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레이저 변수와 분말 기공율이 SLM 공정의 분말베드내 열특성에 미치는 영향 고찰

Investigation of Influence of Laser Parameters and Powder Porosity on Thermal Characteristics in the Powder Bed of a SLM Process

Journal of the Korean Society for Precision Engineering 2019;36(8):761-769.
Published online: August 1, 2019

1 조선대학교 대학원 기계공학과

2 한국생산기술연구원 극한가공기술그룹

3 한국생산기술연구원 디지털제조공정그룹

1 Department of Mechanical Engineering, Graduate School, Chosun University

2 Extreme Fabrication Technology Group, Korean Institute of Industrial Technology

3 Digital Manufacturing Process Group, Korean Institute of Industrial Technology

#E-mail: smart@chosun.or.kr, TEL: +82-62-230-7043
• Received: April 10, 2019   • Revised: May 27, 2019   • Accepted: June 10, 2019

Copyright © The Korean Society for Precision Engineering

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Effects of Deposition Strategy and Preheating Temperature on Thermo-Mechanical Characteristics of Inconel 718 Super-Alloy Deposited on AISI 1045 Substrate Using a DED Process
    Ho Kim, Kwang-Kyu Lee, Dong-Gyu Ahn, Hyub Lee
    Materials.2021; 14(7): 1794.     CrossRef

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Investigation of Influence of Laser Parameters and Powder Porosity on Thermal Characteristics in the Powder Bed of a SLM Process
J. Korean Soc. Precis. Eng.. 2019;36(8):761-769.   Published online August 1, 2019
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Investigation of Influence of Laser Parameters and Powder Porosity on Thermal Characteristics in the Powder Bed of a SLM Process
J. Korean Soc. Precis. Eng.. 2019;36(8):761-769.   Published online August 1, 2019
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Investigation of Influence of Laser Parameters and Powder Porosity on Thermal Characteristics in the Powder Bed of a SLM Process
Image Image Image Image Image Image Image Image Image Image Image Image Image Image Image
Fig. 1 Inside of PROX DMP300 apparatus
Fig. 2 Simulation model and meshes for a FEA
Fig. 3 Temperature dependent thermal properties of SUS17-4PH and S45C (Solid material)16-18
Fig. 4 Temperature dependent thermal properties of Nitrogen21-23
Fig. 5 Maximum temperatures for different moving distances and efficiencies of heat flux (P = 172 W and ν = 1.6 m/s)
Fig. 6 Temperature distributions for different efficiencies of heat flux (P = 172 W and ν = 1.6 m/s)
Fig. 7 Effects of the efficiency on the width (w) and the length (D) of the molten pool (P = 172 W and ν = 1.6 m/s)
Fig. 8 Effects of the power and the scan speed of the laser on the maximum temperature
Fig. 9 Influence of the effective heat input on the maximum temperature in steady-state
Fig. 10 Influence of the scan speed of the laser on the temperature distribution in the vicinity of the irradiated region (P = 172W)
Fig. 11 Effects of the power of the laser on the temperature distribution in the vicinity of the irradiated region (ν = 1.6 m/s)
Fig. 12 Influence of the effective heat input on the length, the width and the aspect ratio of the molten pool
Fig. 13 Effects of the porosity on the formation of the molten pool (P = 172 W and ν = 1.6 m/s)
Fig. 14 Temperature dependent thermal conductivity of SUS17-4PH considering porosity and contact status of powders
Fig. 15 Influence of the porosity on the length, the width and the aspect ratio of the molten pool
Investigation of Influence of Laser Parameters and Powder Porosity on Thermal Characteristics in the Powder Bed of a SLM Process

Specification of experimental system

Laser λ (nm) re (μm) ψ (μm) δ (nm) Gas
Nd:YAG 1,063 37.5 40 50 Nitrogen

Initial temperature, convection coefficient, interfacial thermal conductance, and emissivity

Ti (oC) h (W/mm2oC) G (W/mm2oC) ε 13
90oC 316oC
25 10 0.01 0.44 0.51

Conditions of FEAs

P (W) ν (m/s) h Φ (%)
172-324 1.2- 2.0 0.15-0.25 0-30

Relationship between effective heat input and maximum temperature in steady-state

Measure Regression equations R2
Tmax,s (oC) 60.207 Qeff0.9428 0.99

Relationship between effective heat input and measures of the formation of the molten pool in steady-state

Measures Regression equations R2
Δ (μm) 0.0528 Qeff1.6890 0.99
ω (μm) 16.785 Qeff0.3089 0.91
Π 0.0031 Qeff1.3801 0.97
Table 1 Specification of experimental system
Table 2 Initial temperature, convection coefficient, interfacial thermal conductance, and emissivity
Table 3 Conditions of FEAs
Table 4 Relationship between effective heat input and maximum temperature in steady-state
Table 5 Relationship between effective heat input and measures of the formation of the molten pool in steady-state