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Abstract

Mechanical and microstructural properties of titanium alloys change with β-phase fraction. This in turn influences the dominant tool wear mechanisms in their machining. This work therefore involves turning experimentation on three titanium alloys with varying β-phase fraction, namely, α, α+β and β-rich alloys using coated carbide tools, to identify dominant wear mechanisms, which hitherto have not been adequately investigated. The dominant wear mechanisms were investigated using scanning electron microscopy and energy-dispersive X-ray analysis of worn tool surfaces and were also correlated with the cutting forces during machining. Abrasion, abrasion with built-up edge and plastic deformation of cutting edge appeared to be the dominant tool wear mechanisms in α, α+β and β-rich alloy, respectively. At the same time, diffusion of Sn, V and Mo from α, α+β and β-rich alloys to tool face, respectively, was observed. The chip–tool contact length predicted using the analytical models from the literature matched closely with the experimental values.

Keywords

Tool wear chip–tool contact length wear mechanism diffusion coating delamination titanium

Introduction

Titanium alloys have a two-phase (α-hexagonal close-packed (HCP) and β-body-centered cubic (BCC) microstructure at room temperature. A change in β-phase fraction in titanium alloy can lead to significant changes in the mechanical properties and microstructure of titanium alloys. The change in β-phase fraction also changes the shear band forming tendency and the corresponding segmentation frequency during machining of these alloys. Consequently, the mechanism of tool wear would differ with a change in β-phase fraction in titanium alloy. It is envisaged that an investigation into the identification of dominant tool wear mechanism would help design appropriate cutting tools and lubrication systems for machining of the titanium alloys.

In titanium alloys, the percentage of α and β phases at room temperature can be changed with the help of different alloying elements. Higher contents of α stabilizer alloying element, namely, Al, Sn, O and so on, increase the proportion of α phase at room temperature. Similarly, a higher proportion of β stabilizer element, namely, V, W and Mo, increases the proportion of β phase in titanium alloys at room temperature. Figure 1 illustrates three different titanium alloys and their approximate place on β isomorphous phase diagram obtained by changing the alloying elements. It may be noted that the β phase is more ductile and has more number of slip systems available than α phase. Therefore, titanium alloys with higher proportion of β phase are easier to process thermo-mechanically than those containing higher proportion of α phase. Consequently, they affect the tool wear during machining. This study focuses on the influence of β phase fraction on the mechanism of tool wear.

Figure 1.

β Isomorphous phase diagram showing approximate position of analyzed titanium alloys.

Numerous researchers have worked on machining of titanium alloys to identify wear mechanisms while machining with different tool materials. While machining titanium alloys with high-speed steel (HSS) and cemented carbide tools, excessive cratering and deformation at the nose were identified as predominant tool wear mechanisms. However, with a composite tool containing wurtzite boron nitride-cubic boron nitride composite (wBN-cBN), which has high fracture toughness and hardness, tool wear was found to be due to diffusion–dissolution.¹ Maximum flank face wear and excessive chipping at the cutting edge were identified as major tool wear mechanisms in machining of Ti-6246 with cemented carbide tools. Also, it was observed that the cemented carbide inserts with finer grain size and honed cutting edge show longer tool life than coarse-grain carbides in machining of titanium alloys.² Face milling of Ti6Al4V shows chipping on rake face as a dominant tool wear mechanism. Furthermore, it was evident that chemical vapor deposition (CVD)–coated tungsten carbide inserts outperformed physical vapor deposition (PVD)–coated inserts due to their strong adhesion property.³ If the machining temperature reaches above 700 °C, an excessive diffusion wear in machining $α + β$ stabilized titanium alloy was evident with polycrystalline cubic boron nitride (PCBN) tools.⁴ Cemented carbide tools have a longer tool life than the cubic boron nitride (CBN) tools when high-pressure coolant was used.⁵ Slot milling with BCBN tools shows adhesion of work material and attrition as a significant tool wear mechanism.⁶ Diffusion and superficial plastic deformation were identified as tool wear mechanisms on uncoated carbides in machining of titanium alloys. In the case of polycrystalline diamond (PCD) inserts, diffusion, attrition and notching were identified as dominant tool wear mechanisms in machining of titanium alloys.⁷ Milling of Ti6Al4V with H13A carbide insert was carried out and a wear map was developed, which shows a low, moderate and high tool wear region for a particular combination of cutting speed and feed rate.⁸

A summary of tool wear mechanisms that prevail in machining of various titanium alloys is presented in Table 1. It is observed that several tool wear mechanisms^9,10 play a role in the degradation of cutting tools while machining titanium alloys.

