Control rules of surface integrity and formation of metamorphic layer in high-speed milling of 7055 aluminum alloy

Abstract

Orthogonal experiments were conducted to investigate the effects of parameters on surface integrity in milling 7055 aluminum alloy. In order to correlate metamorphic layer with thermal and mechanical phenomena developed during milling, milling force and temperature fields of machined surface were obtained with finite element method, while milling speed and feed per tooth were paid particular attention to study formation of metamorphic layer. Experiment results show that when milling speed, feed per tooth, milling depth, and milling width are 1100 m/min, 0.02 mm/z, 0.7 mm, and 6 mm, respectively, obtained surface roughness, surface residual stress in X direction, surface residual stress in Y direction, and surface micro-hardness are Ra 0.258 µm, −123 MPa, −137 MPa, and 193.76 HV_0.025, respectively. From precision machining to rough machining, depth of compressive residual stress layer increases from 35 to 45 µm, and the depth of plastic deformation layer increases from 5 to 20 µm. Finally, the formation of metamorphic layer can be explained by thermo-mechanical coupling effects.

Keywords

7055 Aluminum alloy surface roughness surface topography surface residual stresses surface micro-hardness metamorphic layer

Introduction

High-strength aluminum alloy is widely used in aerospace because of its low density, high strength, and good machinability. 7055 is a new type of aluminum alloys, which is obtained by increase in impurity of Zn and Cu and decrease in impurity of Fe and Si on 7050 aluminum alloys. The results show that 7055 has higher strength and fracture toughness than 7050 aluminum alloy. To improve processing efficiency and surface integrity of aluminum alloy, high-speed milling technology is widely applied in aluminum alloy process. Surface integrity is an important indicator to evaluate surface quality of the part, which has a certain influence on wear resistance, fatigue resistance, and corrosion resistance of parts. We must focus on the control of surface integrity in machining of high-strength alloy materials.

Many scholars from various countries conducted positive researches on surface integrity of high-speed milled aluminum alloy. De Lacalle et al.¹ studied the cutting conditions and tool optimization in high-speed milling of aluminum alloys. Asad et al.² investigated the effects of cutting speed and depth of cut on chip morphology and surface finish for down-cut milling case. Sriyotha et al.³ studied geometrical modeling of a ball-end finish milling process for a surface finish. They focused on the modeling method and theory adopted in the simulation system, and the method to improve the calculation accuracy was discussed in detail. Niknam and Songmene⁴ found that the effects of cutting tool, feed per tooth, and depth of cut on slot milling burrs are significant. Yang et al.⁵ reported that the obtained surface roughness <0.4 µm when milling depth, feed per tooth, and milling speed are 0.3 mm, 0.05 mm/z, and 7500 m/min respectively. Bi et al.⁶ investigated the distribution of temperature area in high speed of 7050 aluminum alloy. Rao and Shin⁷ reported that a high cutting speed leads to a high chip flow angle, very low thrust forces, and a high shear angle, while producing a thinner chip in high-speed milling of 7075. Ng et al.⁸ investigated that cutting edge radius has a more substantial effect on the resultant cutting forces than the radial rake angle. With smaller cutting edge radius, the un-deformed chip thickness magnitude at which ploughing will occur is reduced. Muñoz-Escalona and Maropoulos⁹ studied the artificial neural networks for surface roughness prediction when face milling 7075-T7351 aluminum and found the cutting speed is the most important cutting parameter affecting the machined surface integrity from Pearson’s correlation analysis. Sivasakthivel and Sudhakaran¹⁰ reported that the optimal combination of machining parameters for minimum temperature of 0.173 °C was found to be 42°, 2,870 r/min, 0.03 mm/rev, 1.7 mm, and 3.4 mm for helix angle, spindle speed, feed rate, axial, and radial depth of cut, respectively. Liu and Barash¹¹ studied the micro-hardness distribution on surface and subsurface in low cutting speed of specimens using the finite element method. Denkena et al.¹² found that an increase in the feed per tooth, a decrease in the width of cut, or the application of higher radii at the secondary cutting edge lead to more pronounced compressive residual stresses at higher workpiece depths. Tang et al.¹³ reported that thermal load plays a significant role in the superficial residual stresses in high-speed milling aluminum alloy. Raju et al.¹⁴ reported that the feed rate is a dominant parameter and surface roughness increases rapidly with the increase in feed rate and decreases with increase in spindle speed, whereas the effect of depth of cut is not regular. Mc Clung¹⁵ provided a broad and extensive literature survey addressing the stability of surface and near-surface residual stress fields during fatigue, including redistribution and relaxation due to static mechanical load, repeated cyclic loads, thermal exposure, and crack extension. Starke and Staley¹⁶ cover the performance and property requirements for airframe components in current aircraft and describe aluminum alloys and product forms that meet these requirements. They also discuss the structure/property relationships of aluminum aircraft alloys and describe the background and drivers for the development of modern aluminum alloys to improve performance. Suresh Kumar Reddy et al.¹⁷ reported that the presence of the reinforcement enhances the machinability in terms of both surface roughness and lower tendency to clog the cutting tool, when compared to a non-reinforced Al alloy. Ryu et al.¹⁸ reported that surface roughness in the middle area where center of the tool bottom passes is worse than that in the side area by about 7 µm in Rmax and 1.5 µm in Ra under general finishing conditions. Chern¹⁹ found that the machining guideline in face milling is to choose a large in-plane exit angle at about 150° and set the depth of cut at a larger value than the corresponding critical depth of cut, so as to reduce burr size effectively through the formation of secondary burr. Chen et al.²⁰ reported that there exists a critical cutting speed in the high-speed milling of aluminum alloy. The value of this critical peed is different for different cutting conditions. The heat flux flowing into the workpiece increases when the spindle speed increases. When the cutting speed exceeds the critical speed, the increase in heat flux flowing into the workpiece will decrease. Jayakumar et al.²¹ found that increase in volume % of SiC_p reinforcement over the matrix results in higher tool–work interface temperature and needs higher cutting force during machining process. El-Axir²² found that residual stress plays an important role for controlling the behavior of fatigue in ball burnishing of aluminum alloy 6061-T6. Akhavan Farid et al.²³ reported that drilling parameters have significant effects on the surface quality and integrity of the drilled hole during high-speed drilling of Al–Si using a high-speed steel drill. Zhang et al.²⁴ found that both block thickness and quench media had critical influences on residual stresses.

