Advances in Materials Science and Engineering
Volume 2017 (2017), Article ID 5131403, 11 pages
https://doi.org/10.1155/2017/5131403

Research Article

Effect of Equal Channel Angular Pressing on the Surface Roughness of Solid State Recycled Aluminum Alloy 6061 Chips

Adel Taha Abbas,¹ Mohamed Adel Taha,² Adham Ezzat Ragab,³ Ehab Adel El-Danaf,¹ and Mohamed Ibrahim Abd El Aal²

¹Department of Mechanical Engineering, College of Engineering, King Saud University, Riyadh, Saudi Arabia
²Department of Mechanical Design and Production, College of Engineering, Zagazig University, Sharkia, Egypt
³Department of Industrial Engineering, College of Engineering, King Saud University, Riyadh, Saudi Arabia

Correspondence should be addressed to Adel Taha Abbas; atabbas1954@yahoo.com

Received 4 January 2017; Revised 5 February 2017; Accepted 7 February 2017; Published 6 March 2017

Academic Editor: Pavel Lejcek

Copyright © 2017 Adel Taha Abbas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Solid state recycling through hot extrusion is a promising technique to recycle machining chips without remelting. Furthermore, equal channel angular pressing (ECAP) technique coupled with the extruded recycled billet is introduced to enhance the mechanical properties of recycled samples. In this paper, the surface roughness of solid state recycled aluminum alloy 6061 turning chips was investigated. Aluminum chips were cold compacted and hot extruded under an extrusion ratio (ER) of 5.2 at an extrusion temperature (ET) of 425°C. In order to improve the properties of the extruded samples, they were subjected to ECAP up to three passes at room temperature using an ECAP die with a channel die angle of 90°. Surface roughness ( and ) of the processed recycled billets machined by turning was investigated. Box-Behnken experimental design was used to investigate the effect of three machining parameters (cutting speed, feed rate, and depth of cut) on the surface roughness of the machined specimens for four materials conditions, namely, extruded billet and postextrusion ECAP processed billets to one, two, and three passes. Quadratic models were developed to relate the machining parameters to surface roughness, and a multiobjective optimization scheme was conducted to maximize material removal rate while maintaining the roughness below a preset practical value.

1. Introduction

In order to reduce energy consumption and CO₂ emissions in manufacturing processes, recycling of wastes became very important. The main methods used for scrap recycling are conventional and solid state recycling [1]. The conventional recycling, which involves remelting of scrap, has many disadvantages such as high energy consumption, high production and labor cost, and large number of operations. Furthermore, in case of aluminum chips recycling, the losses are about 50% of the recycled scrap due to high surface area to volume ratio of the chips and contamination with machining oils [2, 3]. The need for a recycling method in which the scrap can be recycled without remelting to avoid the disadvantages associated with the conventional method was the motivation of many recent investigations [1, 4–7] of solid state recycling techniques. It was found that recycling of aluminum alloys chips by solid state method through hot extrusion can produce approximately fully dense products [4]. Moreover, about 95% of the primary material can be used by avoiding metal loss during the remelting process [4]. Furthermore, solid state recycling process can be applied to produce finished or semifinished products directly [5–7]. In order to improve the mechanical properties of the extruded recycled billets, it can be subjected to severe plastic deformation to refine and homogenize the grain structure. Recently, several studies on solid state recycling of machining chips through severe plastic deformation (SPD) have been conducted [8–10]. SPD techniques induce remarkably high strains that are capable of refining bulk materials with coarse grain structures.

Equal channel angular pressing (ECAP) technique being the most prominent of SPD techniques has been widely used for producing ultra-fine-grained (UFG) metals and alloys. ECAP involves pressing the sample in a die having intersecting equal channels. The deformation is mainly carried out by simple shear while the cross-section is maintained. This means that the samples can be repeatedly pressed to accumulate large amount of plastic strain that is capable of breaking down the coarse grains into submicron grains. During deformation the grain develop subgrains with low angle boundaries along with high dislocation density. Further deformation causes the subgrains to develop into grains with high angle boundaries. The associated enhancement in mechanical properties has been demonstrated in many previous works [11–15].