Table 1.

Tool wear mechanisms in machining of titanium alloys.

Tool wear	Abrasion	Adhesion	Diffusion	Chipping and fracture	Coating delamination
Reasons	Presence of hard particles in work	Seizure of chip with the rake face due to high temperature and pressure	Higher cutting speed causes increase in temperature at the rake face and gives rise to smooth dissolution–diffusion wear	Existence of high temperature and stress at the cutting edge coupled with brittleness of material causes chipping	Work–tool interface temperature activates chemical reaction of coating with substrate
	Irregular material flow past the cutting edge at low cutting speed	Thermal softening at high temperature increases this wear	Diffusion of cobalt and tungsten atoms on the chip shows this kind of wear	Poor chip-groove utilization and a very sharp cutting edge	Crack at interface of coating and substrate causes this kind of wear
	Built-up edge formation at the cutting edge	It is dominated on the rake face
	It is dominated at the flank face and nose	It is dominated on the rake face
Typical photographs
Ti alloy	Ti6Al2Sn4Zr6Mo	Ti6Al4V	Ti6Al4V	Ti6Al4V	Ti6Al4V
Machining parameters	Turning operation, surface speed of 60–100 m/min, feed rate of 0.25 and 0.35 mm/rev, depth of cut of 2 mm, dry machining	Face milling, cutting speed of 55–100 m/min, feed of 0.1–0.15 mm/tooth, axial and radial depth of cut of 2 and 58 mm, respectively. Coolant: Hocut-808 (6%–7% concentration)	End milling, cutting speed of 40–120 m/min for carbide insert	Turning operation, cutting speed of 150–250 m/min, depth of cut of 0.5 mm, feed rate of 0.15 mm/rev. Conventional coolant flow	Face milling, cutting speed of 55–100 m/min, feed of 0.1–0.15 mm/tooth, axial and radial depth of cut of 2 and 58 mm, respectively. Coolant: Hocut 808 (6%–7% concentration)
Machining parameters			End milling, cutting speed of 120–250 m/min for PCD insert, axial depth of cut of 1 mm and feed of 0.1 mm/ tooth. Full immersion cutting
Tool material	Carbide insert CNMG 120408-890, CNMG 120408-883	Coated carbide tool with coating of PVD + TiN and CVD + TiCN/Al₂O₃	Uncoated carbide inserts R245-12-T3K-MM2030, PCD inserts R245-12-T3E-CD10	CBN and uncoated carbide tool	Coated carbide tool with coating of PVD + TiN and CVD + TiCN/Al₂O₃
Reference	Jawaid et al.³	Zoya and Krishnamurthy⁴	Ezugwu et al.⁵	Bhaumik et al.¹	Zoya and Krishnamurthy⁴

PCD: poly crystalline diamond; PVD: physical vapor deposition; CBN: cubic boron nitride; CVD: chemical vapor deposition.

It is apparent from the literature reviewed that the tool wear mechanisms change with cutting tool materials and machining processes. Very few studies have concentrated on the influence of work material properties on the tool wear mechanism. Titanium alloys with a change in β-phase fraction differ widely in microstructure and mechanical properties. Therefore, the tool is subjected to a variation in the magnitude of cutting forces. Also, microstructure of titanium alloy changes from coarse-grain equiaxed to fine-grain lamellar. Therefore, identifying a dominant tool wear mechanism in each of the titanium alloys will enable appropriate selection of tool materials, coolants and lubrication methods and tool geometry, thereby helping in minimizing the tool wear rate.

Therefore, machining experiments were carried out on three types of titanium alloys. To analyze the mechanism of tool wear, scanning electron microscopy (SEM) and an energy-dispersive X-ray analysis (EDAX) were performed on the worn-out face and flank surfaces of the worn cutting tools.

Theme of experiment

Figure 2(a) shows the theme of this work. The mechanical properties of titanium alloys differ significantly with their composition and so are their interactions with cutting tools during machining. Therefore, in this work, three titanium alloys, that is, α, $α + β$ and β-rich $α + β$ alloys with an increase in β-phase fraction, have been used. These alloys differ widely in mechanical properties and microstructure. The main objective of this work has been to identify a variation in the mechanism of tool wear during machining as the β-phase fraction of titanium alloy changes.