Although a lot of researches in high-speed milling of aluminum alloys have been done, the current research often focuses on 7050 and 7075 to study surface roughness and residual stresses. Moreover, formation of metamorphic layers is not well correlated to important experimental physical phenomena such as dynamic milling force and milling temperature. The objective of this article is to investigate the effects of milling parameters on surface integrity in high-speed milling of 7055. To be able to correlate metamorphic layer with the thermal and mechanical phenomena developed during milling, milling force and milling temperature fields were obtained with finite element method. Finally, the formation of metamorphic layer can be explained by thermo-mechanical coupling effects.

Experimental conditions and procedure

Workpiece material and preparation of samples

Workpiece material used in all experiments is aluminum alloy 7055. Chemical compositions of the alloy are given in Table 1, and mechanical properties of the alloy are shown in Table 2.

Table 1.

Chemical composition of Al7055.

Element	Si	Fe	Cu	Mn	Mg	Cr	Zr	Zn	Ti	Al
wt%	0.024	0.12	2.12	<0.01	1.99	<0.01	0.016	7.70	0.11	Bal.

Table 2.

Mechanical properties of Al7055.

σ _b (MPa)	σ _0.2 (MPa)	δ (%)
589–595	565–570	14–5.2

Experimental scheme

The experiments were conducted on a Mikron HSM 800 with emulsified liquid. Machine spindle is capable of running up to 36,000 r/min with Heidenhain iTNC 530 CNC system. End-milling and down-milling were used. The three-flute uncoated cemented carbide end-milling cutter was used, and its diameter is 12 mm. The dimension of the specimen is 50 mm × 25 mm × 25 mm, as shown in Figure 1. High-speed milling procedure is shown in Figure 2.

Figure 1.

End-milling diagram.

Figure 2.

High-speed milling procedure.

In order to study the effects of end-milling parameters on surface integrity, orthogonal experiments of four factors and three levels were conducted. Every specimen was machined using a new cutter. The experiment parameters and test results are shown in Table 3.

Table 3.

Experimental parameters and test results.

Number	n (r/min)	v_c (m/min)	f_z (mm/z)	a_p (mm)	a_e (mm)	$\bar{R} a$ (µm)	${\bar{σ}}_{x}$ (MPa)	${\bar{σ}}_{y}$ (MPa)	$\bar{H}$ (HV_0.025)
1	18,569	700	0.02	0.3	4	0.384	−55	−124	197.14
2	18,569	700	0.04	0.5	6	0.724	−37	−115	196.18
3	18,569	700	0.06	0.7	8	1.067	−37	−77	191.44
4	23,874	900	0.02	0.5	8	0.425	−118	−107	192.80
5	23,874	900	0.04	0.7	4	0.569	−38	−139	191.13
6	23,874	900	0.06	0.3	6	0.762	−50	−116	185.20
7	29,179	1100	0.02	0.7	6	0.258	−123	−137	193.76
8	29,179	1100	0.04	0.3	8	0.685	−129	−133	191.81
9	29,179	1100	0.06	0.5	4	0.812	−30	−151	189.01

Surface integrity testing

Testing method for surface integrity is very important. Surface integrity testing regions for milled surface are shown in Figure 3. For the sake of statistical significance of the repeatability, multiple measurements were made for the same physical and the average testing values computed are shown in Table 3.

Figure 3.

Surface integrity testing regions for milled surface.

Surface roughness and topography

The three-dimensional (3D) optical surface topography tester Veeco NT1100 was applied to measure surface roughness and surface topography. The magnification was 10 times. The measuring resolution was 736 × 480, and the measuring region size of each sample was 830.22 × 830.22 nm². Measurement precision can reach 0.01 nm. Choosing five points along the milling direction in region A on the machined surface, the surface roughness and surface topography of each sample are shown in Figure 3.

Residual stress

The residual stress on workpiece was tested by Proto LXRD MG2000 residual stress test analysis system. Using aluminum alloy, block calibrates the instrument before measurement; measured residual stress for zero-stress aluminum of 99.5% is close to 0. When CoKα_avg = 1.790 Å, 2θ = 148.9°, and $1 / 2 (S 2) = 18.5606 \times 10^{- 6} MP a^{- 1}$ , measured residual stress for proto stress standard is $- 268 \pm 35 MPa$ . Three equidistant points in region B on the machined surface shown in Figure 3 were selected to test the residual stress. In order to obtain the residual stress distribution along the direction of depth, specimens were stripped using electrochemical method, and the stripping depth was 10 µm. For specimens stripped, the residual stress was tested until close to the body material’s residual stress.

