructure, reducing the residual stresses. Heat treatments at 900, 980, and 1065 °C gradually triggered the melt pool and dendritic structures dissolution, drastically reducing the residual stresses. Heat treatments at 900 and 980 °C involved the formation of δ phases, whereas 1065 °C generated carbides. These heat treatments were also performed on components with narrow internal channels revealing that heat treatments up to 900 °C did not trigger sintering mechanisms allowing to remove the powder from the inner channels.

scholarly journals The effect of build direction and geometric optimization in laser powder bed fusion of Inconel 718 structures with internal channels

2021 ◽  
pp. 109858
Author(s):  
Galina Kasperovich ◽  
Ralf Becker ◽  
Katia Artzt ◽  
Pere Barriobero-Vila ◽  
Guillermo Requena ◽  
...  
Keyword(s):  
Inconel 718 ◽  
Geometric Optimization ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed

scholarly journals Optimization of Laser Powder Bed Fusion Processing Using a Combination of Melt Pool Modeling and Design of Experiment Approaches: Density Control

2019 ◽  
Vol 3 (1) ◽  
pp. 21 ◽  
Author(s):  
Morgan Letenneur ◽  
Alena Kreitcberg ◽  
Vladimir Brailovski
Keyword(s):  
Scanning Speed ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Density Prediction ◽  
Melt Pool ◽  
Density Control ◽  
Pool Model ◽  
Conventional Material ◽  
Prediction Approach

A simplified analytical model of the laser powder bed fusion (LPBF) process was used to develop a novel density prediction approach that can be adapted for any given powder feedstock and LPBF system. First, calibration coupons were built using IN625, Ti64 and Fe powders and a specific LPBF system. These coupons were manufactured using the predetermined ranges of laser power, scanning speed, hatching space, and layer thickness, and their densities were measured using conventional material characterization techniques. Next, a simplified melt pool model was used to calculate the melt pool dimensions for the selected sets of printing parameters. Both sets of data were then combined to predict the density of printed parts. This approach was additionally validated using the literature data on AlSi10Mg and 316L alloys, thus demonstrating that it can reliably be used to optimize the laser powder bed metal fusion process.

scholarly journals Optimization of the Post-Process Heat Treatment of Inconel 718 Superalloy Fabricated by Laser Powder Bed Fusion Process

Metals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 144
Author(s):  
Eslam M. Fayed ◽  
Mohammad Saadati ◽  
Davood Shahriari ◽  
Vladimir Brailovski ◽  
Mohammad Jahazi ◽  
...  
Keyword(s):  
Inconel 718 ◽  
Mechanical Performance ◽  
Solution Treatment ◽  
Heat Treatments ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Homogenization Treatment ◽  
Powder Bed ◽  
Post Process ◽  
High Fraction

In the present study, multi-objective optimization is employed to develop the optimum heat treatments that can achieve both high-mechanical performance and non-distinctive crystallographic texture of 3D printed Inconel 718 (IN718) fabricated by laser powder bed fusion (LPBF). Heat treatments including homogenization at different soaking times (2, 2.5, 3, 3.5 and 4 h) at 1080 °C, followed by a 1 h solution treatment at 980 °C and the standard aging have been employed. 2.5 h is found to be the homogenization treatment threshold after which there is a depletion of hardening precipitate constituents (Nb and Ti) from the γ-matrix. However, a significant number of columnar grains with a high fraction (37.8%) of low-angle grain boundaries (LAGBs) have still been retained after the 2.5 h homogenization treatment. After a 4 h homogenization treatment, a fully recrystallized IN718 with a high fraction of annealing twins (87.1%) is obtained. 2.5 and 4 h homogenization treatments result in tensile properties exceeding those of the wrought IN718 at both RT and 650 °C. However, considering the texture requirements, it is found that the 4 h homogenization treatment offers the optimum treatment, which can be used to produce IN718 components offering a balanced combination of high mechanical properties and adequate microstructural isotropy.

A Physics-Informed Two-Level Machine Learning Model for Predicting Melt-Pool Size in Laser Powder Bed Fusion

2021 ◽  
Author(s):  
Yong Ren ◽  
Qian Wang ◽  
Panagiotis (Pan) Michaleris
Keyword(s):  
Machine Learning ◽  
Initial Temperature ◽  
Pool Size ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Input Feature ◽  
Melt Pool Size ◽  
Melt Pool Characteristics

Abstract Laser powder bed fusion (L-PBF) additive manufacturing (AM) is one type of metal-based AM process that is capable of producing high-value complex components with a fine geometric resolution. As melt-pool characteristics such as melt-pool size and dimensions are highly correlated with porosity and defects in the fabricated parts, it is crucial to predict how process parameters would affect the melt-pool size and dimensions during the build process to ensure the build quality. This paper presents a two-level machine learning (ML) model to predict the melt-pool size during the scanning of a multi-track build. To account for the effect of thermal history on melt-pool size, a so-called (pre-scan) initial temperature is predicted at the lower-level of the modeling architecture, and then used as a physics-informed input feature at the upper-level for the prediction of melt-pool size. Simulated data sets generated from the Autodesk's Netfabb Simulation are used for model training and validation. Through numerical simulations, the proposed two-level ML model has demonstrated a high prediction performance and its prediction accuracy improves significantly compared to a naive one-level ML without using the initial temperature as an input feature.

Measurement of the Melt Pool Length During Single Scan Tracks in a Commercial Laser Powder Bed Fusion Process

2017 ◽  
Author(s):  
J. C. Heigel ◽  
B. M. Lane
Keyword(s):  
Laser Power ◽  
High Speed ◽  
Infrared Camera ◽  
Powder Bed Fusion ◽  
Single Track ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Significant Difference ◽  
Scan Speed

This work presents high speed thermographic measurements of the melt pool length during single track laser scans on nickel alloy 625 substrates. Scans are made using a commercial laser powder bed fusion machine while measurements of the radiation from the surface are made using a high speed (1800 frames per second) infrared camera. The melt pool length measurement is based on the detection of the liquidus-solidus transition that is evident in the temperature profile. Seven different combinations of programmed laser power (49 W to 195 W) and scan speed (200 mm/s to 800 mm/s) are investigated and numerous replications using a variety of scan lengths (4 mm to 12 mm) are performed. Results show that the melt pool length reaches steady state within 2 mm of the start of each scan. Melt pool length increases with laser power, but its relationship with scan speed is less obvious because there is no significant difference between cases performed at the highest laser power of 195 W. Although keyholing appears to affect the anticipated trends in melt pool length, further research is required.

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