Abbas et al. [16] investigated the surface roughness for five starting material conditions (annealed and ECAP processed to 1, 2, 3, and 4 passes) for 1050 aluminum alloy. Quadratic models that related the four surface roughness (, , and ) values to the three cutting parameters (cutting speed, feed rate, and depth of cut) were developed, while the fourth parameter (number of ECAP passes) was considered as categorical factor. The results showed that optimum (minimum) surface roughness was achieved at minimum depth of cut (0.15 mm) and minimum feed rate (0.0 5 mm/rev) with slightly different cutting speeds that ranged between 193 m/min for and 207.5 m/min for . The surface quality of the ECAP processed material was found to be much superior compared to its annealed counterpart, for the same cutting conditions.

Khamis et al. [17] investigated the mechanical properties of recycled AA6061 chip that was produced from high speed milling. ANOVA analysis showed that holding compaction time was the most influential parameter whereas chip size had the least effect. The desirability function concluded that longer holding time and more precompaction with large chip size will give the higher tensile strength (UTS) value.

Chan and Lajis [18] investigated the cold compaction of aluminum 6061 chips to conclude that the optimum pressure is 650 MPa. The associated density was reported to be about 98.5% of the reference sample without going into any sintering process. They concluded that pressureless sintering breaks the interlocking which increases the gaps that increase the overall volume which causes the density of the compressed specimen to be reduced. They concluded that the mechanical properties of the compacted samples are still lower than their cast counterpart.

Duflou et al. [19] investigated the solid state recycling techniques of aluminum alloys directly from production scrap. They used three different techniques, namely, hot extrusion, screw extrusion, and spark plasma sintering (SPS), and compared them with the conventional remelting route for reference. It was concluded that aluminum recycling reduced the environmental impact with preferential material and energy savings. An overall impact reduction with a factor of 2 for the SPS route and 3-4 for the extrusion routes was reported.

Chiba and Yoshimura [7] investigated the solid state recycling of Al-Si alloy chips produced by milling and turning. Cold compaction into columnar billets that were subsequently profile-extruded into equilateral c-channels at 600 K, under extrusion ratios of 10 and 18, was performed. Uniaxial tensile tests showed that the dense recycled material had a higher ductility than the original ingot, with a reduction of around 30% in the ultimate tensile strength. The material recycled from the turning chips exhibited insufficient bonding, as compared to that recycled from the milling chips under the same conditions, thereby resulting in inferior mechanical properties.

The objective of the current work is to investigate the surface roughness, as an indicator of product surface quality, of solid state recycled 6061 aluminum chips produced by dry turning. Solid state recycling involved three steps comprising cold compaction followed by hot extrusion and finally for improving mechanical properties the extruded billet was further deformed in an equal channel die up to one, two, and three passes. Cutting parameters, namely, depth of cut, feed rate, and cutting speed, will be the process variables considered in a quadratic model that relates surface roughness to experimental machining conditions.

2. Materials and Methods

The material used in this paper is aluminum alloy AA6061 (as-received extruded rod). Table 1 presents the chemical composition of this alloy. The machined chips were prepared by dry turning of the as-received rod under the following cutting conditions: cutting speed of 88 m/min , feed of 1 mm/rev , and depth of cut of 1 mm . The chips were placed in a die with a diameter of 25 mm, cold compacted at room temperature, and then hot extruded at a temperature of 425°C with an extrusion ratio of 5.2. In order to improve the properties of the extruded samples, the samples were subjected to ECAP process up to three passes at room temperature using an ECAP die with a channel die angle equal 90°.

Table 1: Chemical composition of Aluminum Alloy AA6061.