Micro-hardness

Micro-hardness was tested using FEM-8000 semi-automatic digital micro-hardness testing system. Test force was set as 25 g, and the time of keeping load was set as 10 s in the testing process. Measurement precision can reach 0.01 MPa. The selecting three equidistant points, perpendicular to the feed direction in region C on the machined surface shown in Figure 3, were set to test the micro-hardness. The average micro-hardness testing results are shown in Table 3. In order to obtain the micro-hardness distribution in the depth direction, the specimen was mounted in embedded machine, and then coarse grinding, precise grinding, and polishing were done to measure the material micro-hardness. Micro-hardness was measured one time by moving 10 µm under the surface until close to the body material’s hardness.

Microstructure

The metallographic test sample was made through cutting machined sample along the milling direction and is shown as region D in Figure 3. Then, the cutted section was corroded after abrading and polishing. The corrodent was matched as HNO₃:HF:H₂O = 1:1:10. The microstructure of the cutted section was observed with DMI 5000 M.

Experiment results and analysis

Surface integrity control law

Surface roughness and topography

Mathematical model for surface roughness

Surface roughness mathematical model was built up by multiple linear regression analysis based on the data in Table 3

Ra = 230.55 v_{c}^{- 0.54} f_{z}^{0.84} a_{p}^{- 0.08} a_{e}^{0.24}

(1)

The average error and significance of the model are 8.1% and 0.013, respectively. From the model, surface roughness is most sensitive to f_z, secondarily sensitive to v_c and a_e, and least sensitive to a_p. Surface roughness increases with the increase in f_z and a_e and gradually decreases with the increase in v_c and a_p.

Calculation of extremum difference

Extremum difference analysis was used to study the effects of milling parameters on surface roughness. On the basis of the data in Table 3, range analysis table for $\bar{R} a$ , ${\bar{σ}}_{x}$ , ${\bar{σ}}_{y}$ , and $\bar{H}$ is shown in Table 4.

Table 4.

Range analysis table for $\bar{R} a$ , ${\bar{σ}}_{x}$ , ${\bar{σ}}_{y}$ , and $\bar{H}$ .

		v_c	f_z	a_p	a_e
$\bar{R} a$ (µm)	k ₁	0.725	0.354	0.610	0.588
	k ₂	0.585	0.659	0.654	0.580
	k ₃	0.583	0.880	0.630	0.726
	Range	0.142	0.526	0.044	0.146
${\bar{σ}}_{x}$ (MPa)	k ₁	−43.000	−98.667	−78.000	−41.000
	k ₂	−68.667	−68.000	−61.667	−70.000
	k ₃	−94.000	−39.000	−66.000	−94.667
	Range	51.000	59.667	16.333	53.667
${\bar{σ}}_{y}$ (MPa)	k ₁	−105.333	−122.667	−124.333	−138
	k ₂	−120.667	−129	−124.333	−122.667
	k ₃	−140.333	−114.667	−117.667	−105.667
	Range	35.000	14.333	6.666	32.333
$\bar{H}$ (HV0.025)	k ₁	194.920	194.567	191.383	192.427
	k ₂	189.710	193.040	192.663	191.713
	k ₃	191.527	188.550	192.110	192.017
	Range	5.210	6.017	1.280	0.714

In Table 4, for surface roughness, surface residual stress, and surface micro-hardness, k₁, k₂, and k₃ are the average values when the factor takes value at the corresponding level, respectively, and range is the extremum difference of the maximum and the minimum.²⁵

From Table 4, the ranges of surface roughness for v_c, f_z, a_p, and a_e are 0.142, 0.526, 0.044, and 0.146 µm, respectively. So, surface roughness is most sensitive to f_z, secondarily sensitive to a_e and v_c, and least sensitive to a_p, same as the result of the mathematical model (equation (1)).

Effects of milling parameters on surface roughness

The effect of milling parameters on surface roughness is obtained by extremum difference analysis, as shown in Figure 4. The effect of v_c on surface roughness is given in Figure 4(a). When v_c increases from 700 to 1100 m/min, surface roughness gets better and decreases from Ra 0.725 to 0.585 µm. This may be due to the induced softening material by the raise of cutting temperature when v_c increases.

Figure 4.

Effect of milling parameters on surface roughness: (a) effect of v_c on surface roughness, (b) effect of f_z on surface roughness, (c) effect of a_p on surface roughness, and (d) effect of a_e on surface roughness.

The effect of f_z on the surface roughness is given in Figure 4(b). From geometrical factors, reducing feed rate can reduce the height of residual area. Thereby reducing the feed rate can reduce surface roughness. As f_z increases from 0.02 to 0.06 mm/z, surface roughness increases linearly in the range 0.356–0.880 µm.

The effect of a_p on surface roughness is given in Figure 4(c). Milling depth has little effect on surface roughness. As a_p increases from 0.3 to 0.7 mm, surface roughness increases from Ra 0.610 to 0.654 µm. This is due to the milling force fluctuations caused by the change in cutting depth. With the increase in milling force, when a_p increases, the effect of milling force fluctuations on surface roughness also increases.

The effect of a_e on surface roughness is given in Figure 4(d). As a_e increases from 4 to 6 mm, surface roughness decreases slowly from Ra 0.588 to 0.584 µm. When a_e ranges from 6 to 8 mm, surface roughness increases drastically from Ra 0.581 to 0.726 µm.

Interaction effects of milling parameters on surface roughness

For the selection of milling parameters, the interaction effect of milling parameters on surface roughness should also be considered. The effect of milling parameters interaction on surface roughness is shown in Figure 5.

Figure 5.

Interaction effect of milling parameters on surface roughness: (a) interaction effect of v_c and f_z on Ra and (b) interaction effect of f_z and a_e on Ra.

Figure 5(a) shows that the worse surface roughness appears in region A: low v_c and high f_z, and surface roughness is larger than Ra 0.9 µm. The better surface roughness appears in region C: high v_c and low f_z, and surface roughness is less than Ra 0.6 µm. Surface roughness in region B is between regions A and C and is from Ra 0.5 to 0.9 µm.

