Multi-Objective Optimization of Coaxial Powder Feeding Laser Cladding Based on NSGA-II

Table 1. Performances of matrix and repaired materials
View table
Table 1. Performances of matrix and repaired materials
Material Melting point /℃ Density /(g·cm^-3) Tensilestrength /MPa Yieldstrength /MPa Brinellhardness /HB
Steel 20 1398-1454 7.93 410 245 156
Inconel625 1290-1350 8.4 827 414 220

Table 2. Main compositions of matrix and repaired materials
View table
Table 2. Main compositions of matrix and repaired materials
Material Mass fraction /%
Cr Mo C Si Mn Nb Fe
Steel 20 0.25 8 0.17-0.24 0.17-0.37 0.70-1.00 3.15 Bal.
Inconel625 23 8 - - - 4.15 5

Table 3. Cladding parameters
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Table 3. Cladding parameters
Parameter Content
Distance from nozzle to substrate /mm 12
Laser beam diameter at substrate /mm 2.5
Shielding gas Argon
Powder transport gas Argon
Powder transport gas flow rate /(m³·h^-1) 0.425

Table 4. Process parameters and corresponding coded values in CCD experiments
View table
Table 4. Process parameters and corresponding coded values in CCD experiments
Parameter α=-1.5 α=-1 α=0 α=1 α=+1.5
Laser power /W 800 1100 1400 1700 2000
Scanning speed /(mm·s^-1) 8 9.5 11 12.5 14
Powder flow rate /(g·min^-1) 10.08 11.34 12.6 13.86 15.12

Table 5. Dilution rate predicted based on multiple regression and neural network
View table
Table 5. Dilution rate predicted based on multiple regression and neural network
Single-passexperiment No. Measuredvalue Prediction result
Multipleregression Neuralnetwork
1 0.520 0.58 0.54
2 0.640 0.60 0.63
3 0.601 0.57 0.63
4 0.456 0.49 0.48
5 0.150 0.09 0.14
6 0.080 0.07 0.09

Table 5. Variables and corresponding measured results in CCD experimental design

View table

Table 5. Variables and corresponding measured results in CCD experimental design

CCDExperiment No.	Parameter			Response
CCDExperiment No.	Laser power /W	Scanning rate /(mm·s^-1)	Feed-powder speed/(g·min^-1)	Section area /mm²	Dilution	Microhardness/HV	HAZ depth /mm	Porosity /%
1	800	8.0	15.12	0.88	0.05	259.93	0.45	2.30
2	800	8.0	10.08	0.64	0.06	262.67	0.51	0.27
3	800	14.0	10.08	0.28	0.34	206.10	0.53	1.70
4	800	14.0	15.12	0.36	0.11	258.07	0.47	0.39
5	1100	11.0	12.6.0	1.00	0.28	244.03	0.62	1.17
6	1400	12.5	12.60	1.36	0.50	201.23	0.84	0.36
7	1400	9.5	12.60	1.92	0.44	209.17	0.90	0.08
8	1400	11.0	11.34	1.48	0.50	200.63	0.86	0.21
9	1400	11.0	13.86	1.60	0.45	208.77	0.84	0.20
10	1400	11.0	12.60	1.58	0.48	197.97	0.88	0.14
11	1400	11.0	12.60	1.56	0.50	192.83	0.89	0.03
12	1400	11.0	12.60	1.60	0.47	192.93	0.89	0.15
13	1400	11.0	12.60	1.60	0.46	197.67	0.86	0.04
14	1400	11.0	12.60	1.64	0.45	199.17	0.85	0.24
15	1400	11.0	12.60	1.54	0.47	197.53	0.85	0.20
16	1700	11.0	12.60	2.00	0.55	186.83	1.06	1.48
17	2000	8.0	15.12	3.64	0.52	186.17	1.40	0.97
18	2000	8.0	10.08	3.32	0.63	170.43	1.57	1.59
19	2000	14.0	10.08	2.00	0.68	160.37	1.22	1.01
20	2000	14.0	15.12	2.00	0.58	178.60	1.11	1.29

Table 6. Microhardness predicted based on multiple regression and neural network
View table
Table 6. Microhardness predicted based on multiple regression and neural network
Single-passexperiment No. Measuredvalue Prediction result
Multipleregression Neuralnetwork
1 186.43 192.15 184.67
2 163.70 154.53 167.43
3 177.70 163.65 171.50
4 207.47 202.42 206.94
5 234.00 240.04 257.35
6 250.47 255.44 258.08

Table 7. Comparison of response values before and after optimization
View table
Table 7. Comparison of response values before and after optimization
Response Dilution HAZdepth /mm Microharness /HV Efficiency /(mm²·s^-1)
Before 0.518 0.855 186.433 15.24
After 0.320 0.736 218.337 16.17

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Kai Zhao, Xudong Liang, Wei Wang, Ping Yang, Yunbo Hao, Zhongliang Zhu. Multi-Objective Optimization of Coaxial Powder Feeding Laser Cladding Based on NSGA-II[J]. Chinese Journal of Lasers, 2020, 47(1): 0102004

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Paper Information

Category: laser manufacturing

Received: Jul. 29, 2019

Accepted: Sep. 26, 2019

Published Online: Jan. 9, 2020

The Author Email: Kai Zhao (zkdlut@163.com), Xudong Liang (zkdlut@163.com)

DOI:10.3788/CJL202047.0102004

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Performances of matrix and repaired materials

Table 1. Performances of matrix and repaired materials

Table 2. Main compositions of matrix and repaired materials

Table 2. Main compositions of matrix and repaired materials

Table 3. Cladding parameters

Table 3. Cladding parameters

Table 4. Process parameters and corresponding coded values in CCD experiments

Table 4. Process parameters and corresponding coded values in CCD experiments

Table 5. Dilution rate predicted based on multiple regression and neural network

Table 5. Dilution rate predicted based on multiple regression and neural network

Table 5. Variables and corresponding measured results in CCD experimental design

Table 5. Variables and corresponding measured results in CCD experimental design

Table 6. Microhardness predicted based on multiple regression and neural network

Table 6. Microhardness predicted based on multiple regression and neural network

Table 7. Comparison of response values before and after optimization

Table 7. Comparison of response values before and after optimization