Optimization of Laser Paint Removal Process for Carbon Fiber Composite Substrate Based on Response Surface Analysis

Yajun Chen; Wenting Lu; Yating Yang

doi:10.3788/CJL221134

Journals >Chinese Journal of Lasers >Volume 50 >Issue 12 >Page 1202208 > Article

Chinese Journal of Lasers
Vol. 50, Issue 12, 1202208 (2023)

Optimization of Laser Paint Removal Process for Carbon Fiber Composite Substrate Based on Response Surface Analysis

Yajun Chen^">**, Wenting Lu, and Yating Yang

Author Affiliations

Sino-European Institute of Aviation Engineering, Civil Aviation University of China, Tianjin 300300, China

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DOI: 10.3788/CJL221134 Cite this Article Set citation alerts

Yajun Chen, Wenting Lu, Yating Yang. Optimization of Laser Paint Removal Process for Carbon Fiber Composite Substrate Based on Response Surface Analysis[J]. Chinese Journal of Lasers, 2023, 50(12): 1202208 Copy Citation Text

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Fig. 1. Schematic of scanning path of laser paint removal

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Fig. 2. Epoxy primer on sample surface. (a) Paint thickness distribution; (b) morphology of paint

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Fig. 3. Comparison of actual and predicted values. (a) Fiber exposure percentage E; (b) single pulse paint removal depth D; (c) ten-point height of microcosmic irregularity R_z

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Fig. 4. Effect of interaction of different factors on fiber exposure percentage

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Fig. 5. Effect of laser power and repetition frequency on fiber exposure percentage. (a) Contour plot; (b) response surface plot

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Fig. 6. Effect of scanning speed and repetition frequency on fiber exposure percentage. (a) Contour plot; (b) response surface plot

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Fig. 7. Effect of laser power and scanning speed on fiber exposure percentage. (a) Contour plot; (b) response surface plot

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Fig. 8. Effect of interaction of different factors on single-pulse paint removal depth

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Fig. 9. Effect of laser power and repetition frequency on single-pulse paint removal depth. (a) Contour plot; (b) response surface plot

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Fig. 10. Effect of scanning speed and repetition frequency on single-pulse paint removal depth. (a) Contour plot; (b) response surface plot

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Fig. 11. Effect of scanning speed and laser power on single-pulse paint removal depth. (a) Contour plot; （b） response surface plot

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Fig. 12. Influence of interaction of different factors on ten-point height of microcosmic irregularity

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Fig. 13. Effect of laser power and repetition frequency on ten-point height of microcosmic irregularity. (a) Contour plot; (b) response surface plot

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Fig. 14. Influence of scanning speed and repetition frequency on ten-point height of microcosmic irregularity. (a) Contour map;

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Fig. 15. Effect of scanning speed and laser power on ten-point height of microcosmic irregularity. (a) Contour plot; (b) response surface plot

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Fig. 16. Laser paint removal sample. (a) SEM morphology of sample surface with residual paint; (b) SEM morphology of complete paint removal surface; (c) three-dimensional morphology

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Technical parameter	Numerical value
Laser wavelength $λ$ /nm	1064
Maximum laser power P_max /W	20
Single pulse energy e /mJ	<1
Pulse width $τ$ /ns	110-140
Repetition frequency f /kHz	20-80
Scanning speed v /（mm·s^-1）	<12000
Focal length /mm	160
Spot diameter /μm	20
Operating voltage /V	220
Minimum line width /mm	0.02
Marking range /（mm×mm）	100×100
Total power /W	≤500

Table 1. Main technical parameters of laser paint removal system

Factor	Level
Factor	Low	Medium	High
Laser scanning speed v /（mm·s^-1）	130	165	200
Laser power P /W	11	13	15
Laser repetition frequency f /kHz	20	50	80

Table 2. Response surface optimization test input factors and level design

No.	Parameter			Result
No.	v /（mm·s^-1）	P /W	f /kHz	E /%	D /（μm·pulse^-1）	R_z /μm
1	200	11	50	0	3.39	40.16
2	200	13	20	0.027	41.49	42.02
3	200	15	50	0.017	11.87	40.81
4	200	13	80	0	3.21	58.63
5	130	13	20	0.185	42.20	120.12
6	165	13	50	0.007	9.86	50.33
7	165	13	50	0.003	8.06	53.97
8	130	13	80	0.012	4.71	52.43
9	165	13	50	0.005	8.40	51.15
10	165	15	80	0.015	5.84	45.03
11	165	13	50	0.027	8.61	58.80
12	165	15	20	0.163	49.98	116.73
13	165	13	50	0.042	9.24	59.20
14	165	11	20	0.019	30.71	47.76
15	165	11	80	0	1.05	45.03
16	130	11	50	0	3.47	62.03
17	130	15	50	0.148	22.78	76.91

Table 3. Response surface optimization test design matrix and test results

Source	Sum of squares	Degree of freedom	Mean square	F-value	p-value
Model	0.0589	9	0.0065	30.69	<0.0001
v	0.0113	1	0.0113	52.87	0.0002
P	0.0131	1	0.0131	61.61	0.0001
f	0.0167	1	0.0167	78.51	<0.0001
vP	0.0042	1	0.0042	19.84	0.0030
vf	0.0053	1	0.0053	24.82	0.0016
Pf	0.0041	1	0.0041	19.45	0.0031
f ²	0.0024	1	0.0024	11.04	0.0127
Residual	0.0015	7	0.0002
Lack of fit	0.0003	3	0.0001	0.4045	0.7585
Pure error	0.0011	4	0.0003
Cor total	0.0604	16

Table 4. Analysis of variance of mathematical model of E

Source	Sum of squares	Degree of freedom	Mean square	F-value	p-value
Model	3946.15	9	438.46	220.23	<0.0001
v	21.79	1	21.79	10.95	0.0130
P	336.14	1	336.14	168.84	<0.0001
f	2796.48	1	2796.48	1404.63	<0.0001
vP	29.37	1	29.37	14.75	0.0064
Pf	52.39	1	52.39	26.32	0.0014
f ²	689.14	1	689.14	346.14	<0.0001
Residual	13.94	7	1.99
Lack of fit	11.88	3	3.96	7.73	0.0386
Pure error	2.05	4	0.5128
Cor total	3960.09	16

Table 5. Analysis of variance of mathematical model of D

Source	Sum of squares	Degree of freedom	Mean square	F-value	p-value
Model	7987.31	6	1331.22	12.22	0.0004
v	2108.80	1	2108.80	19.36	0.0013
P	892.70	1	892.70	8.20	0.0169
f	1968.91	1	1968.91	18.08	0.0017
vf	1777.00	1	1777.00	16.32	0.0024
Pf	1189.25	1	1189.25	10.92	0.0080
Residual	1089.07	10	108.91
Lack of fit	1019.78	6	169.96	9.81	0.0223
Pure error	69.29	4	10.0732
Cor total	9076.38	16

Table 6. Analysis of variance of mathematical model of R_z

Technical parameter	Criteria			Weight
Technical parameter	Goal	Lower limit	Upper limit	Weight
Laser scanning speed v /（mm·s^-1）	In range	130	200	1
Laser power P /W	In range	11	15	1
Laser repetition frequency f /kHz	In range	20	80	1
Fiber exposure percentage E /%	Maximization	0.04	0.15	1
Single-pulse paint removal depth D /（μm·pulse^-1）	Maximization	30	50	1
Ten-piont height of microcosmic irregularity R_z /μm	In range	45	55	1