Figure 5(b) shows that worse surface roughness appears in region D: high a_e and high f_z, and surface roughness is larger than Ra 0.8 µm. The better surface roughness appears in region F: low a_e and low f_z, and surface roughness is less than Ra 0.5 µm. Region E was the transition region of regions F and D, and surface roughness ranges from Ra 0.5 to 0.8 µm.

Effect of milling parameters on surface topography

The machined surface topography is a comprehensive action of extrusion and tearing, elastic deformation and plastic deformation, and thermal–mechanical coupling. Figure 6 shows the typical 3D surface topography in high-speed milling of 7055 aluminum alloy. The peaks have more opportunity to contact with the cutter edge, and chip formation can be obtained. The valleys are driven up by the slip deformation due to ploughing action. The final surface profile after continuous cutting is determined by the cutting and ploughing actions. The machined surface topography has the regularity, which consists of high and low regions generated by cutter edge.

Figure 6.

3D surface topography of milled 7055 alloy.

From surface topography of specimens 1–9 shown in Figure 7, surface topography can be affected by different proportions of v_c and f_z. In Figure 7(a), (d), and (g), with the increase in v_c, better surface can be obtained. For f_z = 0.02 mm/z, the distance between two corresponding peaks is equal no matter what v_c is. In Figure 7(g), (h), and (i), narrow groove and firm texture are obtained when f_z = 0.02 mm/z. However, wide groove and sparse texture can be obtained when f_z = 0.04 or 0.06 mm/z. With the increase in f_z, the peak-to-valley height in the surface topography gets higher, and the distance between two corresponding peaks gets larger.

Figure 7.

Measured 3D topographies in different milling parameters: (a) specimen 1, Ra 0.384 µm; (b) specimen 2, Ra 0. 724 µm; (c) specimen 3, Ra 1.067 µm; (d) specimen 4, Ra 0.425 µm; (e) specimen 5, Ra 0.569 µm; (f) specimen 6, Ra 0.762 µm; (g) specimen 7, Ra 0.258 µm; (h) specimen 8, Ra 0.685 µm; and (i) specimen 9, Ra 0.812 µm.

In Figure 7(a), (d), and (g), f_z = 0.02 mm/z, and surface roughness is below Ra 0.5 µm. In Figure 7(b), (e), and (h), f_z = 0.04 mm/z, and surface roughness is above Ra 0.5 µm. In Figure 7(c), (f), and (i), f_z = 0.06 mm/z, and surface roughness is above Ra 0.7 µm. It can be seen that f_z has greater effect on surface topography than v_c in the range of selected process parameters.

Surface residual stress

Mathematical model for surface residual stress

Mathematical model of residual stress is built using multiple linear regression analysis based on the data in Table 3

{\begin{matrix} σ_{x} = 10^{- 4.31} v_{c}^{1.36} f_{z}^{- 0.80} a_{p}^{- 0.31} a_{e}^{1.06} \\ σ_{y} = 1.85 v_{c}^{0.67} f_{z}^{- 0.07} a_{p}^{- 0.10} a_{e}^{- 0.41} \end{matrix}

(2)

where σ_x means residual stress along feed direction and σ_y means the residual stress along the step-over direction. The average error and significance for the model of σ_x are 8.9% and 0.002, respectively, while the average error and significance for the model of σ_y are 4.8% and 0.035, respectively.

From formula (2), σ_x is most sensitive to v_c, secondarily sensitive to a_e and f_z, and least sensitive to a_p. The σ_x increases with the increase in v_c and a_e and decreases gradually with the increase in f_z and a_p. σ_y is most sensitive to v_c, secondarily sensitive to a_e and a_p, and least sensitive to f_z. σ_y increases with the increase in v_c and decreases gradually with the increase in f_z and a_p.

Calculation of extremum difference

From Table 4, the ranges of σ_x for v_c, f_z, a_p, and a_e are 51, 59.667, 16.333, and 53.667 MPa, respectively. So, σ_x was most sensitive to f_z, secondarily sensitive to a_e and v_c, and least sensitive to a_p. The ranges of σ_y for v_c, f_z, a_p, and a_e are 35, 14.333, 6.666, and 32.333 MPa, respectively. So, σ_y is most sensitive to v_c, secondarily sensitive to a_e and f_z, and least sensitive to a_p, same as the result of the mathematical model (equation (2)).

Effects of milling parameters on residual stress

The effects of v_c, f_z, a_p, and a_e on surface residual stress are shown in Figure 8 obtained by extremum difference analysis. Compressive residual stresses are observed on all machined surfaces. From Figure 8(a), as v_c increases from 700 to 900 m/min, σ_x increases from −42 to −64 MPa, and σ_y increases from −105 to −121 MPa. When v_c increases from 900 to 1100 m/min, σ_x increases from −69 to −94 MPa, and σ_y increases from −121 to −140 MPa. From Figure 8(b), as f_z increases from 0.02 to 0.04 mm/z, σ_x decreases from −99 to −68 MPa, and σ_y increases from −123 to −129 MPa. When f_z increases from 0.04 to 0.06 mm/z, σ_x decreases from −68 to −39 MPa, and σ_y decreases from −129 to −115 MPa. From Figure 8(c), as a_p increases from 0.3 to 0.5 mm, σ_x decreases from −78 to −62 MPa, and σ_y is −124 MPa. When a_p increases from 0.5 to 0.7 mm, σ_x increases from −62 to −66 MPa, and σ_y decreases from −124 to −118 MPa. From Figure 8(d), as a_e increases from 4 to 6 mm, σ_x increases from −41 to −70 MPa, and σ_y decreases from −138 to −123 MPa; as a_p increases from 6 to 8 mm, σ_x increases from −70 to −95 MPa, and σ_y decreases from −113 to −106 MPa.

