Chinese Journal of Lasers, Volume. 52, Issue 8, 0802201(2025)
Parameters Optimization of Laser Cladding Process for H13 Mold Steel Surface Based on Comprehensive Statistical Analysis Method
Figures & Tables(19)
Fig. 3. Morphology of the upper surface and X1 cross-section of the specimen (x0 represents the datum position; x1, x2, and x3 are used to indicate the position of X1, X2, and X3 cross-sections. Specimens 1, 7, and 8: x1=5 mm, x2=15 mm, x3=25 mm; specimen 2: x1=10 mm, x2=20 mm, x3=30 mm; specimens 3, 4, 5, 6, 9, 10, 11, 12, 14, and 15: x1=15 mm, x2=25 mm, x3=35 mm; specimen 13: x1=25 mm, x2=35 mm, x3=45 mm; specimen 16: x1=20 mm, x2=30 mm, x3=40 mm)
Fig. 4. Influence of process parameters on geometric morphology of the cladding layer
Fig. 6. Relationship between process parameters and comprehensive evaluation coefficient under different comprehensive evaluation methods
Fig. 7. Microhardness of cladding layer section. (a) Along the vertical direction; (b) along the horizontal direction
Fig. 8. Microstructures. (a) Cladding layer region; (b) the junction zone between the cladding layer and the heat affected zone; (c) heat affected zone (HAZ); (d) substrate
Fig. 9. Microstructures of cladding layer in each pass. (a) The first pass; (b) the second pass; (c) the third pass; (d) the fourth pass
Table 1. Factor and level table
View tableTable 1. Factor and level table
Level P /W V /（mm/s） G /（g/min） D /% 1 2000 4 10 35 2 2200 6 12 45 3 2400 8 14 55 4 2600 10 16 65
Table 2. Experimental schedule and corresponding response values
View tableTable 2. Experimental schedule and corresponding response values
No. Process parameter Geometric shape size Response value P /W V /
（mm/s）
G /
（g/min）
D /% Cladding layer width
W /mm
Cladding layer height
H /mm
Cladding layer area
Sc /mm2
Molten pool area
Sm /mm2
τ η 3 2000 4 10 35 18.100 0.782 11.114 9.197 0.783 0.453 5 2000 8 16 45 16.003 0.754 7.914 3.199 0.656 0.288 8 2000 6 14 65 12.369 1.318 10.805 2.223 0.663 0.171 15 2000 10 12 55 14.185 0.606 4.608 2.530 0.536 0.354 1 2200 4 12 45 15.798 1.173 14.501 7.270 0.783 0.334 7 2200 10 10 65 12.456 0.554 4.199 3.021 0.609 0.419 10 2200 8 14 35 17.916 0.527 7.432 4.826 0.787 0.394 14 2200 6 16 55 14.488 1.253 11.253 4.016 0.620 0.263 4 2400 10 16 35 18.029 0.477 6.663 5.106 0.775 0.434 6 2400 8 12 65 12.585 0.832 6.392 4.725 0.611 0.425 11 2400 6 10 45 16.354 0.648 7.516 10.535 0.710 0.584 16 2400 4 14 55 14.935 1.532 15.941 7.719 0.697 0.326 2 2600 8 10 55 14.486 0.638 5.766 7.836 0.625 0.576 9 2600 4 16 65 13.288 2.111 18.886 6.457 0.673 0.255 12 2600 6 12 35 18.246 0.730 9.396 13.583 0.706 0.591 13 2600 10 14 45 16.271 0.595 6.074 6.406 0.629 0.513
Table 3. Variance analysis of cladding layer morphology
View tableTable 3. Variance analysis of cladding layer morphology
Dependent variable Parameter F Influence degree /% Significance W Variance model 5120.832 <0.001 P 3.109 0.836 0.188 V 1.303 0.350 0.417 G 0.747 0.201 0.592 D 366.662 98.613 <0.001 H Variance model 148.247 <0.001 P 2.584 2.153 0.228 V 66.342 55.265 0.003 G 21.261 17.711 0.016 D 29.856 24.871 0.10 Sc Variance model 203.162 <0.001 P 2.228 1.566 0.264 V 118.206 83.094 0.001 G 19.441 13.666 0.018 D 2.380 1.673 0.247 Sm Variance model 57.832 0.004 P 15.940 33.302 0.028 V 11.880 24.820 0.041 G 7.816 16.329 0.072 D 12.229 25.549 0.040
