Determining the Optimal Mode of the Inconel 718 Alloy Deposition at a Direct Laser Deposition Plant

2021 ◽  
Vol 1037 ◽  
pp. 3-12
Author(s):  
Maxim Oleynik ◽  
Alexander I. Khaimovich ◽  
Andrey V. Balaykin

The paper describes determining the optimal direct laser deposition mode when processing the results of a two-factor experiment by the steep ascent method. The dependence of the ultimate tensile strength on the volumetric energy density and the lateral pitch was chosen as the target function.

Vacuum ◽  
2019 ◽  
Vol 161 ◽  
pp. 225-231 ◽  
Author(s):  
Qiang Wang ◽  
Song Zhang ◽  
Chunhua Zhang ◽  
Jianqiang Wang ◽  
M. Babar Shahzad ◽  
...  

Author(s):  
Christopher Katinas ◽  
Shunyu Liu ◽  
Yung C. Shin

Understanding the capture efficiency of powder during direct laser deposition (DLD) is critical when determining the overall manufacturing costs of additive manufacturing (AM) for comparison to traditional manufacturing methods. By developing a tool to predict the capture efficiency of a particular deposition process, parameter optimization can be achieved without the need to perform a costly and extensive experimental study. The focus of this work is to model the deposition process and acquire the final track geometry and temperature field of a single track deposition of Ti–6Al–4V powder on a Ti–6Al–4V substrate for a four-nozzle powder delivery system during direct laser deposition with a LENS™ system without the need for capture efficiency assumptions by using physical powder flow and laser irradiation profiles to predict capture efficiency. The model was able to predict the track height and width within 2 μm and 31 μm, respectively, or 3.3% error from experimentation. A maximum of 36 μm profile error was observed in the molten pool, and corresponds to errors of 11% and 4% in molten pool depth and width, respectively. Based on experimentation, the capture efficiency of a single track deposition of Ti–6Al–4V was found to be 12.0%, while that from simulation was calculated to be 11.7%, a 2.5% deviation.


2019 ◽  
Vol 238 ◽  
pp. 210-213 ◽  
Author(s):  
Yanchuan Tang ◽  
Haichao Yang ◽  
Daosi Huang ◽  
Longzhi Zhao ◽  
Dejia Liu ◽  
...  

2019 ◽  
Vol 363 ◽  
pp. 161-169 ◽  
Author(s):  
Hao Xu ◽  
Hui Xing ◽  
Anping Dong ◽  
Dafan Du ◽  
Donghong Wang ◽  
...  

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