Si
Mg
Fe
Cu
Mn
Others
Al

0.8
0.85
0.48
0.26
0.051
0.329
Balance

The microstructure of as-received and extruded specimens was examined using optical microscopy on Zeiss Axio Imager. On the other hand, after ECAP, the microstructure was examined using FEI INSPECT S50 scanning electron microscope (SEM), because of the expected fine microstructure. Metallographic specimens were ground, polished, and etched using kellers reagent. Vickers microhardness was measured under an applied loading of 100 gf and a dwell time of 15 sec at room temperature using Buehler Micromet 5100 device. The tensile test was conducted at room temperature using LR300 K (300 kN) universal testing machine. Tensile tests were performed at an initial strain rate of  s⁻¹ at room temperature. Tensile test specimens were fabricated parallel to extrusion and ECAP direction in accordance with ASTM-B557-06.

The final processed billets were machined using Emco Concept Turn 45 CNC lathe. This machine is equipped with Sinumeric 840-D. All test runs were done using CNC part program. The specifications for tool holder and insert are SVJCL2020K16 and VCGT160404 FN-ALU, respectively. The clearance angle, cutting edge angle, and nose radius are maintained at 5°, 35° and 0.4 mm, respectively. All cutting parameters were controlled via CNC part program and all the experiments were conducted in wet conditions. The surface roughness was evaluated using surface roughness tester TESA. The test specimens had an initial diameter of 12 mm and a length of 100 mm. The test specimens were divided into six areas. The first area with a length of 40 mm was used for chuck clamping, and the other four areas with 10 mm for each and separated by a groove of 2 mm were used for random machining with different cutting parameters and the last area was used for centering. The test specimen drawing is shown in Figure 1. The test specimens had four different starting conditions: hot extruded at 425°C and ECAP up to three passes. The cutting parameters and values of surface roughness (, and ) and the calculated material removal rate were recorded in the Appendix. Where is the arithmetic average deviation of the assessed profile (µm) and is the average maximum height of the profile (µm).

Figure 1: Test specimen drawing.

3. Design of Experiments

Box-Behnken design is one of response surface methodology (RSM) designs that is used extensively in studying and optimizing surface roughness of different machining processes through several publications [20–23]. RSM is a collection of statistical and mathematical techniques used to optimize a considered output variable, or response (represented in the model by the dependent variable) that is influenced by a set of controllable input variables, or factors (represented in the model by the independent variables) [24].

The Box-Behnken design was first introduced in 1960 by Box and Behnken [24]. In this research a rotatable Box-Behnken design consisting of 60 experiments was built including four factors, namely, cutting speed, depth of cut, feed rate, and specimen condition. Table 2 summarizes the studied factors and their levels. The specimen condition was treated as a categorical variable, while the other factors were treated as continuous variables. The Appendix illustrates the full list of experiments with measured response values ( and ) in micrometers.

Table 2: The cutting parameters and their levels used in the Box-Behnken design.

Designation
Process parameter
Level 1
Level 2
Level 3
Level 4

A
V
100
150
200
—

B
d
0.10
0.25
0.40
—

C

0.012
0.081
0.15
—

D
Specimen condition
No ECAP
One pass ECAP
Two passes ECAP
Three passes ECAP

4. Results and Discussions

The microstructures of the as-received sample are shown in Figure 2(a). It consists of coarse-grained structure with grain size of about 48 µm. On the other hand, the microstructure of the hot extruded specimen consists of fine grains of about 13.5 µm, as shown in Figure 2(b). The finer grained microstructure is caused by severe plastic strain imposed during the recycling processes and the positive effect of chip boundaries which can act as barriers between grains to prevent grain growth [25–28]. The decrease in grain size was congruent with previous work done by Haase et al. [25] where the grain size of the as-received AA-6060 alloy was 385 µm, while it was 31.8 µm for the hot extruded chips at 450°C. Also, Selmy et al. [26, 27] recycled AA-6061 chips through hot extrusion; the grain size was 48 µm for as-received samples while it was 15.8 and 10.9 µm for the recycled samples produced by hot extrusion at 500 and 350°C, respectively. Moreover in previous work by Hu et al. [28], the Mg chips were classified into three different groups based on its size. The Mg chips were cold compacted and followed by hot extrusion at 400°C. The grain size of the as-received sample was 200 µm, while it was 22, 25, and 11 µm for the three different groups of Mg chips recycled by hot extrusion. SEM micrographs of ECAPed samples after 1 and 3 passes are shown in Figures 2(c) and 2(d), respectively. It is obvious that additional grain refinement is exhibited with increasing number of ECAP passes. The grain size for the ECAPed samples processed to 1 and 3 passes is 5 and 3.25 µm, respectively.

