# The Effects of Processing Parameters during the Wire Arc Additive Manufacturing of 308L Stainless Steel on the Formation of a Thin-Walled Structure

^{1}

^{2}

^{3}

^{4}

^{*}

^{†}

## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Experimental Setup

#### 2.2. Materials

#### 2.3. Design of Experiments (DOE)

#### 2.4. Metallographic Preparation and Observation

_{3}= 3:1) for 5 s. Nitric acid can oxidize the stainless steel surface with the formation of an oxide layer, and the HCl content of aqua regia can dissolve that. So, the surface is cleaned and, due to short contact time, is passivated. Observation of the weld bead section shape and the thin-wall wall section was conducted using an OLYMPUS GX51(Olympus Corporation, Tokyo, Japan) metallurgical optical microscope (OM). ImageJ 1.51 software was utilized to measure the geometric characteristics of the weld bead, including the bead height, bead depth, bead width, wetting angle, and dilution rate.

## 3. Results and Discussion

#### 3.1. Single-Pass Single-Layer Welding Seam Formation Test

#### 3.2. Influence of Process Parameters on Single-Pass Single-Layer Formation

#### 3.2.1. Effect of Process Parameters on Bead Height

_{0}is the constant, and b

_{1}to b

_{9}represent the linear and interactive coefficients. The terms X

_{1}, X

_{2}, X

_{3}, X

_{1}

^{2}, X

_{2}

^{2}, X

_{3}

^{2}, X

_{1}X

_{2}, X

_{1}X

_{3}, and X

_{2}X

_{3}correspond to the independent factors (process parameters). The correlation coefficients (R

^{2}), adjusted R

^{2}, and predicted R

^{2}values were determined using Equations (2)–(4), respectively [20].