Figure 8.

Effects of milling parameters on surface residual stress: (a) effect of v_c on residual stress, (b) effect of f_z on residual stress, (c) effect of a_p on residual stress, and (d) effect of a_e on residual stress.

Interaction effects of milling parameters on surface residual stress

The interaction effect of milling parameters on surface residual stress should also be considered for selecting milling parameters. The effect of a_e and v_c interaction on residual stress is shown in Figure 9.

Figure 9.

(a) Interaction effect of v_c and a_e on σ_x and (b) interaction effect of v_c and a_e on σ_y.

Figure 9(a) shows that the higher σ_x appears in region G: high v_c and high a_e, and σ_x is higher than −80 MPa. The lower σ_x appears in region H: low v_c and low a_e, and σ_x is less than −40 MPa. σ_x in region I ranges from −40 to −80 MPa.

Figure 9(b) shows that the higher σ_y appears in region J: high v_c and low a_e, and σ_y is about −140 MPa. The lower σ_y appears in region K: low v_c and high a_e, and σ_y is about −100 MPa. The σ_y in region L ranges from −100 to −140 MPa.

Surface micro-hardness

Mathematical model for surface micro-hardness

Mathematical model of micro-hardness is built using multiple linear regression analysis based on the data in Table 3

H = 235.431 v_{c}^{- 0.042} f_{z}^{- 0.027} a_{p}^{0.006} a_{e}^{- 0.003}

(3)

The average error and significance of the model are 0.8% and 0.254, respectively. From formula (3), surface micro-hardness is most sensitive to v_c, secondarily sensitive to f_z and a_p, and least sensitive to a_e. Surface micro-hardness increases with the increase in a_p and decreases gradually with the increase in v_c, f_z, and a_e.

Calculation of extremum difference

From Table 4, the ranges of micro-hardness for v_c, f_z, a_p, and a_e are 5.210, 6.017, 1.280, and 0.714 HV_0.025, respectively. So, micro-hardness is most sensitive to f_z, secondarily sensitive to v_c and a_p, and least sensitive to a_e, same as the result of the mathematical model (equation (3)).

Effects of milling parameters on micro-hardness

In Table 3, micro-hardness has a small variation range of 185.20–197.14 HV_0.025. The effects of milling parameters on micro-hardness are investigated using extremum difference analysis, as shown in Figure 10. Milling parameters have little impact on micro-hardness in high-speed milling of aluminum alloy 7055. So, the interaction effects of milling parameters on micro-hardness were no further studied.

Figure 10.

Effects of milling parameters on surface micro-hardness: (a) effect of v_c on H, (b) effect of f_z on H, (c) effect of a_p on H, and (d) effect of a_e on H.

According to the above analysis, good surface integrity can be obtained with v_c = 1100 m/min, f_z = 0.02 mm/z, a_p = 0.7 mm, and a_e = 6 mm in milling of 7055 alloy, while $\bar{R} a$ , ${\bar{σ}}_{x}$ , ${\bar{σ}}_{y}$ , and $\bar{H}$ are Ra 0.258 µm, −123 MPa, −137 MPa, and 193.76 HV_0.025, respectively.

Metamorphic layer analysis

Measurement and simulation for milling force and temperature in milling of 7055

Acquisition of force and temperature in high-speed machining is still a difficult problem. Milling speed in the study is about 1000 m/min. Response frequency for acquisition system of force and temperature cannot meet the requirement. Milling experiments and simulation of 7055 alloy in low-speed milling were carried out.

Measurement for milling force and temperature

Yao et al.²⁶ measured the milling temperature using a semi-artificial thermocouple composed by TB6 and constantan and reported the effect of thermal–mechanical coupling on residual stress in milling of TB6. A semi-artificial thermocouple composed by 7055 alloy and constantan (Φ 0.3 mm) was used to measure milling temperature in this article. The fabricating procedure of a 7055-constantan thermocouple, as shown in Figure 11(a), can be briefly described as follows: machine two pieces of 7055 specimen, carve a groove with both the width and depth close to 0.3 mm (the diameter of constantan wire) on one surface of one specimen, squeeze the constantan wire with insulation paint layer about 0.01 mm into the groove, coat a layer of glue on one surface for another specimen, bind two specimens together to make the constantan wire be clamped by two workpieces, stay this sample being clamped by vise moderately for 8–12 h in room temperature, get off the sample from vise, and check the insulativity of constantan wire and un-carved 7055 workpiece. This 7055-constantan thermocouple is fixed on a CNC machine worktable with vise to measure the cutting temperature.

Figure 11.

Measurement of milling force and temperature: (a) machining process, (b) measurement for milling force, and (c) measurement for temperature.

The cutting experiments were carried out in YHVT850Z. The cutting tool is a three-flute uncoated cemented carbide end mill. Rake angle, relief angle, helix angle, and diameter of this tool are 14°, 10°, 40°, and 12 mm, respectively. Milling parameters are given in Table 4. The measurement of milling force and temperature is shown in Figure 11.

The measurement system of cutting force consists of a Kistler 9255 B dynamic piezoelectric dynamometer, a Kistler 5017 A charge amplifier, and a recorder. The mean force by averaging 20 peak values of continuous transient cutting force was used as the experiment result of cutting force. The signal obtained from the measurement system of milling force is shown in Figure 12. In Figure 12(a), F_x and F_y are 70 and 32 N, respectively, and $F_{toa} = \sqrt{{F_{x}}^{2} + {F_{y}}^{2}} = 77 N$ . In Figure 12(b), F_x and F_y are 100 and 67 N, respectively, and $F_{toa} = \sqrt{{F_{x}}^{2} + {F_{y}}^{2}} = 120 N$ . F_toa is shown in Table 5.

