Morphology Prediction of Coaxial Powder Feeding Multichannel Laser Cladding Layer Based on Response Surface

Wanxu Liang; Yong Yang; Kang Jin; Kang Qi; Li Xiong; Yi Liu; Longjie Dai

doi:10.3788/LOP202259.0114012

Journals >Laser & Optoelectronics Progress >Volume 59 >Issue 1 >Page 0114012 > Article

Laser & Optoelectronics Progress
Vol. 59, Issue 1, 0114012 (2022)

Morphology Prediction of Coaxial Powder Feeding Multichannel Laser Cladding Layer Based on Response Surface

Wanxu Liang¹, Yong Yang^1、*, Kang Jin¹, Kang Qi¹, Li Xiong¹, Yi Liu², and Longjie Dai²

Author Affiliations

¹School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao , Shandong 266520, China

²Qingdao Choho Industrial Co., Ltd., Qingdao , Shandong 266705, China

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DOI: 10.3788/LOP202259.0114012 Cite this Article Set citation alerts

Wanxu Liang, Yong Yang, Kang Jin, Kang Qi, Li Xiong, Yi Liu, Longjie Dai. Morphology Prediction of Coaxial Powder Feeding Multichannel Laser Cladding Layer Based on Response Surface[J]. Laser & Optoelectronics Progress, 2022, 59(1): 0114012 Copy Citation Text

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Fig. 1. Laser cladding equipment

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Fig. 2. Schematic of coaxial powder feeding multi-channel laser cladding

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Fig. 3. Section morphology of cladding layer

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Fig. 4. Cross-sectional morphologies of cladding layers of each sample. (a) Sample 10; (b) sample 20; (c) sample 30; (d) sample 40; (e) sample 50; (f) sample 60; (g) sample 70; (h) sample 80; (i) sample 90

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Fig. 5. Effect Pareto diagram of average height of cladding layer

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Fig. 6. Effect Pareto diagram of average substrate melt depth

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Fig. 7. Three-dimensional response surfaces of average substrate melt depth under different significant interaction terms. (a) Laser power P and distance from cladding head to the substrate L; (b) overlap rate O_r and distance from cladding head to the substrate L; (c) scanning speed S and overlap rate O_r

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Fig. 8. Effect Pareto diagram of average dilution rate

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Fig. 9. Three-dimensional response surfaces of average dilution rate under different significant interaction terms. (a) Scanning speed S and overlap rate O_r; (b) distance from cladding head to the substrate L and laser power P; (c) distance from cladding head to the substrate L and scanning speed S

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Fig. 10. Effect Pareto diagram of average surface height difference

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Fig. 11. Three-dimensional response surfaces of average surface height difference under different significant interaction terms. (a) Overlap rate O_r and laser power P; (b) distance from cladding head to the substrate L and overlap rate O_r

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Fig. 12. Cladding layer morphologies after optimization.(a) Surface morphology; (b) cross-sectional morphology

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Material	Mass fraction /%
Material	C	Si	Mn	S	P	Cr	Ni	Mo	Cu
45 steel	0.46	0.27	0.65	-	-	0.23	0.3	-	0.24
316L powder	0.07	0.90	1.90	0.03	0.035	17.5	12	2.5	-

Table 1. Chemical composition of 45 steel and 316L stainless steel powder

Variable	Notation	Value
Laser power	$P / k W$	1.0，1.2，1.4
Scanning speed	S / $(m m \cdot s^{- 1})$	5，7，9
Overlap rate	$O_{r} / %$	10，20，30，40，50
Distance from cladding head to substrate	$L / m m$	1.5，2.0

Table 2. Process parameter values

No.	$P / k W$	S / $(m m \cdot s^{- 1})$	$O_{r} / %$	$L / m m$	$H / m m$	$H^{'} / m m$	$Δ_{1} / %$
Average							10.09
10	1.0	5	10	1.5	0.934	0.845	9.53
20	1.2	5	30	1.5	0.886	0.908	2.49
30	1.4	5	20	2.0	0.795	0.792	0.37
40	1.0	7	10	2.0	0.328	0.418	27.46
50	1.2	7	30	2.0	0.571	0.481	15.82
60	1.4	7	40	1.5	0.679	0.789	16.20
70	1.0	9	40	2.0	0.256	0.250	2.51
80	1.2	9	50	1.5	0.609	0.558	8.39
90	1.4	9	50	2.0	0.463	0.426	8.01

Table 3. Predicted average height of cladding layers

No.	$P / k W$	S / $(m m \cdot s^{- 1})$	$O_{r} / %$	$L / m m$	$D / m m$	$D^{'} / m m$	$Δ_{2} / %$
Average							4.96
10	1.0	5	10	1.5	0.147	0.149	1.02
20	1.2	5	30	1.5	0.327	0.349	6.64
30	1.4	5	20	2.0	0.638	0.593	7.08
40	1.0	7	10	2.0	0.221	0.197	10.97
50	1.2	7	30	2.0	0.393	0.390	0.95
60	1.4	7	40	1.5	0.426	0.409	3.96
70	1.0	9	40	2.0	0.125	0.137	9.71
80	1.2	9	50	1.5	0.229	0.227	1.11
90	1.4	9	50	2.0	0.442	0.429	2.98

Table 4. Predicted average substrate melt depth

No.	P /kW	S /（mm⋅s^-1）	O_r /%	L /mm	D_r /%	$D_{r}^{'} / %$	$Δ_{3} / %$
Average							8.83
10	1.0	5	10	1.5	15.5	12.6	18.77
20	1.2	5	30	1.5	28.3	27.6	2.59
30	1.4	5	20	2.0	45.5	44.8	1.46
40	1.0	7	10	2.0	32.2	31.0	3.81
50	1.2	7	30	2.0	40.7	45.2	10.89
60	1.4	7	40	1.5	32.5	34.4	5.87
70	1.0	9	40	2.0	32.6	39.6	21.75
80	1.2	9	50	1.5	28.9	24.9	13.80
90	1.4	9	50	2.0	49.0	49.3	0.55

Table 5. Predicted average dilution rate

No.	P /kW	S /（mm⋅s^-1）	O_r /%	L /mm	$A_{d} / m m$	$A_{d}^{'} / m m$	$Δ_{4} / %$
Average							8.34
10	1.0	5	10	1.5	0.337	0.322	4.32
20	1.2	5	30	1.5	0.253	0.282	11.58
30	1.4	5	20	2.0	0.286	0.273	4.47
40	1.0	7	10	2.0	0.280	0.290	3.27
50	1.2	7	30	2.0	0.196	0.200	2.40
60	1.4	7	40	1.5	0.239	0.262	9.85
70	1.0	9	40	2.0	0.115	0.137	19.54
80	1.2	9	50	1.5	0.203	0.240	18.03
90	1.4	9	50	2.0	0.153	0.155	1.58

Table 6. Predicted average surface height difference

	No.	P /kW	S /（mm⋅s^-1）	O_r /%	L /mm	H /mm	D /mm	$D_{r} / %$	$A_{d} / m m$
Predict	I	1.1	6	30	1.4	0.796	0.270	23.6	0.272
	Ⅱ	1.2	8	45	1.4	0.661	0.267	24.6	0.261
	Ⅲ	1.3	9	45	1.3	0.706	0.259	23.3	0.266
Experimental	I	1.1	6	30	1.4	0.829	0.246	22.1	0.268
	Ⅱ	1.2	8	45	1.4	0.698	0.424	36.8	0.209
	Ⅲ	1.3	9	45	1.3	0.776	0.318	29.6	0.230

Table 7. Optimization results and validation

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