#### 3.2.2. Effect of Process Parameters on Bead Depth

#### 3.2.3. Effect of Process Parameters on Bead Width

#### 3.2.4. Effect of Process Parameters on Wetting Angle

#### 3.2.5. Effect of Process Parameters on Dilution Rate

#### 3.3. Influence of Process Parameters on Accuracy of Single-Pass Multi-Layer Formation

#### 3.3.1. Influence of Parameter Optimization on Accuracy of Single-Pass Multi-Layer Formation

#### 3.3.2. Influence of Swing on Accuracy of Single-Pass Multi-Layer Formation

## 4. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

- Li, W.; Sugio, K.; Liu, X.; Yamamoto, M.; Guo, Y.; Zhu, S.; Sasaki, G. Microstructure Evolution and Mechanical Properties of 308L Stainless Steel Coatings Fabricated by Laser Hot Wire Cladding. Mater. Sci. Eng. A
**2021**, 824, 141825. [Google Scholar] [CrossRef] - Li, K.; Li, D.; Liu, D.; Pei, G.; Sun, L. Microstructure Evolution and Mechanical Properties of Multiple-Layer Laser Cladding Coating of 308L Stainless Steel. Appl. Surf. Sci.
**2015**, 340, 143–150. [Google Scholar] [CrossRef] - Zhang, K.; Xiong, J.; Zhang, G. Effect of Heat Treatment on Microstructure and Corrosion Properties of Double-Wire GTA Additive Manufactured 308L Stainless Steel. Mater. Lett.
**2022**, 309, 131362. [Google Scholar] [CrossRef] - Li, Y.; Yuan, Y.; Wang, D.; Fu, S.; Song, D.; Vedani, M.; Chen, X. Low Cycle Fatigue Behavior of Wire Arc Additive Manufactured and Solution Annealed 308 L Stainless Steel. Addit. Manuf.
**2022**, 52, 102688. [Google Scholar] [CrossRef] - Herzog, D.; Seyda, V.; Wycisk, E.; Emmelmann, C. Additive Manufacturing of Metals. Acta Mater.
**2016**, 117, 371–392. [Google Scholar] [CrossRef] - Dong, B.; Cai, X.; Lin, S.; Li, X.; Fan, C.; Yang, C.; Sun, H. Wire Arc Additive Manufacturing of Al-Zn-Mg-Cu Alloy: Microstructures and Mechanical Properties. Addit. Manuf.
**2020**, 36, 101447. [Google Scholar] [CrossRef] - Nagamatsu, H.; Sasahara, H.; Mitsutake, Y.; Hamamoto, T. Development of a Cooperative System for Wire and Arc Additive Manufacturing and Machining. Addit. Manuf.
**2020**, 31, 100896. [Google Scholar] [CrossRef] - Jia, C.; Liu, W.; Chen, M.; Guo, M.; Wu, S.; Wu, C. Investigation on Arc Plasma, Droplet, and Molten Pool Behaviours in Compulsively Constricted WAAM. Addit. Manuf.
**2020**, 34, 101235. [Google Scholar] [CrossRef] - Ma, Y.; Hu, Z.; Tang, Y.; Ma, S.; Chu, Y.; Li, X.; Luo, W.; Guo, L.; Zeng, X.; Lu, Y. Laser Opto-Ultrasonic Dual Detection for Simultaneous Compositional, Structural, and Stress Analyses for Wire + Arc Additive Manufacturing. Addit. Manuf.
**2020**, 31, 100956. [Google Scholar] [CrossRef] - Priarone, P.C.; Catalano, A.R.; Simeone, A.; Settineri, L. Effects of Deposition Parameters on Cumulative Energy Demand for Cold Metal Transfer Additive Manufacturing Processes. CIRP Ann.
**2022**, 71, 17–20. [Google Scholar] [CrossRef] - Benakis, M.; Costanzo, D.; Patran, A. Current Mode Effects on Weld Bead Geometry and Heat Affected Zone in Pulsed Wire Arc Additive Manufacturing of Ti-6-4 and Inconel 718. J. Manuf. Process.
**2020**, 60, 61–74. [Google Scholar] [CrossRef] - Erfanmanesh, M.; Abdollah-Pour, H.; Mohammadian-Semnani, H.; Shoja-Razavi, R. An Empirical-Statistical Model for Laser Cladding of WC-12Co Powder on AISI 321 Stainless Steel. Opt. Laser Technol.
**2017**, 97, 180–186. [Google Scholar] [CrossRef] - Yadav, P.; Khanna, P. Effect of Input Parameters on Weld Bead Geometry and Weld Dilution for Weld Surfacing of Flux Cored 308L Stainless Steel on Low Carbon Steel. Mater. Today Proc.
**2022**, 62, 3608–3616. [Google Scholar] [CrossRef] - Chen, M.; Zhang, D.; Wu, C. Current Waveform Effects on CMT Welding of Mild Steel. J. Mater. Process. Technol.
**2017**, 243, 395–404. [Google Scholar] [CrossRef] - de Oliveira, U.; Ocelík, V.; De Hosson, J.T.M. Analysis of Coaxial Laser Cladding Processing Conditions. Surf. Coat. Technol.
