Numerical Simulation and Regression Orthogonal Experiment Optimization of Laser Cladding of Nickel-Based Superalloy

Sirui Yang; Haiqing Bai; Chaofan Li; Xinhe Zhang; Zongqiang Jia

doi:10.3788/LOP220699

Laser & Optoelectronics Progress, Volume. 60, Issue 5, 0514008(2023)

Numerical Simulation and Regression Orthogonal Experiment Optimization of Laser Cladding of Nickel-Based Superalloy

Sirui Yang¹, Haiqing Bai^1,2、*, Chaofan Li¹, Xinhe Zhang¹, and Zongqiang Jia¹

Author Affiliations

¹School of Mechanical Engineering, Shaanxi University of Technology, Hanzhong 723001, Shaanxi, China

²Shaanxi Key Laboratory of Industrial Automation, Hanzhong 723001, Shaanxi, China

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Figures & Tables(22)

Fig. 1. 3D model

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Fig. 2. Schematic diagram of temperature measurement. (a) Geometrical characteristics of cladding layer cross section; (b) position and direction of temperature measurement; (c) determination of molten pool width; (d) determination of molten pool depth

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Fig. 3. 3 kW fiber laser cladding machine

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Fig. 4. Ultra depth of field microscope

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Fig. 5. Microvickers hardness tester

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Fig. 6. Microstructure of Inconel718 alloy powder

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Fig. 7. Microstructure of cladding layer

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Fig. 8. Variation of hardness with laser power

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Fig. 9. Variation of hardness with powder feeding rate

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Fig. 10. Variation of cladding layer morphology with laser power

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Fig. 11. Variation of cladding layer morphology with powder feeding rate

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Fig. 12. Variation of dilution rate with laser power

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Fig. 13. Variation of dilution rate with powder feeding rate

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Table 1. Basic physical parameters
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Table 1. Basic physical parameters
Material Density /（kg·m^-3） Melting point /℃ Phase transition temperature region /℃
45^#steel 7850 1495 1490—1530
Inconel718 alloy powder 8240 1260 1260—1320

Table 2. Thermal physical properties of 45^# steel

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Table 2. Thermal physical properties of 45^# steel

Temperature /℃	20	100	200	300	400	500	600	800	1000	1200	1400	1600
Specific heat /（J·kg^-1·℃^-1）	472	480	798	560	586	615	700	806	637	602	587	576
Coefficient of thermal conductivity /（W·m^-1·℃^-1）	47.68	43.53	40.44	38.13	36.02	34.16	21.98	26.49	25.92	24.02	23.51	22.66

Table 3. Thermal physical parameters of Inconel718 alloy

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Table 3. Thermal physical parameters of Inconel718 alloy

Temperature /℃	20	100	200	300	400	500	600	800	1000	1200	1400	1600
Specific heat /（J·kg^-1·℃^-1）	421	442	453	472	481	502	527	562	606	628	636	649
Coefficient of thermal conductivity /（W·m^-1·℃^-1）	11.9	12.4	13.7	15.2	16.9	18.7	21.7	25.6	22.9	19.1	17.7	15.8

Table 4. Comparison and error of molten pool size

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Table 4. Comparison and error of molten pool size

Experimental scheme			results /mm Simulation		results /mm Experimental		Error /%
Laser power /W	Scanning speed /（mm·s^-1）	Powder feeding rate x₃ /（g·min^-1）	Width	Depth	Width	Depth	Width	Depth
1200	15	18	1.73	0.44	1.64	0.42	5.6	5.3
1500	21	19	1.89	0.53	1.87	0.51	1.1	3.9
1800	15	17	1.99	0.67	1.98	0.65	0.3	2.7
2100	23	20	1.83	0.39	1.83	0.38	0.3	3.9
2400	17	16	2.22	0.88	2.17	0.88	2.2	0.2

Table 5. Factor level coding table
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Table 5. Factor level coding table
Factor x_j Laser power x₁ /W Scan speed x₂ /（mm·s^-1） Powder feeding rate x₃ /（g·min^-1）
Upper level（1） 2400 23 20
Lower level（-1） 1200 15 16
Zero level（0） 1800 19 18
Varying pitch ∆_j 600 4 2