Figure 12.

Signal obtained from measurement system of milling force: (a) v_c = 170 m/min, f_z = 0.02 mm/z, a_p = 0.5 mm, and a_e = 12 mm and (b) v_c = 110 m/min, f_z = 0.06 mm/z, a_p = 0.5 mm, and a_e = 12 mm.

Table 5.

Experiment and simulation results for milling force and temperature.

Number	v_c (m/min)	f_z (mm/z)	a_e (mm)	a_p (mm)	F_toa (N)			T_highest (°C)
					Experimental	Simulation	Error (%)	Experimental	Simulation	Error (%)
10	170	0.02	12	0.5	77	66	14.29	220	260	18.18
11	110	0.06			120	97	19.17	230	260	13.04

The measurement system of cutting temperature was constructed by a semi-artificial 7055-constantan thermocouple, an A11S11 signal disposal module, a UA305 high-speed USB data collector, and a computer. The signal obtained from the measurement system of milling temperature is shown in Figure 13. Collected milling temperatures are shown in Table 5.

Figure 13.

Signal obtained from measurement system of milling temperature: (a) v_c = 170 m/min, f_z = 0.02 mm/z, a_p = 0.5 mm, and a_e = 12 mm and (b) v_c = 110 m/min, f_z = 0.06 mm/z, a_p = 0.5 mm, and a_e = 12 mm.

Calibration curve between cutting temperatures and thermoelectric potentials of 7055-constantan thermocouple is shown in Figure 14 to predict cutting temperature by measuring thermoelectric potential.

Figure 14.

Calibration curve of 7055-constantan thermocouple.

Simulation for milling force and temperature

Third Wave Systems provides AdvantEdge FEM software for metal cutting simulation through a combination of finite element analyses and validated material modeling. Standard material database for AdvantEdge FEM includes 7055 alloy and was used to simulate milling force and temperature. Established temperature field simulation model is shown in Figure 15. Finite element model of two-dimensional milling is shown in Figure 16. Down-milling and no cutting fluid were used. Rake angle, relief angle, cutting edge radius, and diameter of the mill are 14°, 10°, 0.15 mm, and 24 mm, respectively. Initial temperature is 20 °C in milling processing.

Figure 15.

Simulation model.

Figure 16.

Finite element model of two-dimensional milling.

The milling force and temperature field simulation in different milling parameters are shown in Figures 17 and 18. When v_c = 170 m/min, f_z = 0.02 mm/z, a_e = 12 mm, and a_p = 0.5 mm, the maximum cutting forces of F_x and F_y are 28 and 60 N, respectively, and $F_{toa} = \sqrt{{F_{x}}^{2} + {F_{y}}^{2}} = 66 N$ ; the highest temperature T_highest for cutting region is 260 °C. When v_c = 110 m/min, f_z = 0.06 mm/z, a_e = 12 mm, and a_p = 0.5 mm, the maximum cutting forces of F_x and F_y are 55 and 80 N, respectively, and $F_{toa} = \sqrt{{F_{x}}^{2} + {F_{y}}^{2}} = 97 N$ ; the highest temperature T_highest for cutting region is also 260 °C.

Figure 17.

Milling force simulation in different milling parameters: (a) milling force simulation for specimen 10 and (b) milling force simulation for specimen 11.

Figure 18.

Milling temperature field simulation in different milling parameters: (a) milling temperature simulation for specimen 10 and (b) milling temperature simulation for specimen 11.

The F_toa and T_highest on workpiece were extracted from the simulation results, as shown in Table 5. Experiment results for milling force and temperature are also shown in Table 5. As can be seen from the table, the error between experiment and simulation results is small. So, the simulation results are credible.

Simulation of milling force and temperature in high-speed milling of 7055

In order to obtain the effect of thermal–mechanical coupling effect on surface metamorphic layer, three levels of milling parameters shown in Table 6 are designed to conduct milling experiment for 7055. The specific processing parameters are shown in Table 6. Milling force and temperature fields in three levels were carried out by AdvantEdge FEM software and shown in Figures 19 and 20.

Table 6.

Simulation parameters and results for three levels.

Number	v_c (m/min)	f_z (mm/z)	a_e (mm)	a_p (mm)	F_toa (N)	T_highest (°C)
12 (level 1)	500	0.02	6	0.5	16	220
13 (level 2)	900	0.06			36	260
14 (level 3)	1300	0.1			47	320

Figure 19.

Milling force simulation for (a) specimen 12, (b) specimen 13, and (c) specimen 14.

Figure 20.

Milling temperature field simulation for (a) specimen 12, (b) specimen 13, and (c) specimen 14.

From Figures 19 and 20, for specimen 12, namely, level 1, the maximum cutting forces of F_x and F_y are 11.5 and 10.5 N, respectively, and $F_{toa} = \sqrt{{F_{x}}^{2} + {F_{y}}^{2}} = 16 N$ ; the highest temperature T_highest is 220 °C. For level 2, the maximum cutting forces of F_x and F_y are 32 and 16 N, respectively, and $F_{toa} = \sqrt{{F_{x}}^{2} + {F_{y}}^{2}} = 36 N$ ; the highest temperature T_highest is 260 °C. For level 3, the maximum cutting forces of F_x and F_y are 42 and 20 N, respectively, and $F_{toa} = \sqrt{{F_{x}}^{2} + {F_{y}}^{2}} = 47 N$ ; the highest temperature T_highest is 320 °C. From levels 1 to 3, the depth of heat-affected layer h_a is 20, 25, and 30 µm, respectively. F_toa and T_highest of three levels obtained from simulation results for milling force and temperature are shown in Table 6.