**2005**, 197, 127–136. [Google Scholar] [CrossRef] - Sun, Y.; Hao, M. Statistical Analysis and Optimization of Process Parameters in Ti6Al4V Laser Cladding Using Nd:YAG Laser. Opt. Lasers Eng.
**2012**, 50, 985–995. [Google Scholar] [CrossRef] - Qin, L.; Wang, K.; Li, X.; Zhou, S.; Yang, G. Review of the Formation Mechanisms and Control Methods of Geometrical Defects in Laser Deposition Manufacturing. Chin. J. Mech. Eng. Addit. Manuf. Front.
**2022**, 1, 100052. [Google Scholar] [CrossRef] - Tomar, B.; Shiva, S.; Nath, T. A Review on Wire Arc Additive Manufacturing: Processing Parameters, Defects, Quality Improvement and Recent Advances. Mater. Today Commun.
**2022**, 31, 103739. [Google Scholar] [CrossRef] - Jafari, D.; Vaneker, T.H.J.; Gibson, I. Wire and Arc Additive Manufacturing: Opportunities and Challenges to Control the Quality and Accuracy of Manufactured Parts. Mater. Des.
**2021**, 202, 109471. [Google Scholar] [CrossRef] - Pavan, A.R.; Chandrasekar, N.; Arivazhagan, B.; Kumar, S.; Vasudevan, M. Study of Arc Characteristics Using Varying Shielding Gas and Optimization of Activated-Tig Welding Technique for Thick AISI 316L(N) Plates. CIRP J. Manuf. Sci. Technol.
**2021**, 35, 675–690. [Google Scholar] [CrossRef] - Le, V.T.; Mai, D.S.; Doan, T.K.; Paris, H. Wire and Arc Additive Manufacturing of 308L Stainless Steel Components: Optimization of Processing Parameters and Material Properties. Eng. Sci. Technol. Int. J.
**2021**, 24, 1015–1026. [Google Scholar] [CrossRef] - Lai, X.M.; Luo, A.H.; Zhang, Y.S.; Chen, G.L. Optimal Design of Electrode Cooling System for Resistance Spot Welding with the Response Surface Method. Int. J. Adv. Manuf. Technol.
**2009**, 41, 226–233. [Google Scholar] [CrossRef] - Zhao, D.; Wang, Y.; Sheng, S.; Lin, Z. Multi-Objective Optimal Design of Small Scale Resistance Spot Welding Process with Principal Component Analysis and Response Surface Methodology. J. Intell. Manuf.
**2014**, 25, 1335–1348. [Google Scholar] [CrossRef] - Muhammad, N.; Manurung, Y.H.P.; Hafidzi, M.; Abas, S.K.; Tham, G.; Haruman, E. Optimization and Modeling of Spot Welding Parameters with Simultaneous Multiple Response Consideration Using Multi-Objective Taguchi Method and RSM. J. Mech. Sci. Technol.
**2012**, 26, 2365–2370. [Google Scholar] [CrossRef] - Dai, Y.L.; Yu, S.F.; Shi, Y.S.; He, T.Y.; Zhang, L.C. Wire and Arc Additive Manufacture of High-Building Multi-Directional Pipe Joint. Int. J. Adv. Manuf. Technol.
**2018**, 96, 2389–2396. [Google Scholar] - Xiong, J.; Lei, Y.; Chen, H.; Zhang, G. Fabrication of Inclined Thin-Walled Parts in Multi-Layer Single-Pass GMAW-Based Additive Manufacturing with Flat Position Deposition. J. Mater. Process. Technol.
**2017**, 240, 397–403. [Google Scholar] [CrossRef] - Dinovitzer, M.; Chen, X.; Laliberte, J.; Huang, X.; Frei, H. Effect of Wire and Arc Additive Manufacturing (WAAM) Process Parameters on Bead Geometry and Microstructure. Addit. Manuf.
**2019**, 26, 138–146. [Google Scholar] [CrossRef] - Li, W.; Liu, X.; Yamamoto, M.; Guo, Y.; Zhu, S.; Sugio, K.; Sasaki, G. Research on Interface Characteristics of 308L Stainless Steel Coatings Manufactured by Laser Hot Wire Cladding. Surf. Coat. Technol.
**2021**, 427, 127822. [Google Scholar] [CrossRef] - Le, V.T.; Mai, D.S.; Paris, H. Influences of the Compressed Dry Air-Based Active Cooling on External and Internal Qualities of Wire-Arc Additive Manufactured Thin-Walled SS308L Components. J. Manuf. Process.
**2021**, 62, 18–27. [Google Scholar] [CrossRef] - Martina, F.; Mehnen, J.; Williams, S.W.; Colegrove, P.; Wang, F. Investigation of the Benefits of Plasma Deposition for the Additive Layer Manufacture of Ti-6Al-4V. J. Mater. Process. Technol.
**2012**, 212, 1377–1386. [Google Scholar] [CrossRef] - Wang, C.; Suder, W.; Ding, J.; Williams, S. The Effect of Wire Size on High Deposition Rate Wire and Plasma Arc Additive Manufacture of Ti-6Al-4V. J. Mater. Process. Technol.
**2021**, 288, 116842. [Google Scholar] [CrossRef]