Figure 2.

Plan of experiment: (a) theme of the experiment and (b) experimental setup.

Experimental specifications

Experimental specifications including details on alloy compositions, their hardness, machines and tools, processing parameters and response variables used in this work are presented in Table 2. In order to get insight into the mechanical properties of the three titanium alloys, hardness of the alloys was measured with a nano indenter. An average of the measured hardness values is given in Table 2. From Table 2, it is observed that the hardness of β-rich alloy was the highest and that of α alloy was the lowest.

Table 2.

Experimental specifications.

Tool–work combination		α alloy Ti5.26Al3.03Sn (pipe ϕ 100 mm, 1 mm thick)
		$α + β alloy Ti 6 Al 4 V (p ipe ϕ 93 mm, 1 mm thick)$
		$β - rich and α + β alloy Ti 4.16 Al 3.26 V 3.89 Mo$ (pipe ϕ 193 mm, 1 mm thick)
Alloy type		α alloy	$α + β$ alloy	$β - rich α + β alloy$
Hardness (GPa)		3.56	5.44	5.52
Machine		EMCO CNC lathe
Cutting tool holder		Tool holder PTGNR 16 × 16
Carbide insert CNMG 120404-M5-TP-3500 PVD TiAlN coated
C	N	M	G	TP-3500
80° diamond	0° relief angle	Thickness of 0.13 mm, inscribed circle of 0.05–0.15 mm	Cylindrical hole with double-sided chip breaker	Turning for general purpose
Lubrication		Dry
Processing parameters		Cutting speed of 73 m/min, feed rate of 0.11 mm/rev, depth of cut of 1 mm and machining time of 20 s

CNC: computer numerical control; PVD: physical vapor deposition.

Experimental procedure

The orthogonal turning experiments were carried out on a computer numerical control (CNC) lathe as per the specifications given in Table 2. A new carbide insert edge was used for machining each titanium alloy. Although the workpieces of different diameters were used in the experiments, the cutting speed and feed rate were maintained at 73 m/min and 0.11 mm/rev, respectively. The machining duration was kept 20 s for the three titanium alloys. All the tests were repeated once. Cutting forces during machining were measured using the piezoelectric Kistler dynamometers. The worn-out inserts were examined under SEM. Also, EDAX was performed on the cutting tool surfaces to identify the diffusion of alloying elements from work surface to the tool face. Temperature during machining was measured using thermal image camera FLIR P640 at 30 Hz that has a spatial resolution of 640 × 480 pixels.

Also, several orthogonal machining experiments on each of the three alloys were done to obtain chip roots using a quick-stop device. This device withdraws the cutting tool instantaneously leaving a partially formed chip on the work surfaces. The roots thus obtained were examined under SEM to obtain various parameters such as shear angle, chip segment pitch and chip compression factor that are required to evaluate chip–tool contact length.

Results and discussion

In this section, results of experiments described in the previous section are presented. SEM images of the worn-out surfaces and cutting edges of tools were analyzed to identify tool wear mechanisms operating during machining of each titanium alloy. The results of an EDAX on worn-out cutting edge show the diffusion of various alloying element from a titanium alloy to the insert face. A pattern of cutting and feed forces during machining of the three titanium alloys has been correlated with the mechanisms of tool wear. Finally, chip–tool contact length was evaluated using various analytical models, and the results are compared with those obtained from this experimental work.

Temperature at cutting zone

The temperature reached during machining has a profound effect on tool wear mechanism. A higher temperature at the cutting zone softens the tool and accelerates its wear. In this experiment, maximum temperature reached during machining operation is recorded and thermal images of this are shown in Figure 3(a)–(c). It is known that a thermal image camera gives an overall temperature of the cutting zone, which may not represent the exact temperature of tool–work or tool–chip interface. Therefore, the recorded temperature by this method is considered to be the overall temperature of the cutting zone.

Figure 3.

Thermal image of maximum temperature reached during machining: (a) α alloy, (b) $α + β$ alloy, (c) β-rich alloy and (d) maximum temperature at cutting zone of the three titanium alloys.