From levels 1 to 3, the region of temperature field for rake face became larger and larger. Temperature distributions for rake and relief faces for three levels are shown in Figure 21. The highest temperature and temperature distribution area of the tool all increase gradually with the increase in process strength. Among the three levels, the highest temperature occurs at a point along the rake face and close to the tool tip. This is because the chip flows along the rake face, and the cutting heat is concentrated in the contact area of tool rake face and chip. For specimens 12–14, distances between the highest temperature point and tool tip are 20, 50, and 50 µm, respectively.

Figure 21.

Temperature distribution of rake and relief faces for three levels.

Distribution of residual stress

Residual stress on subsurface for specimens 12–14 are all tested and shown in Figure 22. From it, all machined surfaces perform compressive residual stress, and residual stress tends to 0 gradually with the increase in h. Figure 22(a) shows that σ_x and σ_y on machined surface are −118 and −108 MPa, respectively, and the depth of compressive residual stress layer is about 35 µm; Figure 22(b) shows that σ_x and σ_y on machined surface are −59 and −87 MPa, respectively, and the depth of compressive residual stress layer is about 45 µm; Figure 22(c) shows that σ_x and σ_y on machined surface are −9 and −128 MPa, respectively, and the depth of compressive residual stress layer is about 45 µm.

Figure 22.

Distribution of residual stress on subsurface for three levels: (a) specimen 12, (b) specimen 13, and (c) specimen 14.

From specimens 12–14, milling force increased from 16 to 47 N, and milling temperature increased from 220 °C to 320 °C. In the first deformation zone, severe plastic deformation and shear effect induce large tensile stress. In the third deformation zone, severe friction and squeeze between flank of milling cutter and workpiece induce tensile plastic deformation. Small elastic modulus for aluminum alloy induces larger rebound on machined surface and leads to strong surface burnishing effect. Compared with the plastic bulge deformation effect by milling force and heat, surface burnishing effect by milling force is more significant. Both effects result in compressive residual stresses on machined surface.

Distribution of micro-hardness

Micro-hardness on subsurface for specimens 12–14 are all tested and shown in Figure 23. Micro-hardness for three levels changes slightly with increase in h. From specimens 12–14, milling force increases from 16 to 47 N, and milling temperature increases from 220 °C to 320 °C. The hardening effect increases with increase in force. The hardening effect is the combined result of cutting force enhancement and cutting heat weakening effect. The highest temperature of 320 °C does not exceed the dynamic recrystallization temperature and phase transition temperature.

Figure 23.

Distribution of micro-hardness in subsurface for three levels.

Microstructure

Microstructures of specimens 12–14 are shown in Figure 24. As can be seen, with increase in milling force and temperature, deformation degree of crystal grain increases, and the depth of deformation layer increases. Because most heat was taken away by chip, phase transition did not occur on three specimens.

Figure 24.

Morphology of microstructure for three levels: (a) specimen 12, (b) specimen 13, and (c) specimen 14.

From Figure 24(a), plastic deformation of specimen 12 is very small along feed direction, and the depth of deformation layer is less than 5 µm. This is mainly because of the fact that strain hardening on subsurface is not obvious when milling force and temperature are 16 N and 220 °C, respectively. From Figure 24(b), plastic deformation of specimen 13 along feed direction is larger than that of specimen 12, and the depth of plastic deformation layer is about 15 µm. This is mainly because strain hardening on subsurface increases when milling force and temperature are 36 N and 260 °C, respectively. From Figure 24(c), plastic deformation of specimen 14 along feed direction is larger than that of specimen 13. Surface grain fibrosis leads to a large degree of deformation, and the depth of plastic deformation layer is about 20 µm. This is mainly because strain hardening caused by thermal–mechanical coupling effect is significant when milling force and temperature are 47 N and 320 °C, respectively.

Conclusion

The major results obtained in high-speed milling of 7055 aluminum alloy are as follows:

Surface roughness is most sensitive to the variation of f_z, secondarily sensitive to v_c, and least sensitive to a_p. Surface roughness increases with the increase in f_z and a_e, decreases with the increase in v_c, and initially increases and then decreases with the increase in a_p. The combined proportion of v_c and f_z affects surface topography.

The X direction residual stress σ_x is most sensitive to v_c, secondarily sensitive to a_e and f_z, and least sensitive to a_p. The σ_x increases with the increase in v_c and a_e, decreases with the increase in f_z, and initially decreases and then increases with the increase in a_p. The Y direction residual stress σ_y is most sensitive to v_c, secondarily sensitive to a_e and a_p, and least sensitive to f_z. The σ_y increases with the increase in v_c, decreases with the increase in a_p and a_e, and initially increases and then decreases with the increase in f_z. All machined surfaces perform compressive residual stress and change from −151 to −30 MPa.

Surface micro-hardness is most sensitive to v_c, secondarily sensitive to f_z and a_p, and least sensitive to a_e. Milling parameters have little impact on micro-hardness in high-speed milling of 7055 alloy, and micro-hardness changes from 185.2 to 197.14 HV_0.025.

In high-speed milling of 7055 alloy, with increase in milling parameters in this research, milling force increases from 16 to 47 N, and milling temperature increases from 220 °C to 320 °C. The depth of compressive residual stress layer increases from 35 to 45 µm, and the depth of plastic deformation layer increases from 5 to 20 µm. Thus, the strong thermal–mechanical coupling effect induced large plastic deformation layer and large residual stress layer in metamorphic layer.