**Figure 2.**Variation rules of the characteristic parameters of the 308L thin-walled single-pass deposits: (

**a**) bead height; (

**b**) bead depth; (

**c**) bead width; (

**d**) wetting angle, (

**e**) dilution rate; (

**f**) WAAM process parameter databases (tungsten electrode angle, welding current, and welding speed) of the 308L according to the requirements.

**Figure 4.**Single layer interface with different process parameters: (

**a**) head, (

**b**) middle, and (

**c**) tail.

**Figure 5.**Schematic diagram of the geometric characteristics of a single-pass, single-layer weld: bead height (r), bead depth (p), and bead weight (w), (

**a**) r < p, w > r + p, (

**b**) r ≈ p, w > r + p, (

**c**) r > p, w > r + p, (

**d**) r < p, w ≈ r + p, (

**e**) the calculation method for dilution rate.

**Figure 6.**(

**a**) The effect of tungsten electrode angle on bead height, (

**b**) the effect of welding current on bead height, (

**c**) the effect of welding speed on bead height, (

**d**) comparison of predicted and actual values of bead height.

**Figure 7.**(

**a**) The interaction effect of tungsten electrode angle and welding current on the melt height, (

**b**) The interaction effect of tungsten electrode angle and welding speed on the melt height, (

**c**) The interaction effect of welding speed angle and welding current on the melt height.

**Figure 8.**(

**a**) The effect of tungsten electrode angle on bead depth, (

**b**) the effect of welding current on bead depth, (

**c**) the effect of welding speed on bead depth, (

**d**) comparison of predicted and actual values of bead depth.

**Figure 9.**(

**a**) The effect of tungsten electrode angle on bead width, (

**b**) the effect of welding current on bead width, (

**c**) the effect of welding speed on bead width, (

**d**) comparison of predicted and actual values of bead width.

**Figure 10.**(

**a**) The effect of tungsten electrode angle on wetting angle, (

**b**) the effect of welding current on wetting angle, (

**c**) the effect of welding speed on wetting angle, (

**d**) comparison of predicted and actual values of wetting angle.

**Figure 11.**(

**a**) The effect of tungsten electrode angle on dilution rate, (

**b**) the effect of welding current on dilution rate, (

**c**) the effect of welding speed on dilution rate, (

**d**) comparison of predicted and actual values of dilution rate.

**Figure 12.**Shape of single-pass single-layer welds after parameter optimization and 8 mm swing: (

**a**) 35°/135 A/100 mm/min, (

**b**) 35°/145 A/100 mm/min, (

**c**) 35°/135 A/120 mm/min, (

**d**) 35°/135 A/100 mm/min + 8 mm swing, (

**e**) 35°/145 A/100 mm/min + 8 mm swing, (

**f**) 35°/135 A/120 mm/min + 8 mm swing.

**Figure 13.**(

**a**,

**b**) are schematic diagrams of fish scale patterns formed by non-swing process and swing process, respectively.

**Figure 14.**Cross-sectional view of the weld after parameter optimization and swing, (

**a**) 35°/135 A/100 mm/min, (

**b**) 35°/145 A/100 mm/min, (

**c**) 35°/135 A/120 mm/min, (

**d**) 35°/135 A/100 mm/min + 8 mm swing, (

**e**) 35°/145 A/100 mm/min + 8 mm swing, (

**f**) 35°/135 A/120 mm/min + 8 mm swing.