In α alloy, temperature of the cutting zone exceeds 550 °C during machining (see Figure 3(a)). In $α + β$ alloy, the maximum temperature reached during machining was 519 °C (see Figure 3(b)). In the case of β-rich alloy, the maximum temperature recorded was 506 °C (see Figure 3(c)). Thus, during machining α alloy, cutting tool was subjected to the highest temperature followed by $α + β$ and β-rich alloy, when machined under identical processing conditions. It may be noted that due to a higher proportion of α phase in α alloy, a higher temperature was reached during its machining, as compared to the other two alloys. This indicates an increase in the severity in machining with a higher proportion of α a phase in the titanium alloy.

Tool wear in α alloy

Figure 4(a)–(c) shows SEM images of the rake face of the tool used in machining α alloy. The worn-out cutting edge of tool shows some wear mechanisms in machining of α titanium alloy. A magnified image of the tool face in Figure 4(a) is shown in Figure 4(b) and (c). Appearance of rough surface on the tool face shows that material from the cutting edge has been peeled off nonuniformly and there is no sign of adherence of chip material on the tool face (see Figure 4(c)). The tool face appears to be rough and delamination of coating material appears to be caused due to rubbing of chips over it. Therefore, in machining α alloy, tool coating appears to be less effective in minimizing tool wear. Also, no plastic deformation on the cutting edge is observed. This may be due to low hardness of α alloys. The chip–tool contact length on the rake face has been measured from the magnified SEM image of cutting edge of insert, as shown in Figure 4(b), which is about 201 µm.

Figure 4.

SEM image of worn-out tool face and cutting edge used to machine α alloys: (a) insert, (b) magnified image of insert showing chip–tool contact length and (c) mechanism of tool wear.

EDAX of the material on the tool face shows the presence of Sn on the worn edge. By ignoring the presence of Ti and Al, which are the part of coating, the presence of Sn confirms its diffusion from the workpiece on to the tool face (see Table 3 and Figure 5).

Table 3.

Element analysis of worn-out edge.

α alloy		$α + β$ alloy		β-rich alloy
Element	wt%	Element	wt%	Element	wt%
C	22.62	C	33.46	C	36.13
Al	6.23	Al	4.89	Al	4.22
W	1.71	W	2.48	W	7.55
Sn	2.41	–	–	Si	11.63
Ti	67.03	Ti	41.68	Mo	6.03
V	0	V	1.17	Ca	3.63
Co	–	Co	0.71	Si	2.77

Note: Sn, V, Mo are significant alloying elements of rich alloy, which are diffused on the worn out cutting edge of insert.

Figure 5.

Element analysis at the cutting edge by EDAX in machining α alloy.

Similar to rake face, flank face of the insert has also been observed under SEM. Figure 6(a)–(c) shows SEM images of the flank face at various magnifications that illustrate the wear pattern on inserts. Chipping of the cutting edge is observed during machining of α alloy (see Figure 6(a)). The material on the flank face away from the cutting edge is being removed. Also, SEM image of the cutting edge at very high magnification shows a nonuniform wear (see Figure 6(b)) and a further enlarged view in Figure 6(c). The width of wear land measured is 109 µm (see Figure 6(a)). Thus, in machining α alloy, wear mechanisms prevalent on the flank face are chipping and nonuniform abrasive wear of the surface.

Figure 6.

Flank face of worn-out insert in machining α alloy: (a) insert edge and surface at flank, (b) magnified image of flank surface and (c) magnified image of cutting edge.

Tool wear in $α + β$ alloy

SEM images of a worn-out insert used in machining of $α + β$ titanium alloy are shown in Figure 7(a)–(c). The worn-out edge of the insert shows adherence of chip on the cutting edge (see Figure 7(a)–(c)).The chips appear to get welded to the cutting edge (see Figure 7(b) and (c)). A change in color of the worn-out part of insert shows initiation of delamination of the coating. However, the delamination occurs slowly by moving chips on the rake face. This observation is similar to that by Ibrahim et al.¹¹ where slow damage to the coating was observed in the first 10 s of machining at similar cutting conditions. This confirms the utility of the tool coating in machining Ti6AL4V. However, the worn-out edge appears uniform without any dimple marks or trough on the rake face. This shows that the contact between the chip and the rake face is uniform, which prevents abrasion¹¹ of tool material by moving chips. The length of chip–tool contact measured on the tool face is about 201 µm (see Figure 7(b)).

Figure 7.

SEM image of worn-out face and cutting edge used to machine $α + β$ alloys: (a) insert, (b) magnified image of insert showing chip–tool contact length and (c) mechanism of tool wear.