For high-milling 7055 aluminum alloy, when v_c = 1100 m/min, f_z = 0.02 mm/z, a_p = 0.7 mm, and a_e = 6 mm, good surface integrity can be obtained, and the surface roughness, surface residual stresses, and surface micro-hardness are Ra 0.258 µm, −123 MPa, −137 MPa, and 193.76 HV_0.025, respectively.

Footnotes

Declaration of conflicting interests

The authors declare that there is no conflict of interest.

Funding

This study was supported by the National Natural Science Foundation of China (grant no. 51005184; grant no. 51375393), Aeronautical Science Foundation of China (grant no. 2013ZE53060), and graduate starting seed fund of Northwestern Polytechnical University (grant no. Z2013048).

References

De Lacalle

LNL

Lamikiz

Sánchez

. Cutting conditions and tool optimization in the high-speed milling of aluminium alloys. Proc IMechE, Part B: J Engineering Manufacture 2001; 215(9): 1257–1269.

Asad

Mabrouki

Memon

. Three-dimensional finite element modeling of rough to finish down-cut milling of an aluminum alloy. Proc IMechE, Part B: J Engineering Manufacture 2013; 227(1): 75–83.

Sriyotha

Sahasrabudhe

Yamazaki

. Geometrical modelling of a ball-end finish milling process for a surface finish. Proc IMechE, Part B: J Engineering Manufacture 2006; 220(4): 467–477.

Niknam

Songmene

. Factors governing burr formation during high-speed slot milling of wrought aluminum alloys. Proc IMechE, Part B: J Engineering Manufacture 2013; 227(8): 1165–1179.

Yang

Guo

. Experimental research on surface roughness of 7050 alloy under high speed milling. Mach Build & Auto 2011; 3: 34–35.

Fang

Dong

. Research on 3D numerical simulation and experiment of cutting temperature for high speed milling of aerospace aluminum alloy. J Mech Eng 2010; 46(7): 160–165.

Rao

Shin

. Analysis on high-speed face-milling of 7075-T6 aluminum using carbide and diamond cutters. Int J Mach Tool Manu 2001; 41(12): 1763–1781.

Szablewski

Dumitrescu

. High speed face milling of a aluminium silicon alloy casting. CIRP Ann Manuf Techn 2004; 53(1): 69–72.

Muñoz-Escalona

Maropoulos

. Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351. J Mater Eng Perform 2010; 19(2): 185–193.

10.

Sivasakthivel

Sudhakaran

. Optimization of machining parameters on temperature rise in end milling of Al 6063 using response surface methodology and genetic algorithm. Int J Adv Manuf Tech 2013; 67(9–12): 2313–2323.

11.

Liu

Barash

. The mechanical state of the sublayer of a surface generated by chip-removal process. J Manuf Sci Eng 1976; 98(4): 1192–1199 and 1202–1208.

12.

Denkena

Boehnke

De Leon

. Machining induced residual stress in structural aluminum parts. Prod Engineer 2008; 2(3): 247–253.

13.

Tang

Liu

Wan

. Study on residual stresses in milling aluminium alloy 7050-T7451. Adv Des Manuf Gain Compet Edge: New Manuf Tech Role Improv Enterp Perform 2008; 169–178.

14.

Raju

KVMK

Janardhana

Kumar

. Optimization of cutting conditions for surface roughness in CNC end milling. Int J Precis Eng Man 2011; 12(3): 383–391.

15.

Mc Clung

. A literature survey on the stability and significance of residual stresses during fatigue. Fatigue Fract Eng M 2007; 30(3): 173–205.

16.

Starke

Staley

. Application of modern aluminum alloys to aircraft. Prog Aerosp Sci 1996; 32(2–3): 131–172.

17.

Suresh Kumar Reddy

Kwang-Sup

Yang

. Experimental study of surface integrity during end milling of Al/SiC particulate metal–matrix composites. J Mater Process Tech 2008; 201(1–3): 574–579.

18.

Ryu

Choi

Chu

. Roughness and texture generation on end milled surfaces. Int J Mach Tool Manu 2006; 46(3–4): 404–412.

19.

Chern

. Experimental observation and analysis of burr formation mechanisms in face milling of aluminum alloys. Int J Mach Tool Manu 2006; 46(12–13): 1517–1525.

20.

Chen

Sun

Wang

. Experimental research on the dynamic characteristics of the cutting temperature in the process of high-speed milling. J Mater Process Tech 2003; 138(1–3): 468–471.

21.

Jayakumar

Mathew

Joseph

. An investigation of cutting force and tool–work interface temperature in milling of Al–SiC_p metal matrix composite. Proc IMechE, Part B: J Engineering Manufacture 2013; 227(3): 362–374.

22.

El-Axir

. An investigation into the ball burnishing of aluminium alloy 6061-T6. Proc IMechE, Part B: J Engineering Manufacture 2007; 221(12): 1733–1742.

23.

Akhavan Farid

Sharif

Idris

. Surface integrity study of high-speed drilling of Al–Si alloy using HSS drill. Proc IMechE, Part B: J Engineering Manufacture 2011; 225(7): 1001–1007.

24.

Zhang

Feng

Xiao

. FEM simulation and experimental study on the quenching residual stress of aluminum alloy 2024. Proc IMechE, Part B: J Engineering Manufacture 2013; 227(7): 954–964.

25.

Liu

Huang

Tian

. Experimental design and data processing. Beijing, China: Chemical Industry Press, 2010, pp.62–70.

26.

Yao

Tan

. Effects of cutting parameters on surface residual stress and its mechanism in high-speed milling of TB6. Proc IMechE, Part B: J Engineering Manufacture 2013; 227(4): 483–493.