(a)

(b)

(c)

(d)

Figure 2: Microstructure of (a) as-received, (b) ET = 425°C, (c) ECAP-1, and (d) ECAP-3.

Table 3 presents the relative density, microhardness, and ultimate tensile strength; elongation to failure and grain size of the solid state recycled aluminum alloy 6061 chips after extrusion and after the extruded billet were processed by ECAP to one, two, and three passes. The values are presented in Table 3 for the properties of the solid state recycled billets point towards the successfulness of recycling the chips into a consolidated bulk materials via cold compaction, followed by hot extrusion and finally ECAP. Table 3 shows the influence of number of ECAP passes on the microhardness of recycled samples. The microhardness has increased from 43 HV after extrusion to about 83 HV when extrusion was coupled with ECAP to 3 passes, which means that the hardness is almost doubled. Also, the ultimate tensile strength has increased from 115 to 307 MPa, which means that the tensile strength is almost tripled. This remarkable increase in mechanical strength is mainly due to the high dislocation density and the grain refinement associated with severe deformation accompanied with ECAP. Room temperature ECAP deformation has also resulted in improving the relative density. The increase in mechanical strength is expected to have significant effect on surface roughness.

Table 3: Effect of ECAP process on the Solid Sate Recycled Aluminum Alloy 6061 chips after Extrusion temperature 425°C.

Description
ET = 425°C
ECAP-1
ECAP-2
ECAP-3

Relative density %
96.4
99
99.8
99.8

Microhardness, Vickers
43
76.25
80.75
82.75

Ultimate T. Strength, MPa
114.7
198
230.8
306.4

Elongation to failure, mm
9.85
10.3
11.2
12.3

Grain size, µm
13.5
5.22
4
3.25

Figures 3 and 4 show the variation of both and versus the specimen condition, respectively. The roughness was measured at the same machining conditions (cutting speed of 150 m/min, depth of cut of 0.25 mm, and feed rate of 0.081 mm/rev.) which embrace the center point of the Box-Behnken design. The figures illustrate that the roughness values of studied specimens decrease with the number of ECAP passes. The change between extruded specimens (no ECAP) and one pass ECAP specimens is significantly high. Extra passes reduce the value of surface roughness but with less slope.

Figure 3: Surface roughness, (µm) versus specimen condition.

Figure 4: Surface roughness, (µm) versus specimen condition.

A quadratic model of the form given in (1) was fitted to the data using Minitab 17 software depending on the Box-Behnken design. Stepwise technique was used to reduce the model into significant terms only. Stepwise is an automated technique that adds terms to the model one by one. The added term is kept in the model if it has a significant effect ( value < 0.05); otherwise, it is removed. The process is repeated until the model includes only all of the significant term.

where is the constant term, represents the linear effects, represents the pure quadratic effects, and represents the second level interaction effects. Table 4 illustrates the quadratic models developed for and . The specimen condition (factor ) and its significant interactions are not included in the equation since it is treated as a categorical factor as mentioned before. The adequacy of the quadratic models was tested through calculating the coefficient of determination. Adjusted R-squared and predicted R-squared were calculated as 99% and 98% for , respectively, and 95% and 93% for , respectively. Anderson-Darling test was conducted to check the normality of residuals with a result of value = 0.695 for and 0.169 for assuming normally distributed residuals. The null hypothesis of such a test is that the data are normal and a value < 0.05 proves nonnormality.

Table 4: Quadratic models for , and .

