Process Parameters Optimization of Wet Shot Peening for Paint Cleaning
Abstract
:1. Introduction
2. Experimental
2.1. Equipment
2.2. Substance and Coating Material
2.3. Experimental Design and Procedure
2.4. Related Parameter Definition
3. Results and Discussion
3.1. Surface Topography Analysis
3.1.1. “Pseudo-Crack” Phenomenon
3.1.2. Layer-by-Layer Paint Removal
3.2. Analysis of Jet Velocity of Wet Shot Peening
3.3. Process Parameter Optimization Based on Cleaning Efficiency
3.4. Process Parameter Optimization Based on Removal Mass of Substrate
4. Conclusions
- (1)
- According to the change of paint surface during the cleaning process, it is inferred that paint removal is achieved layer by layer, and it is pointed out that the pseudo-crack phenomenon is the main reason that the cleaning width of the two sides edge is higher than that of the middle part, so increasing paint surface crack is an effective way to improve cleaning efficiency.
- (2)
- Taking cleaning efficiency and the mass ratio of the substrate removed (R-sub) as the evaluation indexes of cleaning effect, it is found that increasing pressure, stand-off distance, traverse rate or reducing cleaning times can effectively improve the cleaning efficiency. The pressure and cleaning times were positively correlated with the R-sub, while the traverse rate was negatively correlated. With the increase of stand-off distance, the R-sub first increased and then decreased. According to the range, the traverse rate has the greatest influence on the cleaning efficiency and the R-sub, followed by the cleaning times, and the cleaning pressure and stand-off distance have little influence on it.
- (3)
- According to the change in the regular pattern of process parameters and the degree of influence on the evaluation index, the optimal process parameter with cleaning efficiency as the index is determined as A3B3C3D1, that is, 0.45 MPa pressure, 140 mm stand-off distance, 5 mm/s traverse rate, and one-time cleaning. The cleaning efficiency can reach 64.23%/min under this experiment. The optimization results of process parameters based on smaller R-sub are A1B1C3D1 and A1B3C3D1, that is to say, 0.25 MPa pressure, 60 mm or 140 mm stand-off distance, 5 mm/s traverse rate, and one-time cleaning. Under these parameters, the R-sub and the cleaning efficiency are almost zero. In the practical application of WSP, cleaning efficiency and the R-sub should be considered comprehensively. In other words, the adverse effect on the substrate of WSP cleaning is minimized while ensuring high cleaning efficiency. Therefore, combining the two index analyses, the transverse rate should be reduced from 5 mm/s to 3 mm/s, and the stand-off distance should be set as 140 mm. Under these conditions, the R-sub and cleaning efficiency were 5.37% and 38.65% /min, respectively.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Property | Value |
---|---|
Density | 6.8–7.3 g/cm3 |
Tensile strength | 250 MPa |
Hardness | 209 HB (est bar diameter: 30 mm) |
Melting point | 1145–1250 °C |
Elements | Content Percentage |
---|---|
C | 3.16–3.30 |
Si | 1.79–1.93 |
Mn | 0.89–1.04 |
S | 0.094–0.125 |
P | 0.120–0.170 |
Fe | Others |
Parameter | Value |
---|---|
Pressure (MPa) | 0.50 |
Stand-off distance (mm) | 200 |
Exposure time (s) | 20 |
Impact angle | 90° |
Nozzle diameter (mm) | 8 |
Nozzle type | Round nozzle |
Traverse length (mm) | 60 |
Abrasive type | 24# steel shot |
No. | Factors | |||
---|---|---|---|---|
A | B | C | D | |
Pressure/MPa | Stand-Off Distance/mm | Traverse Rate/mm∙s−1 | Cleaning Times | |
1 | 1 (0.25) | 1 (60) | 1 (1) | 1 (1) |
2 | 1 | 2 (100) | 2 (3) | 2 (2) |
3 | 1 | 3 (140) | 3 (5) | 3 (3) |
4 | 2 (0.35) | 1 | 2 | 3 |
5 | 2 | 2 | 3 | 1 |
6 | 2 | 3 | 1 | 2 |
7 | 3 (0.45) | 1 | 3 | 2 |
8 | 3 | 2 | 1 | 3 |
9 | 3 | 3 | 2 | 1 |
Parameter | Value |
---|---|
Pressure (MPa) | 0.25–0.35–0.45 |
Stand-off distance (mm) | 60–100–140 |
Traverse rate (mm/s) | 1–3–5 |
Cleaning times | 1–2–3 |
Impact angle | 90° |
Nozzle diameter (mm) | 8 |
Nozzle type | Round nozzle |
Traverse length (mm) | 60 |
Mixing volume ratio of abrasive and water | 1:15 |
Abrasive type | 60# white fused alumina |
No. | Experiment Result | |||
---|---|---|---|---|
Cleaning Efficiency /%∙min−1 | Removal Area Ratio /% | Removal Mass Ratio /% | Surface Roughness (Ra) /μm | |
1 | 25.25 | 25.25 | 45.02 | 2.41 |
2 | 38.90 | 25.93 | 38.47 | 3.26 |
3 | 44.92 | 26.95 | 39.74 | 3.24 |
4 | 28.60 | 28.60 | 55.83 | 2.88 |
5 | 53.51 | 10.70 | 23.79 | 4.37 |
6 | 29.00 | 58.00 | 112.11 | 2.73 |
7 | 51.52 | 20.61 | 37.16 | 3.55 |
8 | 17.78 | 53.33 | 170.14 | 3.00 |
9 | 63.87 | 21.29 | 33.21 | 3.86 |
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Wu, S.; Jia, X.; Xiong, S.; Li, F.; Ma, M.; Wang, X.; Li, C. Process Parameters Optimization of Wet Shot Peening for Paint Cleaning. Sustainability 2021, 13, 12915. https://doi.org/10.3390/su132212915
Wu S, Jia X, Xiong S, Li F, Ma M, Wang X, Li C. Process Parameters Optimization of Wet Shot Peening for Paint Cleaning. Sustainability. 2021; 13(22):12915. https://doi.org/10.3390/su132212915
Chicago/Turabian StyleWu, Shuangshuang, Xiujie Jia, Sheng Xiong, Fangyi Li, Mingliang Ma, Xing Wang, and Chenghao Li. 2021. "Process Parameters Optimization of Wet Shot Peening for Paint Cleaning" Sustainability 13, no. 22: 12915. https://doi.org/10.3390/su132212915