Optimization of the Surface Roughness and Chip Compression Ratio of Duplex Stainless Steel in a Wet Turning Process Using the Taguchi Method
Abstract
1. Introduction
2. Materials and Methods
2.1. Experimental Setup
2.2. Design of Experiments
3. Results and Discussions
3.1. Experimental Results
3.2. Taguchi Analysis
3.3. Analysis of Variance
4. Conclusions
- A cutting velocity of 200 m/min, feed of 0.05 mm/rev, and cutting depth of 1 mm are found to give the lowest surface roughness Ra that is equal to 0.433 µm;
- A cutting velocity of 200 m/min, feed of 0.15 mm/rev, and cutting depth of 0.5 mm are found to give the smallest CCR that is equal to 1.39, indicating the smallest plastic deformation during the material removal process;
- The experimental results proved that additional cooling allows us to achieve better surface roughness quality compared to dry and wet turning;
- The experimental data could be useful in collecting as much data as possible for the use of artificial intelligence techniques, i.e., for the training and validation of models; the lack of data provides overfitted models.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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C | Si | Mn | P | S | Cr | Mo | Ni | N |
---|---|---|---|---|---|---|---|---|
0.03 | 1 | 2 | 0.035 | 0.015 | 21–23 | 2.5–3.5 | 4.5–6.5 | 0.1–0.22 |
Parameters | Levels | ||||
---|---|---|---|---|---|
Description | Symbol | Unit | 1 | 2 | 3 |
Cutting velocity | Vc | m/min | 150 | 200 | 250 |
Feed | f | mm/rev | 0.05 | 0.1 | 0.15 |
Cutting depth | ap | mm | 0.5 | 1.0 | 1.5 |
Factors | Data of the Experiment | |||||
---|---|---|---|---|---|---|
Run Order | Cutting Velocity (m/min) | Feed (mm/rev) | Cutting Depth (mm) | Time of Experiment (s) | Material Removal Rate (mm3/min) | Volume of Removed Material (mm3) |
1 | 1 | 1 | 1 | 38 | 3750 | 2375 |
2 | 1 | 2 | 2 | 21 | 15,000 | 5250 |
3 | 1 | 3 | 3 | 15 | 33,750 | 8437.5 |
4 | 2 | 1 | 2 | 29 | 10,000 | 4833.3 |
5 | 2 | 2 | 3 | 17 | 30,000 | 8500 |
6 | 2 | 3 | 1 | 13 | 15,000 | 3250 |
7 | 3 | 1 | 3 | 24 | 18,750 | 7500 |
8 | 3 | 2 | 1 | 15 | 12,500 | 3125 |
9 | 3 | 3 | 2 | 11 | 37,500 | 6875 |
Cutting Conditions | Output Results | ||||||||
---|---|---|---|---|---|---|---|---|---|
Run | Cutting Velocity | Feed | Depth of Cut | Surface Roughness | Chip Evaluation | Max Hardness | |||
m/min | (mm/rev) | (mm) | Ra (µm) | Rz (µm) | Rz1max (µm) | Thickness (µm) | (CCR) | HV | |
1 | 150 | 0.05 | 0.5 | 0.448 | 3.177 | 3.373 | 105.2 | 2.1 | 241.4 |
2 | 150 | 0.1 | 1 | 0.974 | 5.696 | 6.502 | 189.05 | 1.9 | 266 |
3 | 150 | 0.15 | 1.5 | 2.155 | 10.483 | 11.056 | 277.4 | 1.85 | 235 |
4 | 200 | 0.05 | 1 | 0.433 | 3.133 | 3.512 | 116.7 | 2.33 | 256.2 |
5 | 200 | 0.1 | 1.5 | 1.023 | 6.375 | 8.009 | 164.7 | 1.65 | 277.1 |
6 | 200 | 0.15 | 0.5 | 2.637 | 11.993 | 12.854 | 208.33 | 1.39 | 260.7 |
7 | 250 | 0.05 | 1.5 | 0.554 | 3.936 | 4.497 | 98.24 | 1.97 | 248 |
8 | 250 | 0.1 | 0.5 | 0.746 | 4.41 | 5.098 | 160.7 | 1.61 | 248 |