Response

Equation

1
1.334 − 0.00971A − 2.101B − 9.972C + 0.000036A ² + 4.468B ² + 120.55C ² + 4.56B C

2
1.191 − 0.00971A − 2.101B − 9.972C + 0.000036A ² + 4.468B ² + 120.55C ²+ 4.56B C

3
1.153 − 0.00971A − 2.101B − 9.972C + 0.000036A ² + 4.468B ² + 120.55C ² + 4.56B C

4
1.130 − 0.00971A − 2.101B − 9.972C + 0.000036A ² + 4.468B ² + 120.55C ² + 4.56B C

1
7.04 − 0.01399A − 27.97B − 51.62C + 36.90B ² + 496.6C ² + 0.0771A B + 0.1211A C

2
5.77 − 0.01399A − 27.97B − 51.62C + 36.90B ² + 496.6C ² + 0.0771A B + 0.1211A C

3
5.57 − 0.01399A − 27.97B − 51.62C + 36.90B ² + 496.6C ² + 0.0771A B + 0.1211A C

4
5.45 − 0.01399A − 27.97B − 51.62C + 36.90B ² + 496.6C ² + 0.0771A B + 0.1211A C

Material removal rate (MRR) was calculated for each run using (2), where V is surface cutting speed (m/min.), is feed rate (mm/rev.), and d is depth of cut (mm). Optimization process was run using the desirability function approach to maximize MRR while maintaining below 0.8 m, which is practically adopted in industry.

Desirability function approach was used to estimate the values of studied process parameters that maximize the MRR keeping the at levels not exceeding a practical value of 0.8 μm. The optimization plot, illustrated in Figure 5, shows that an optimum MRR of 5.812 cm³/min with of 0.520 μm is obtained at cutting speed of 195 m/min., depth of cut of 0.4 mm, and feed rate of 0.073 mm/rev, for three-pass ECAP alloy (specimen condition 4).

Figure 5: Optimization plot for .

ANOVA was used to examine the effect of studied factors, in both linear and quadratic forms, and their interactions for their significance in the model. The results for , illustrated in Table 5, show that all factors has significant effect on with their both linear and quadratic terms. The feed rate, by far, had the greatest influence on the surface roughness in both its linear and quadratic terms.

Table 5: ANOVA results for .

Source
DF
Adj SS
Adj MS
-value
value

Model
10
23.0431
2.3043
475.18
0

Linear
6
18.0698
3.0116
621.05
0

A
1
0.0761
0.0761
15.7
0

B
1
0.1812
0.1812
37.37
0

C
1
17.436
17.436
3595.57
0

D
3
0.3765
0.1255
25.88
0

Square
3
4.9376
1.6459
339.4
0

1
0.1172
0.1172
24.17
0

1
0.1492
0.1492
30.77
0

1
4.8654
4.8654
1003.32
0

2-way interaction
1
0.0356
0.0356
7.35
0.009

1
0.0356
0.0356
7.35
0.009

Error
49
0.2376
0.0048

Lack-of-fit
41
0.2373
0.0058
169.84
0

Pure error
8
0.0003
0

Total
59
23.2807

Figure 6 shows the interaction plot for depth of cut and feed rate which is the only significant interaction affecting . Although the interaction is significant, it has little effect on the variation of which is illustrated by almost parallel curves in the plot. The same pattern is illustrated in the response surface given in Figure 7. The ANOVA results for showed the same patterns except that the significant interactions are cutting speed/depth of cut and cutting speed/feed rate.

Figure 6: Interaction plot of depth of cut and feed rate for .

Figure 7: Response surface plot for versus depth of cut and feed rate at a mean cutting speed of 150 m/min.

To validate the model, extra 12 experimental runs were conducted. Three cutting conditions were selected for the four starting specimen conditions (ET-425°C, ECAP-1, ECAP-2, and ECAP-3). Two among these three conditions were taken within the data range, one of which was the predicted optimum condition. The third condition was taken out of the data range. For all these 12 conditions, the measured surface roughness values were compared to the predicted ones as shown in Table 6. Figure 8 shows a scatter plot for both measured and predicted values. It is clear from the figure that the relation between them is linear with calculated of 0.99. It is worth mentioning that the machining parameters that corresponded to the optimum condition of and MMR (cutting speed of 195 m/min., depth of cut of 0.40 mm, and feed rate of 0.073 mm/rev) yielded an experimental value of of 0.502 compared to the predicted value of 0.520 which exhibits less than 5% error.