**Figure 15.**Macro morphology of single-pass multilayer wall forming after parameter optimization and swing, (

**a**) 35°/135 A/100 mm/min, (

**b**) 35°/145 A/100 mm/min, (

**c**) 35°/135 A/120 mm/min, (

**d**) 35°/135 A/100 mm/min + 8 mm swing, (

**e**) 35°/145 A/100 mm/min + 8 mm swing, (

**f**) 35°/135 A/120 mm/min + 8 mm swing.

**Figure 16.**Local line roughness of single-pass multilayer walls after parameter optimization and swing, (

**a**) 35°/135 A/100 mm/min, (

**b**) 35°/145 A/100 mm/min, (

**c**) 35°/135 A/120 mm/min, (

**d**) 35°/135 A/100 mm/min + 8 mm swing, (

**e**) 35°/145 A/100 mm/min + 8 mm swing, (

**f**) 35°/135 A/120 mm/min + 8 mm swing.

**Figure 17.**Local surface morphology of single-pass multilayer walls after parameter optimization and swing, (

**a**) 35°/135 A/100 mm/min, (

**b**) 35°/145 A/100 mm/min, (

**c**) 35°/135 A/120 mm/min, (

**d**) 35°/135 A/100 mm/min + 8 mm swing, (

**e**) 35°/145 A/100 mm/min + 8 mm swing, (

**f**) 35°/135 A/120 mm/min + 8 mm swing.

**Figure 18.**Single-pass multi-layer wall sections after parameter optimization and swing; (

**a**) 35°/135 A/100 mm/min, (

**b**) 35°/145 A/100 mm/min, (

**c**) 35°/135 A/120 mm/min, (

**d**) 35°/135 A/100 mm/min + 8 mm swing, (

**e**) 35°/145 A/100 mm/min + 8 mm swing, (

**f**) 35°/135 A/120 mm/min + 8 mm swing, (

**g**) schematic of process efficiency.

**Figure 20.**Height of single-pass multilayer wall after parameter optimization and swing (

**a**) and forming efficiency (

**b**), the figure caption (a–f) are respectively: (a) 35°/135 A/100 mm/min, (b) 35°/145 A/100 mm/min, (c) 35°/135 A/120 mm/min, (d) 35°/135 A/100 mm/min + 8 mm swing, (e) 35°/145 A/100 mm/min + 8 mm swing, (f) 35°/135 A/120 mm/min + 8 mm swing.

Materials | C | Mn | Si | S | P | Ni | Cr | Mo | Cu | N | Fe |
---|---|---|---|---|---|---|---|---|---|---|---|

304 substrate | 0.05 | 1.09 | 0.45 | 0.003 | 0.032 | 8.00 | 18.08 | 0.012 | 0.14 | 0.054 | Bal. |

308L | 0.022 | 2.12 | 0.515 | 0.006 | 0.023 | 9.75 | 19.92 | 0.032 | 0.031 | 0 | Bal. |

Process Parameters | Details |
---|---|

Distance of electrode to substrate | 4 mm |

Angle of nozzle to substrate | 30° |

Angle of nozzle to tungsten | 60° |

Gas flow rate of GTAW torch | 15 L/min |

Gas flow rate of trailing shield cover | 15 L/min |

Post-argon flow duration | 5 s |

Dwell time between layers | 120 s |

Serial No. | Input Parameters | Symbols | Units | Levels | ||||
---|---|---|---|---|---|---|---|---|

1 | Tungsten electrode angle | A | ° | 15 | 25 | 35 | 45 | 55 |

2 | Welding current | B | A | 95 | 105 | 115 | 125 | 135 |

3 | Welding speed | C | mm/min | 100 | 120 | 140 | 160 | 180 |

Serial No. | A: Factor 1 | B: Factor 2 | C: Factor 3 | Response 1 | Response 2 | Response 3 | Response 4 | Response 5 |
---|---|---|---|---|---|---|---|---|

Tungsten Electrode Angle | Welding Current | Welding Speed | Bead Height | Bead Depth | Bead Width | Wetting Angle | Dilution Rate | |