Table 4. Analysis of variance for flatness and dilution rate
View tableTable 4. Analysis of variance for flatness and dilution rate
Dependent variable Parameter F Influence degree /% Significance τ Variance model 279.304 <0.001 P 1.047 8.260 0.485 V 3.164 24.963 0.185 G 0.413 3.258 0.756 D 8.051 63.519 0.060 η Variance model 237.667 <0.001 P 26.733 31.661 0.011 V 6.962 8.245 0.073 G 33.873 40.117 0.008 D 18.868 22.346 0.019
Table 5. EWM weight values
View tableTable 5. EWM weight values
Response value Weight W 0.410 τ 0.222 η 0.368
Table 6. Results of optimization analysis
View tableTable 6. Results of optimization analysis
No. Standardized result GRG value RSR value C value W τ η 3 0.975 0.993 0.329 0.767 0.708 0.636 5 0.619 0.477 0.722 0.577 0.652 0.632 8 0 0.504 1.000 0.616 0.505 0.513 15 0.309 0 0.563 0.443 0.372 0.382 1 0.584 0.984 0.612 0.646 0.678 0.654 7 0.015 0.290 0.410 0.399 0.263 0.274 10 0.944 1.000 0.470 0.769 0.762 0.692 14 0.361 0.335 0.781 0.531 0.557 0.531 4 0.963 0.954 0.374 0.749 0.677 0.650 6 0.037 0.297 0.395 0.399 0.280 0.271 11 0.678 0.691 0.017 0.511 0.520 0.428 16 0.437 0.640 0.630 0.538 0.620 0.556 2 0.360 0.354 0.036 0.402 0.292 0.254 9 0.156 0.548 0.801 0.532 0.572 0.505 12 1.000 0.676 0 0.667 0.586 0.506 13 0.664 0.369 0.185 0.483 0.457 0.420
Table 7. Experimental verification of GRA-EWM method
View tableTable 7. Experimental verification of GRA-EWM method
Response value Predicted value Experimental value Specimen No. 10 Sectional image W /mm 17.825 τ 0.833 η 0.437 GRG 0.819 0.871 0.769
Table 8. Experimental verification of TOPSIS-EWM method
View tableTable 8. Experimental verification of TOPSIS-EWM method
Response value Predicted value Experimental value Specimen No. 10 Sectional image W /mm 17.173 τ 0.798 η 0.359 C 0.848 0.709 0.692
Table 9. Experimental verification of RSR-EWM method
View tableTable 9. Experimental verification of RSR-EWM method
Response value Predicted value Experimental value Specimen No. 10 Sectional image W /mm 17.632 τ 0.758 η 0.354 RSR 0.915 0.767 0.762
Table 10. Elemental content of each region
View tableTable 10. Elemental content of each region
Region Mass fraction of each element /% C Si P S V Cr Mn Fe Mo Cladding layer 1.49 1.09 0.02 0.13 4.10 5.34 0.44 86.68 0.71 HAZ 0.65 1.11 0.05 0.19 0.91 5.12 0.48 90.80 0.70 Substrate 1.66 1.08 0.06 0.21 0.78 5.01 0.35 90.30 0.55
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Jianghong Lin, Maohua Du, Chuanxu Pan. Parameters Optimization of Laser Cladding Process for H13 Mold Steel Surface Based on Comprehensive Statistical Analysis Method[J]. Chinese Journal of Lasers, 2025, 52(8): 0802201
Paper Information
Category: Laser Surface Machining
Received: Oct. 9, 2024
Accepted: Dec. 3, 2024
Published Online: Mar. 17, 2025
The Author Email: Maohua Du (1337289843@qq.com)
CSTR:32183.14.CJL241252
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