EDAX shows the presence of vanadium on the worn-out tool edge (see Table 3 and Figure 8). By ignoring the presence of Ti and Al, which are a part of coating, the presence of vanadium at the cutting edge shows its diffusion on the tool face. This is because vanadium is a significant alloying element in $α + β$ alloy. Furthermore, due to high pressure at the tool edge, a partially developed built-up edge appears (see Figure 7(c)). No plastic deformation or chipping is observed on the tool cutting edge.

Figure 8.

Element analysis at the cutting edge by EDAX in machining $α + β$ alloy.

The wear pattern on the flank face shows features that are similar to that on the rake face. In $α + β$ alloy, tool material at the cutting edge appears to have been removed uniformly instead of chipping (see Figure 9(a)). Also, the material on the flank surface has been removed uniformly without any sign of notching or dimples on the flank surface (see Figure 9(b)). At the cutting edge, wear appears to be uniform (see Figure 9(c)). Width of wear land measured on the frank face is 210 µm (see Figure 9(a)). Wear on flank face of the tool in machining $α + β$ alloy is more uniform as compared to that on α alloy.

Figure 9.

Flank face of worn-out insert in machining $α + β$ alloy: (a) insert edge and surface at flank, (b) magnified image of flank surface and (c) magnified image of cutting edge.

Tool wear in β-rich alloy

SEM images of worn-out insert used to machine β-rich titanium alloy are shown in Figure 10(a)–(c). While the cutting edge appears to be intact over most of its length, a small portion of it shows discontinuity, probably due to deformation or fracture of cutting edge (see Figure 10(b) and (c)). This could be due to high temperature of around 506 °C recorded by the thermal camera during machining and higher material hardness (55% higher than α alloy) (see Figure 3(c)). A small contact of the chip over the cutting edge gives rise to high pressure and temperature, which softens the cutting edge material. This affects the integrity of edge due to deformation of the insert material. No adherence of work material on the face of the tool or the cutting edge is observed. A color change along the width of worn-out edge shows removal of coating. However, the planer surface near the cutting edge shows slow rate of coating delamination, which underlines the effectiveness of coating in machining of β-rich alloys. Also, there is no sign of built-up edge formation on the cutting edge along the tool face. Due to deformation of cutting edge, both rake and flank faces get affected. The measured chip–tool contact length from SEM image on the face of insert is 210 µm (see Figure 10(b)).

Figure 10.

SEM image of worn-out face and cutting edge used to machine β-rich $α + β$ alloys: (a) insert, (b) magnified image of insert showing chip–tool contact length and (c) mechanism of tool wear.

EDAX on the tool face shows the presence of Mo on the worn-out tool face (see Table 3 and Figure 11). Ignoring the presence of Ti and Al, which are a part of tool coating, diffusion of Mo, which is a significant alloying element of the work material, is confirmed on tool face.

Figure 11.

Element analysis with EDAX at the cutting edge of β-rich alloy.

Figure 12(a)–(c) shows flank wear pattern on a worn-out insert during machining β-rich titanium alloy. Here, chipping at the cutting edge is observed (see Figure 12(a)). Also, tool material appears to be removed nonuniformly from the flank face during machining (see Figure 12(b)). However, the material at the cutting edge is removed uniformly (see Figure 12(c)). Dimples at the cutting edge show sudden fracture on the cutting edge (see Figure 12(c)). The width of flank wear land measured is 250 µm (see Figure 12(a)). Larger width of flank wear land (250 µm) over the chip–tool contact length points to flank wear as a dominant mode of tool wear in machining β-rich titanium alloy.

Figure 12.

Flank face of worn-out insert in machining β-rich alloy: (a) insert edge and flank surface, (b) magnified image of flank surface and (c) magnified image of cutting edge.

Correlation between machining forces and tool wear

An attempt has been made to correlate pattern of variation in the cutting and thrust forces and the predominant tool wear mechanism in machining of the three titanium alloys. Figure 13(a) and (b) illustrates a representative pattern of cutting forces obtained using dynamometers in machining of the three titanium alloys.

Figure 13.

Pattern of (a) cutting force and (b) thrust force in orthogonal machining of the three titanium alloys.