(°) | (A) | (mm/min) | (μm) | (μm) | (μm) | (°) | (%) | |

1 | 15 | 95 | 100 | 4617.848 | 549.335 | 2878.795 | 135.924 | 4.755% |

2 | 15 | 105 | 120 | 4274.767 | 487.330 | 3324.733 | 126.695 | 4.338% |

3 | 15 | 115 | 140 | 3633.638 | 474.838 | 4058.800 | 114.996 | 6.390% |

4 | 15 | 125 | 160 | 2717.728 | 561.719 | 6731.990 | 66.843 | 14.511% |

5 | 15 | 135 | 180 | 2414.458 | 544.756 | 7202.880 | 61.706 | 14.699% |

6 | 25 | 95 | 160 | 4583.701 | 289.041 | 4558.627 | 113.251 | 2.829% |

7 | 25 | 105 | 180 | 3614.209 | 400.788 | 3659.849 | 111.559 | 4.511% |

8 | 25 | 115 | 100 | 3598.103 | 599.160 | 7114.498 | 86.976 | 8.197% |

9 | 25 | 125 | 120 | 3027.317 | 1342.338 | 6719.678 | 81.501 | 24.081% |

10 | 25 | 135 | 140 | 2448.061 | 1330.182 | 7153.620 | 62.860 | 32.191% |

11 | 35 | 95 | 120 | 4296.385 | 235.481 | 3342.230 | 117.668 | 2.496% |

12 | 35 | 105 | 140 | 3564.160 | 557.588 | 4522.106 | 105.016 | 8.057% |

13 | 35 | 115 | 160 | 3010.714 | 520.264 | 5521.721 | 82.435 | 8.688% |

14 | 35 | 125 | 180 | 2411.061 | 619.916 | 6910.416 | 63.019 | 16.717% |

15 | 35 | 135 | 100 | 3066.646 | 997.576 | 9152.847 | 68.903 | 17.977% |

16 | 45 | 95 | 180 | 4267.049 | 318.010 | 4230.122 | 113.386 | 3.938% |

17 | 45 | 105 | 100 | 4460.113 | 652.508 | 3815.834 | 122.753 | 6.653% |

18 | 45 | 115 | 120 | 3140.439 | 644.889 | 6398.481 | 82.586 | 15.170% |

19 | 45 | 125 | 140 | 2511.521 | 743.472 | 7736.503 | 63.033 | 21.663% |

20 | 45 | 135 | 160 | 2262.966 | 912.661 | 7948.921 | 59.236 | 28.306% |

21 | 55 | 95 | 140 | 4890.840 | 351.168 | 3362.547 | 133.353 | 2.728% |

22 | 55 | 105 | 160 | 4246.538 | 334.481 | 4888.712 | 108.007 | 4.517% |

23 | 55 | 115 | 180 | 3626.270 | 681.448 | 5224.573 | 97.183 | 11.127% |

24 | 55 | 125 | 100 | 3564.171 | 1087.386 | 7506.277 | 80.660 | 20.368% |

25 | 55 | 135 | 120 | 3168.731 | 1334.422 | 7647.319 | 73.923 | 27.924% |

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | Prob > F |
---|---|---|---|---|---|---|

Model | 1.459 × 10^{7} | 9 | 1.621 × 10^{6} | 39.75 | <0.0001 | significant |

A-A | 47,639.54 | 1 | 47,639.54 | 1.17 | 0.2969 | |

B-B | 1.047 × 10^{7} | 1 | 1.047 × 10^{7} | 256.66 | <0.0001 | |

C-C | 9.623 × 10^{5} | 1 | 9.623 × 10^{5} | 23.59 | 0.0002 | |

AB | 21,543.47 | 1 | 21,543.47 | 0.5282 | 0.4786 | |

AC | 0.0567 | 1 | 0.0567 | 1.389 × 10^{−6} | 0.9991 | |

BC | 2.592 × 10^{5} | 1 | 2.592 × 10^{5} | 6.36 | 0.0235 | |

A^{2} | 1.002 × 10^{6} | 1 | 1.002 × 10^{6} | 24.56 | 0.0002 | |

B^{2} | 1.868 × 10^{5} | 1 | 1.868 × 10^{5} | 4.58 | 0.0492 | |

C^{2} | 91,353.02 | 1 | 91,353.02 | 2.24 | 0.1552 | |

Residual | 6.118 × 10^{5} | 15 | 40,786.38 | |||

Cor Total | 1.520 × 10^{7} | 24 |

^{2}—0.9598, Adjusted R

^{2}—0.9356, Predicted R

^{2}—0.8559, Adeq Precision—20.9835.

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | Prob > F |
---|---|---|---|---|---|---|

Model | 1.891 × 10^{6} | 3 | 6.303 × 10^{5} | 19.33 | <0.0001 | significant |

A-A | 54,574.48 | 1 | 54,574.48 | 1.67 | 0.2098 | |

B-B | 1.505 × 10^{6} | 1 | 1.505 × 10^{6} | 46.17 | <0.0001 | |

C-C | 3.310 × 10^{5} | 1 | 3.310 × 10^{5} | 10.15 | 0.0044 | |

Residual | 6.847 × 10^{5} | 21 | 32,602.45 | |||

Cor Total | 2.575 × 10^{6} | 24 |

^{2}—0.7342, Adjusted R

^{2}—0.6962, Predicted R

^{2}—0.6260, Adeq Precision—13.6581.

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | Prob > F |
---|---|---|---|---|---|---|

Model | 6.694 × 10^{7} | 3 | 2.231 × 10^{7} | 37.68 | <0.0001 | significant |

A-A | 1.916 × 10^{6} | 1 | 1.916 × 10^{6} | 3.24 | 0.0864 | |

B-B | 6.466 × 10^{7} | 1 | 6.466 × 10^{7} | 109.19 | <0.0001 | |

C-C | 3.635 × 10^{5} | 1 | 3.635 × 10^{5} | 0.6139 | 0.4421 | |

Residual | 1.244 × 10^{7} | 21 | 5.922 × 10^{5} | |||

Cor Total | 7.938 × 10^{7} | 24 |

^{2}—0.8433, Adjusted R

^{2}—0.8210, Predicted R

^{2}—0.7772, Adeq Precision—17.2398.

