Statistical Analysis of the Combined ECAP and Heat Treatment for Recycling Aluminum Chips Without Remelting
Abstract
:1. Introduction
2. Design of Experiments
3. Materials and Methods
3.1. Machining Chips Fabrication and Cold Compaction
3.2. Direct Hot Extrusion
3.3. Combination of ECAP Process and Heat Treatment
4. Results Analysis and Discussion
4.1. Tensile Testing Results
4.2. Regression Analysis for Ultimate Tensile Strength
4.3. Regression Analysis for Yield Strength
4.4. Percentage Elongation
4.5. Metallographic Analysis
5. Conclusions
- (1)
- The lower extrusion ratio could be used for SSR process if afterwards ECAP process in combination with heat treatment will be applied. Combination of the heat treatment and ECAP after DE significantly improved mechanical properties of the SSR samples compared with SSR sample obtained only with DE and afterwards one ECAP pass.
- (2)
- Description and prediction of the influence of heat treatment parameters on Rm and Rp0.2 was successfully performed utilizing statistical analysis approach. Quadratic mathematical models were suggested for description of the influence of heat treatment parameters on Rm and Rp0.2 of SSR samples. Increase in aging time slightly increases Rm and Rp0.2 for lower aging temperature (100 °C). However, for higher aging temperature (200 °C), increase in aging time decreases Rm and Rp0.2. For constant artificial aging temperature at 100 °C and higher solid solution time (180 min), increase in artificial aging time, also increases Rm value. For lower solid solution time (60 min), increase in aging time increases Rm just slightly. For constant aging temperature at 150 °C, shorter solid solution time (60 min) and artificial aging time (1 h) Rp0.2 values significantly increases. According to the statistical analysis, the influence of heat treatment parameters on percentage elongation cannot be described with statistically significant mathematical model and therefore, mean value of the percentage elongation was taken as final (PEmean = 9.7%).
- (3)
- Heat treatment assisted in the improvement of SSR samples quality by the simultaneous interparticle diffusion bonding, recovery and precipitation hardening. However, too high artificial aging temperature or to long artificial aging time leads to decrement of the SPD effects and precipitation over-aging which caused mechanical properties decrement. Finally, according to the optimization results maximal values for Rm and Rp0.2 of 356 and 336.6 MPa would be obtained if artificial aging temperature, artificial aging time, and solid solution time were set as 148.2 °C, 1 h, and 60 min, respectively.
- (4)
- According to the SEM + EDX analysis microstructure of the recycled samples was very homogeneous and there were not any visible cracks, voids or porosity. Qualitative chemical analysis performed by elemental mapping showed that visible intermetallic phase particles were consisted of the same elements for the SSR samples and for conventionally obtained sample.
Author Contributions
Funding
Conflicts of Interest
References
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Levels of Exp. Runs | Solid Solution Time (°C) | Artificial Aging Temperature (°C) | Artificial Aging Time (min) | Rm (MPa) | Rp0.2 (MPa) | PE (%) |
---|---|---|---|---|---|---|
1 | 106.9 | 200.0 | 3.53 | 286 | 266 | 8.2 |
2 | 60.0 | 200.0 | 8.00 | 248 | 226 | 9.6 |
3 | 105.0 | 155.1 | 1.11 | 362 | 326 | 10.5 |
4 | 180.0 | 200.0 | 2.43 | 292 | 278 | 9.2 |
5 | 115.2 | 154.1 | 5.16 | 336 | 320 | 8.8 |
6 | 105.0 | 100.0 | 5.26 | 349 | 318 | 10.2 |
7 | 180.0 | 100.0 | 5.94 | 322 | 289 | 10.8 |
8 | 60.0 | 200.0 | 1.00 | 300 | 292 | 7.2 |
9 | 180.0 | 100.0 | 5.94 | 334 | 296 | 10.8 |
10 | 180.0 | 200.0 | 8.00 | 264 | 240 | 11.2 |
11 | 128.3 | 100.0 | 1.00 | 308 | 288 | 8 |
12 | 60.0 | 150.0 | 6.79 | 330 | 312 | 8.6 |
13 | 60.0 | 200.0 | 1.00 | 318 | 307 | 9.8 |
14 | 180.0 | 200.0 | 8.00 | 256 | 232 | 9.8 |
15 | 60.0 | 100.0 | 8.00 | 328 | 296 | 9.9 |
16 | 120.0 | 198.5 | 7.06 | 259 | 234 | 11.5 |
17 | 60.0 | 100.0 | 2.45 | 314 | 286 | 9.5 |
18 | 180.0 | 143.0 | 1.00 | 328 | 293 | 11.9 |
19 | 60.0 | 100.0 | 8.00 | 320 | 288 | 9.7 |
20 | 60.0 | 100.0 | 2.45 | 317 | 298 | 7.1 |
Element | Si% | Fe% | Cu% | Mn% | Mg% | Zn% | Ti% | Cr% | Others% |
---|---|---|---|---|---|---|---|---|---|
Min.–Max. | 0.7–1.3 | 0–0.5 | 0–0.1 | 0.4–0.1 | 0.6–1.2 | 0–0.2 | 0–0.1 | 0–0.25 | 0–0.15 |
Turning Parameters | Value |
---|---|
Cutting speed | vc = 350 m/min |
Feed rate | f = 0.14 mm/rev |
Cutting depth | ap = 0.5 mm |
Chip geometry | - |
Length | lavg = 10 mm |
Width | wavg = 1.8 mm |
Thickness | tavg = 0.8 mm |
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Krolo, J.; Lela, B.; Dumanić, I.; Kozina, F. Statistical Analysis of the Combined ECAP and Heat Treatment for Recycling Aluminum Chips Without Remelting. Metals 2019, 9, 660. https://doi.org/10.3390/met9060660
Krolo J, Lela B, Dumanić I, Kozina F. Statistical Analysis of the Combined ECAP and Heat Treatment for Recycling Aluminum Chips Without Remelting. Metals. 2019; 9(6):660. https://doi.org/10.3390/met9060660
Chicago/Turabian StyleKrolo, Jure, Branimir Lela, Ivana Dumanić, and Franjo Kozina. 2019. "Statistical Analysis of the Combined ECAP and Heat Treatment for Recycling Aluminum Chips Without Remelting" Metals 9, no. 6: 660. https://doi.org/10.3390/met9060660