Table 6. Ternary linear regression orthogonal test scheme and test results

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Table 6. Ternary linear regression orthogonal test scheme and test results

Number	Z₁	Z₂	Z₁Z₂	Z₃	Z₁Z₃	X₁	X₂	X₃	Cladding layer width /mm	Depth of molten pool /mm	Forming factor y
1	1	1	1	1	1	2400	23	20	1.78	0.45	3.95
2	1	1	1	-1	-1	2400	23	16	2.03	0.71	2.86
3	1	-1	-1	1	1	2400	15	20	1.98	0.64	3.09
4	1	-1	-1	-1	-1	2400	15	16	2.17	0.87	2.49
5	-1	1	-1	1	-1	1200	23	20	1.31	0.20	6.55
6	-1	1	-1	-1	1	1200	23	16	1.52	0.31	4.91
7	-1	-1	1	1	-1	1200	15	20	1.49	0.26	5.73
8	-1	-1	1	-1	1	1200	15	16	1.67	0.44	3.79

Table 7. Ternary linear regression orthogonal design calculation table

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Table 7. Ternary linear regression orthogonal design calculation table

Number	Z₁	Z₂	Z₁Z₂	Z₃	Z₁Z₃	y	y²	Z₁y	Z₂y	Z₃y	（Z₁Z₂）y	（Z₁Z₃）y
1	1	1	1	1	1	3.95	15.6025	3.95	3.95	3.95	3.95	3.95
2	1	1	1	-1	-1	2.86	8.1796	2.86	2.86	-2.86	2.86	-2.86
3	1	-1	-1	1	1	3.09	9.5481	3.09	-3.09	3.09	-3.09	3.09
4	1	-1	-1	-1	-1	2.49	6.2001	2.49	-2.49	-2.49	-2.49	-2.49
5	-1	1	-1	1	-1	6.55	42.9025	-6.55	6.55	6.55	-6.55	-6.55
6	-1	1	-1	-1	1	4.91	24.1081	-4.91	4.91	-4.91	-4.91	4.91
7	-1	-1	1	1	-1	5.73	32.8329	-5.73	-5.73	5.73	5.73	-5.73
8	-1	-1	1	-1	1	3.79	14.3641	-3.79	-3.79	-3.79	3.79	3.79
∑						33.37	153.7379	-8.59	3.17	5.27	-0.71	-1.89

Table 8. Analysis of variance table

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Table 8. Analysis of variance table

Source of difference	S_SS	f_df	E_MS	F	Significance
Z₁	9.2235	1	9.2235	223.431	* * *
Z₂	1.2561	1	1.2561	30.428	*
Z₃	3.4716	1	3.4716	84.096	* *
Z₁Z₂	0.0630	1	0.0630	1.526
Z₁Z₃	0.4465	1	0.4465	10.816
Return	14.4607	5	2.8921	70.059	* *
Residual	0.0826	2	0.4128
Sum	14.5433	n－1=7

Table 9. Single factor experimental scheme and results

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Table 9. Single factor experimental scheme and results

Serial number	Laser power /W	Powder feeding rate /（g·min^-1）	Depth of molten pool /mm	Molten pool width /mm	Height of cladding layer /mm	Dilution rate	Hardness of cladding layer /HV
1	1200	16	0.42	1.64	0.59	0.416	119.0
2	1500		0.54	1.83	0.67	0.446	196.1
3	1800		0.67	1.98	0.75	0.472	222.8
4	2100		0.72	2.05	0.80	0.474	258.4
5	2400		0.88	2.18	0.94	0.483	292.5
6	1800	16	0.64	1.98	0.65	0.496	196.1
7		17	0.57	1.87	0.60	0.487	219.4
8		18	0.48	1.81	0.54	0.471	238.3
9		19	0.43	1.73	0.49	0.467	255.2
10		20	0.38	1.66	0.45	0.458	267.8

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Sirui Yang, Haiqing Bai, Chaofan Li, Xinhe Zhang, Zongqiang Jia. Numerical Simulation and Regression Orthogonal Experiment Optimization of Laser Cladding of Nickel-Based Superalloy[J]. Laser & Optoelectronics Progress, 2023, 60(5): 0514008

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