Table 6: Extra runs for valediction and verification of the predicted equations in Table 4.

Run Order
Condition
Surface Speed (m/min)
Depth of cut (mm)
Feed (mm/rev)
, (µm)

Experimental
Predicted

1
ET-425
125
0.325
0.125
1.378
1.294

2
ET-425
195
0.400
0.073
0.758
0.732

3
ET-425
250
0.500
0.20
4.88
4.507

4
ECAP-1
125
0.325
0.125
1.267
1.151

5
ECAP-1
195
0.400
0.073
0.654
0.589

6
ECAP-1
250
0.500
0.20
4.589
4.364

7
ECAP-2
125
0.325
0.125
1.190
1.113

8
ECAP-2
195
0.400
0.073
0.610
0.551

9
ECAP-2
250
0.500
0.20
4.303
4.326

10
ECAP-3
125
0.325
0.125
1.082
1.090

11
ECAP-3
195
0.400
0.073
0.502
0.520

12
ECAP-3
250
0.500
0.20
4.223
4.303

Figure 8: Scatter plot for the predicted versus experimental values for the (12) validation runs.

5. Conclusion

Solid state recycling of 6061 aluminum chips was conducted. The final bulk material was produced via cold compaction followed by hot extrusion and finally equal channel angular pressing for one, two, and three passes. Mechanical properties revealed the effectiveness of the compaction route in producing a densified product. Surface roughness was measured for four materials conditions comprising as extruded sample as well as samples extruded and ECAP processed to one, two, and three passes. The sample ECAP processed to three passes exhibited the highest hardness and consequently gave the lowest surface roughness. Box-Behnken experimental design was used to investigate the effect of three machining parameters (cutting speed, feed rate, and depth of cut) on the surface roughness of the machined specimens. A quadratic model was developed that related and to the machining parameters, with the material condition being a categorical variable. Feed rate was concluded to be the most influential parameter affecting surface roughness. Multiobjective optimization results showed that the minimum value of MRR was calculated as 5.812 cm³/min for surface roughness of 0.520 μm at cutting speed of 195 m/min., depth of cut of 0.40 mm, and feed rate of 0.073 mm/rev. (12) validation experimental tests were conducted with three new cutting conditions. The difference between the experimental and predicted values of for the new 12 experiments was in the range of 3–10%, which proves the applicability of the developed models.

Appendix

See Table 7.

Table 7

Run order
Condition
Surface speed (M/min)
Depth of cut (mm)
Feed (mm/rev)
(Mm)
(Mm)
Material removal rate (Cm³/min)