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | Prob > F |
---|---|---|---|---|---|---|

Model | 13,069.07 | 3 | 4356.36 | 44.08 | <0.0001 | significant |

A-A | 34.00 | 1 | 34.00 | 0.3440 | 0.5638 | |

B-B | 12,589.10 | 1 | 12,589.10 | 127.39 | <0.0001 | |

C-C | 445.97 | 1 | 445.97 | 4.51 | 0.0457 | |

Residual | 2075.23 | 21 | 98.82 | |||

Cor Total | 15,144.30 | 24 |

^{2}—0.8630, Adjusted R

^{2}—0.8434, Predicted R

^{2}—0.8122, Adeq Precision—18.9664.

Source | Sum of Squares | df | Mean Square | F-Value | p-Value | Prob > F |
---|---|---|---|---|---|---|

Model | 1608.07 | 3 | 536.02 | 31.80 | <0.0001 | significant |

A-A | 45.82 | 1 | 45.82 | 2.72 | 0.1141 | |

B-B | 1545.35 | 1 | 1545.35 | 91.68 | <0.0001 | |

C-C | 16.90 | 1 | 16.90 | 1.00 | 0.3280 | |

Residual | 353.98 | 21 | 16.86 | |||

Cor Total | 1962.05 | 24 |

^{2}—0.8196, Adjusted R

^{2}—0.7938, Predicted R

^{2}—0.7372, Adeq Precision—15.9977.

Bead Height (μm) | Bead Depth (μm) | Bead Width (μm) | Wetting Angle (°) | Dilution Rate (%) | |
---|---|---|---|---|---|

a | 3018.700 | 1051.654 | 9231.270 | 72.66° | 2.528% |

b | 2786.026 | 935.615 | 11,650.265 | 54.957° | 3.816% |

c | 3118.908 | 1520.438 | 10,409.224 | 59.894° | 4.603% |

d | 2474.025 | 1129.722 | 12,233.838 | 51.758° | 5.516% |

e | 3350.619 | 1227.085 | 7187.254 | 78.733° | 3.386% |

f | 2376.039 | 1032.679 | 11,256.612 | 43.168° | 4.712% |

Number of Layers | Height (mm) | L (μm) | L_{i} (μm) | Forming Efficiency (%) | |
---|---|---|---|---|---|

a | 15 | 36,559.089 | 7241.048 | 11,328.519 | 63.921% |

b | 15 | 34,265.968 | 8016.998 | 11,591.895 | 69.157% |

c | 15 | 29,659.417 | 6656.058 | 10,509.323 | 63.336% |

d | 15 | 33,539.914 | 9501.562 | 10,842.430 | 87.631% |

e | 15 | 32,969.751 | 9628.981 | 10,329.996 | 93.214% |

f | 15 | 30,933.713 | 8404.616 | 8939.096 | 94.015% |

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**MDPI and ACS Style**

Liu, B.; Lan, J.; Liu, H.; Chen, X.; Zhang, X.; Jiang, Z.; Han, J.
The Effects of Processing Parameters during the Wire Arc Additive Manufacturing of 308L Stainless Steel on the Formation of a Thin-Walled Structure. *Materials* **2024**, *17*, 1337.
https://doi.org/10.3390/ma17061337

**AMA Style**

Liu B, Lan J, Liu H, Chen X, Zhang X, Jiang Z, Han J.
The Effects of Processing Parameters during the Wire Arc Additive Manufacturing of 308L Stainless Steel on the Formation of a Thin-Walled Structure. *Materials*. 2024; 17(6):1337.
https://doi.org/10.3390/ma17061337

**Chicago/Turabian Style**

Liu, Bang, Jun Lan, Hongqiang Liu, Xinya Chen, Xin Zhang, Zhengyi Jiang, and Jian Han.
2024. "The Effects of Processing Parameters during the Wire Arc Additive Manufacturing of 308L Stainless Steel on the Formation of a Thin-Walled Structure" *Materials* 17, no. 6: 1337.
https://doi.org/10.3390/ma17061337