9 | 250 | 0.15 | 1 | 1.885 | 10.473 | 12.541 | 238.6 | 1.59 | 280 |
Run: | Cutting Conditions | ||
---|---|---|---|
Cutting Velocity (m/min) | Feed (mm/rev) | Cutting Depth (mm) | |
Prediction | 250 | 0.05 | 1 |
Level | Vc | f | ap |
---|---|---|---|
1 | 0.1781 | 6.4582 | 0.3658 |
2 | −0.4498 | 0.8588 | 0.6643 |
3 | 0.7229 | −6.8658 | −0.5789 |
Delta | 1.1728 | 13.3240 | 1.2432 |
Rank | 3 | 1 | 2 |
Run: | Cutting Conditions | ||
---|---|---|---|
Cutting Velocity (m/min) | Feed (mm/rev) | Cutting Depth (mm) | |
Prediction | 250 | 0.15 | 0.5 |
Level | Vc | f | ap |
---|---|---|---|
1 | −5.788 | −6.560 | −4.480 |
2 | −4.852 | −4.687 | −5.650 |
3 | −4.685 | −4.077 | −5.194 |
Delta | 1.103 | 2.483 | 1.170 |
Rank | 3 | 1 | 2 |
Source | DF | Seq SS | Adj SS | Adj MS | F | P | Contribution (%) | Significance |
---|---|---|---|---|---|---|---|---|
Cutting velocity | 2 | 2.066 | 2.066 | 1.033 | 0.31 | 0.766 | 0.74 | Non-significant |
Feed | 2 | 268.550 | 268.550 | 134.275 | 39.71 | 0.025 | 95.94 | Significant |
Cutting depth | 2 | 2.527 | 2.527 | 1.263 | 0.37 | 0.728 | 0.903 | Non-significant |
Residual Error | 2 | 6.763 | 6.763 | 3.382 | ||||
Total | 8 | 279.907 |
Source | DF | Seq SS | Adj SS | Adj MS | F | P | Contribution (%) | Significance |
---|---|---|---|---|---|---|---|---|
Cutting velocity | 2 | 2.120 | 2.120 | 1.0598 | 1.81 | 0.356 | 13.74 | Non-significant |
Feed | 2 | 10.046 | 10.046 | 5.0232 | 8.59 | 0.104 | 65.14 | Non-significant |
Cutting depth | 2 | 2.085 | 2.085 | 1.0427 | 1.78 | 0.359 | 13.52 | Non-significant |
Residual Error | 2 | 1.170 | 1.170 | 0.5850 | ||||
Total | 8 | 15.421 |
Taguchi Analysis: Surface Roughness Ra | Taguchi Analysis: CCR | ||||
---|---|---|---|---|---|
S | R-Sq | R-Sq(adj) | S | R-Sq | R-Sq(adj) |
1.8389 | 97.58% | 90.33% | 0.7648 | 92.41% | 69.65% |
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Gyliene, V.; Brasas, A.; Ciuplys, A.; Jablonskyte, J. Optimization of the Surface Roughness and Chip Compression Ratio of Duplex Stainless Steel in a Wet Turning Process Using the Taguchi Method. Machines 2024, 12, 437. https://doi.org/10.3390/machines12070437
Gyliene V, Brasas A, Ciuplys A, Jablonskyte J. Optimization of the Surface Roughness and Chip Compression Ratio of Duplex Stainless Steel in a Wet Turning Process Using the Taguchi Method. Machines. 2024; 12(7):437. https://doi.org/10.3390/machines12070437
Chicago/Turabian StyleGyliene, Virginija, Algimantas Brasas, Antanas Ciuplys, and Janina Jablonskyte. 2024. "Optimization of the Surface Roughness and Chip Compression Ratio of Duplex Stainless Steel in a Wet Turning Process Using the Taguchi Method" Machines 12, no. 7: 437. https://doi.org/10.3390/machines12070437
APA StyleGyliene, V., Brasas, A., Ciuplys, A., & Jablonskyte, J. (2024). Optimization of the Surface Roughness and Chip Compression Ratio of Duplex Stainless Steel in a Wet Turning Process Using the Taguchi Method. Machines, 12(7), 437. https://doi.org/10.3390/machines12070437