1
ET-425
100
0.4
0.081
0.862
3.237
3.240

2
ET-425
200
0.4
0.081
0.907
6.696
6.480

3
ET-425
150
0.4
0.012
0.396
2.853
0.720

4
ET-425
150
0.4
0.15
2.034
11.016
9.000

5
ET-425
100
0.25
0.012
0.338
2.952
0.300

6
ET-425
200
0.25
0.012
0.595
4.109
0.600

7
ET-425
100
0.25
0.15
1.959
9.350
3.750

8
ET-425
200
0.25
0.15
2.058
11.010
7.500

9
ET-425
150
0.25
0.081
0.419
3.161
3.038

10
ET-425
150
0.25
0.081
0.425
3.217
3.038

11
ET-425
150
0.25
0.081
0.427
3.212
3.038

12
ET-425
100
0.1
0.081
0.509
3.695
0.810

13
ET-425
200
0.1
0.081
0.577
3.381
1.620

14
ET-425
150
0.1
0.012
0.353
2.699
0.180

15
ET-425
150
0.1
0.15
1.870
10.418
2.250

16
ECAP-1
100
0.4
0.081
0.574
2.837
3.240

17
ECAP-1
200
0.4
0.081
0.645
5.493
6.480

18
ECAP-1
150
0.4
0.012
0.256
2.053
0.720

19
ECAP-1
150
0.4
0.15
1.985
8.808
9.000

20
ECAP-1
100
0.25
0.012
0.296
1.725
0.300

21
ECAP-1
200
0.25
0.012
0.329
2.113
0.600

22
ECAP-1
100
0.25
0.15
1.617
6.083
3.750

23
ECAP-1
200
0.25
0.15
1.824
8.624
7.500

24
ECAP-1
150
0.25
0.081
0.382
2.444
3.038

25
ECAP-1
150
0.25
0.081
0.378
2.398
3.038

26
ECAP-1
150
0.25
0.081
0.369
2.378
3.038

27
ECAP-1
100
0.1
0.081
0.435
2.272
0.810

28
ECAP-1
200
0.1
0.081
0.504
3.021
1.620

29
ECAP-1
150
0.1
0.012
0.242
1.694
0.180

30
ECAP-1
150
0.1
0.15
1.750
10.046
2.250

31
ECAP-2
100
0.4
0.081
0.545
2.695
3.240

32
ECAP-2
200
0.4
0.081
0.613
5.218
6.480

33
ECAP-2
150
0.4
0.012
0.243
1.950
0.720

34
ECAP-2
150
0.4
0.15
1.886
8.368
9.000

35
ECAP-2
100
0.25
0.012
0.281
1.639
0.300

36
ECAP-2
200
0.25
0.012
0.313
2.007
0.600

37
ECAP-2
100
0.25
0.15
1.536
5.779
3.750

38
ECAP-2
200
0.25
0.15
1.733
8.193
7.500

39
ECAP-2
150
0.25
0.081
0.363
2.322
3.038

40
ECAP-2
150
0.25
0.081
0.359
2.278
3.038

41
ECAP-2
150
0.25
0.081
0.351
2.259
3.038

42
ECAP-2
100
0.1
0.081
0.413
2.158
0.810

43
ECAP-2
200
0.1
0.081
0.479
2.870
1.620

44
ECAP-2
150
0.1
0.012
0.230
1.609
0.180

45
ECAP-2
150
0.1
0.15
1.663
9.544
2.250

46
ECAP-3
100
0.4
0.081
0.529
2.614
3.240

47
ECAP-3
200
0.4
0.081
0.594
5.062
6.480

48
ECAP-3
150
0.4
0.012
0.236
1.892
0.720

49
ECAP-3
150
0.4
0.15
1.829
8.117
9.000

50
ECAP-3
100
0.25
0.012
0.273
1.590
0.300

51
ECAP-3
200
0.25
0.012
0.303
1.947
0.600

52
ECAP-3
100
0.25
0.15
1.490
5.605
3.750

53
ECAP-3
200
0.25
0.15
1.681
7.947
7.500

54
ECAP-3
150
0.25
0.081
0.352
2.252
3.038

55
ECAP-3
150
0.25
0.081
0.348
2.210
3.038

56
ECAP-3
150
0.25
0.081
0.340
2.191
3.038

57
ECAP-3
100
0.1
0.081
0.401
2.094
0.810

58
ECAP-3
200
0.1
0.081
0.464
2.784
1.620

59
ECAP-3
150
0.1
0.012
0.223
1.561
0.180

60
ECAP-3
150
0.1
0.15
1.613
9.257
2.250

Nomenclature

: | Depth of cut, mm
ECAP: | Equal channel angular pressing
ER: | Extrusion ratio
ET: | Extrusion temperature, °C
: | Channel die angle
: | Feed rate, mm/rev
MRR: | Material removal rate, cm³/min
: | Spindle speed, rpm
: | The arithmetic average deviation of the assessed profile, µm
: | The average maximum height of the profile, µm
Status: | for extrude temperature 425°C, one pass ECAP, (3) two passes ECAP, and (4) Three passes ECAP
: | Surface speed, meter/min.

Competing Interests

The authors declare that they have no competing interests.

Acknowledgments

This Project was supported by King Saud University, Deanship of Scientific Research, College of Engineering Research Center. Authors would like to thank Twasol Research Excellence Program (TRE Program), King Saud University, Riyadh, Saudi Arabia, for support.

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