Laser Paint Removal Process Parameter Optimization via Response Surface Methodology

Jianian Yang; Jianzhong Zhou; Qi Sun; Xiankai Meng; Ming Zhu; Zhaoheng Guo; Qiang Fu

doi:10.3788/LOP56.231402

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 23 >Page 231402 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 23, 231402 (2019)

Laser Paint Removal Process Parameter Optimization via Response Surface Methodology

Jianian Yang^1、**, Jianzhong Zhou^1、*, Qi Sun¹, Xiankai Meng¹, Ming Zhu¹, Zhaoheng Guo¹, and Qiang Fu²

Author Affiliations

¹School of Mechanical Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China

²Nanjing Institute of Advanced Laser Technology, Nanjing, Jiangsu 210038, China

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DOI: 10.3788/LOP56.231402 Cite this Article Set citation alerts

Jianian Yang, Jianzhong Zhou, Qi Sun, Xiankai Meng, Ming Zhu, Zhaoheng Guo, Qiang Fu. Laser Paint Removal Process Parameter Optimization via Response Surface Methodology[J]. Laser & Optoelectronics Progress, 2019, 56(23): 231402 Copy Citation Text

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Fig. 1. Diagram of laser paint removal

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Fig. 2. Effect of interaction of all factors on surface composition

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Fig. 3. Cleaning surface micromorphology and elemental composition under different overlap rates. (a) 50%; (b) 75%

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Fig. 4. Effects of spot overlap rate and power on surface composition. (a) Contour graph; (b) response graph

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Fig. 5. Effects of spot overlap rate and number of scans on surface composition. (a) Contour graph; (b) response graph

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Fig. 6. Effect of interaction of all factors on surface roughness

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Fig. 7. Cleaning surface micromorphology and line roughness at different powers. (a) 20 W; (b) 25 W

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Fig. 8. Effects of power and number of scans on surface roughness. (a) Contour graph; (b) response graph

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Fig. 9. Effects of power and spot overlap rate on surface roughness. (a) Contour graph; (b) response graph

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Element	C	Si	Mn	Cr	Ni	S	P	N	Fe
Mass fraction /%	≤0.08	≤1.0	≤2.0	18.0-20.0	8.0-10.5	≤0.03	≤0.035	≤0.1	Bal.

Table 1. Main chemical composition of 304 stainless steel

Parameter	Value
Wavelength /nm	1064
Power /W	≤ 100
Pulse width /ns	100
Frequency /kHz	10-100
Scan speed /(mm·s^-1)	≤8000
Focal length /mm	160
Waist diameter /mm	0.05

Table 2. Main technical parameters of laser paint removal system

Factor	Extreme value
Factor	Low(-1)	Medium(0)	High(+1)
Power P /W	15	20	25
Spot overlap rate γ /%	25	50	75
Number of scans N	2	3	4

Table 3. Experimental factors and level design

No.	Parameter			Result
No.	P /W	γ /%	N	S	S_a /μm
1	25	25	3	50	0.6966
2	25	50	2	60	0.8036
3	25	75	3	20	1.1528
4	25	50	4	30	1.5258
5	15	50	2	40	1.5620
6	20	50	3	85	0.5980
7	20	50	3	85	0.6330
8	15	50	4	85	1.0620
9	20	50	3	80	0.7070
10	20	75	4	10	1.0588
11	20	50	3	80	0.7860
12	20	75	2	20	1.0844
13	20	50	3	75	0.5900
14	20	25	2	30	0.8038
15	20	25	4	65	0.8788
16	15	25	3	40	0.9316
17	15	75	3	60	0.9498

Table 4. Design matrix and experimental results

Source	Sum of squares	Degree of freedom	Mean square	F	Probability
Model	10321.99	9	1146.89	16.62	0.0006
P	528.13	1	528.13	7.65	0.0278
γ	703.13	1	703.13	10.19	0.0152
Pγ	625.00	1	625.00	9.06	0.0197
PN	1406.25	1	1406.25	20.38	0.0027
γN	506.25	1	506.25	7.34	0.0303
γ²	3968.38	1	3968.38	57.52	0.0001
N²	1592.85	1	1592.85	23.09	0.0020
Lack of fit	393.75	3	131.25	5.89	0.0599
Note: residual-square R²=0.9553; adjusted residual-square $\begin{matrix} R_{Adj}^{2} \end{matrix}$ =0.8978; predicted residual-square $\begin{matrix} R_{pred}^{2} \end{matrix}$ =0.4040; adeq precision A_P=11.479.

Table 5. ANOVA for surface composition model

Source	Sum of squares	Degree of freedom	Mean square	F	Probability
Model	1.30	9	0.14	25.26	0.0002
γ	0.11	1	0.11	19.17	0.0032
Pγ	0.048	1	0.048	8.42	0.0230
PN	0.37	1	0.37	65.52	<0.0001
P²	0.32	1	0.32	56.24	0.0001
N²	0.38	1	0.38	66.34	<0.0001
Lack of fit	0.012	3	0.004	0.60	0.6484
Note: R²=0.9701, $\begin{matrix} R_{Adj}^{2} \end{matrix}$ =0.9317, $\begin{matrix} R_{pred}^{2} \end{matrix}$ =0.8196, A_P=15.336.