In α alloy, the magnitude of cutting forces (130 N) and fluctuation in their magnitude, from 119 to 136 N, appears to be the highest (see Figure 13(a)). On the other hand, in the case of $α + β$ alloy, magnitude (120 N) and fluctuation (120–124 N) in the cutting forces were the lowest. The magnitude (125 N) and its fluctuation in cutting forces (125–134 N) in β-rich alloy lie in between the two. The α alloys have a presence of only one phase, that is, α phase. On the other hand, $α + β$ and β-rich alloys have the presence of both α and β phases. This makes α alloy more temperature resistant. The heat generated during machining has lower influence on the strength of α alloy. Therefore, a higher magnitude of cutting forces was observed during machining of α alloy.¹²

A change in the pattern of cutting force can be further explained from the chip microstructure of the three titanium alloys, as shown in Figure 14(a)–(c). In α alloy, segments are formed predominantly by thermal softening that leads to formation of shear bands (see Figure 14(a)). Also, grains outside the shear band appear deformed. Due to this, a large reduction in the cutting force was observed during its machining. In $α + β$ alloy, segments are formed by a combination of fracture and shear band formation (see Figure 14(b)). Also, grains outside the shear bands are not deformed similar to α alloy. This causes a reduction in the fluctuation of cutting forces. In the case of β-rich alloy, a sharp shear band without any deformation of grains around it has been observed (see Figure 14(c)). This reduces the fluctuation of cutting forces.

Figure 14.

Chip microstructure of the three titanium alloys: (a) α alloy, (b) $α + β$ alloy and (c) β-rich alloy.

Figure 13(b) shows a variation in the thrust forces. In this case, the highest magnitude of thrust force is observed during machining of β-rich alloys. In α alloy, similar to cutting forces, thrust forces have higher intensity of fluctuation. Hence, the β-rich alloy shows uniform thrust forces. It is observed that this pattern of machining forces reflects the dominant tool wear mechanism for the three titanium alloys. In α alloy, due to higher magnitude and intensity of fluctuation in the cutting forces, continuous contact at the cutting edge of the tool and workpiece occurs for a smaller period of time. This reduces the possibility of formation of built-up edge. However, the higher fluctuation in machining forces causes an early coating delamination and abrasion wear on the rake face. This is evident from the SEM images of inserts used for machining of α alloy, as shown in Figure 4(a)–(c).

In the case of $α + β$ alloys, uniform cutting and thrust forces during machining cause a continuous contact between the tool face and workpiece. This creates a favorable situation for welding of chips on the cutting edge, and hence, the formation of built-up edge takes place. This is evident from the SEM images of the tool inserts in Figure 7(a)–(c). Also, uniform thrust forces cause uniform wear on the flank face of the tool, as shown in Figure 8(a)–(c).

In the case of β-rich alloy, the higher magnitude of cutting forces introduces deformation on some portions of the cutting edge. This is evident from the SEM image of worn-out insert shown in Figure 10(a)–(c). Also, a higher magnitude of thrust forces causes chipping of the cutting edge, as shown in Figure 12(a). As compared to α and $α + β$ alloys, a higher width of flank wear land (250 µm) was observed during machining of β-rich alloy. This could be due to a higher magnitude of thrust forces (see Figure 13(b).

Evaluation of average chip–tool contact length

Chip slides over the rake face of tool. The contact length of the chip with rake face is called chip–tool contact length. This length determines the friction between the chip and the rake face. Also, the maximum temperature reached during machining occurs in this region. Therefore, this value is useful in designing cutting tool geometry, and it determines cutting forces and the rise of temperature during machining.^9,13 A smaller chip–tool contact length ensures less friction and lowers temperature at chip–tool interface and reduces the quantity of heat transferred to the tool. In this work, the chip–tool contact length has been evaluated using various analytical models and compared with the experimentally observed values in machining of the three titanium alloys. The experimental values of chip–tool contact length were measured from SEM images of worn-out inserts. Figures 4(b), 7(b) and 10(b) show chip–tool contact length on the rake face while machining α, $α + β$ and β-rich titanium alloys, respectively. It may be noted that the three titanium alloys show no significant variation in the average chip–tool contact length, even though they have a wide variation in their hardness. It may be noted that coefficient of friction between work–tool interface influences the chip–tool contact length. Therefore, coefficient of friction is determined using Merchant’s shear theory. It is given by the following expression

μ = \frac{F}{N} = \frac{F_{c} \sin α + F_{t} \cos α}{F_{c} \cos α - F_{t} \sin α}

(1)

where µ is average coefficient of friction, F is tangential component of resultant force along the rake face, N is normal component of resultant force, F_c is cutting force, F_t is thrust force and α is rake angle of the tool of 0° for the insert used in the experiment. The average cutting and thrust force measured using dynamometer and friction coefficient evaluated by putting these values in equation (1) are given in Table 4.

Table 4.

Machining forces and friction coefficient.

Serial number	Type of alloy	F_c (N)	F_t (N)	µ
1	α alloy	85	127	0.67
2	$α + β$ alloy	74	118	0.63
3	β-rich alloy	90	125	0.72

The coefficients of friction evaluated are 0.67 for α alloy, 0.63 for $α + β$ alloy and 0.72 for β-rich alloy. In α alloy, a relatively higher friction coefficient increases its average chip–tool contact length. Also, this shows almost same rate of progression of wear on the rake face of the tool in the three titanium alloys. The chip–tool contact length was also evaluated using four different analytical models, as shown in Table 5. The values of shear angle (φ) and chip compression factor (λ) are determined from the SEM pictures of chip roots, see Figure 15 for a typical chip root of α alloy and the corresponding evaluation of shear angle (φ) and chip compression factor (λ).

Table 5.

Average chip–tool contact length evaluated using experimental and various analytical models.

Serial number	Method	Chip–tool contact length L_c (µm)
Serial number	Method	Formula	α	$α + β$	β-rich
1	Experimental	As shown in Figures 3(b), 6(b) and 9(b)	201	201	210
2	Lee and Shaffer¹⁴	$L_{c} = h \sqrt{2} / (\sin ϕ \cdot \sin (45 + ϕ - α))$	268	235	228
3	Abuladze¹⁵	$L_{c} = 2 h [λ \cdot (1 - \tan α) + \sec α]$	572	566	526
4	Poletika¹⁶	$L_{c} = h \cdot (2.05 . λ - 0.55)$	301	294	254
5	Tay et al.¹⁷	$L_{c} = h_{.} \sin θ / (\cos α \cdot \sin ϕ)$	171	159	158

h is uncut chip thickness, which is feed rate for orthogonal cutting; λ is chip compression factor; ϕ is shear angle; α is rake angle; θ is inclination of resultant cutting force to shear plane of $(ϕ + λ - α)$ .

Figure 15.

Method to evaluate shear angle and chip compression ratio.

The chip–tool contact length calculated using the models and their comparison with the experimental values are presented in Figure 16. It may be noted that the results obtained with Lee and Shaffer’s¹⁴ model and Tay et al.’s¹⁷ model match closely with the experimental values. While the Lee and Shaffer’s model overestimates average chip–tool contact length, Tay et al.’s model underestimates it. The average chip–tool contact lengths predicted with Lee and Shaffer’s model are based on the shear angle. In this work, the shear angle is determined from the analysis of chip roots (Figure 15). A typical calculation involved in the evaluation of chip–tool contact length is presented in Appendix 1. It is envisaged that since Lee and Shaffer’s model incorporates shear angle, the model gives prediction closer to the experimental values. Similarly, Tay et al.’s model too involves shear angle beside friction angle. In this work, both these angles are obtained from the experimental data. Again, the prediction of the chip–tool contact length from this model appears to be close to the experimental values, although the values are underestimated. On the other hand, Abuladze’s¹⁵ model uses chip compression ratio to evaluate chip–tool contact length. The inaccuracy in determination of this ratio, particularly for the segmented chips, introduces a large margin of error in the prediction of chip–tool contact length. Poletika’s¹⁶ model is primarily an empirical model. Hence, it requires specific constants. As the constants could not be evaluated for the alloys used in this work, the evaluation of chip–tool contact length with this model lies away from the experimental data.

Figure 16.

A comparison between experimental and analytically predicted chip–tool contact length.

Comparative evaluation of tool wear criteria

Table 6 summarizes a comparative evaluation of different tool wear criteria observed in three titanium alloys. In α- and β-rich alloys, a nonuniform abrasion on the tool face and flank was observed. In $α + β$ alloys, formation of built-up edge was observed. Diffusion of major alloying element of titanium alloy was found on the tool face. Cutting edge integrity was affected in β-rich alloy due to its higher hardness. A relatively higher fluctuation of cutting forces (11 N) could be one of the reasons for a higher tool wear in machining of α alloy.

Table 6.

Summary of tool wear criteria.

Serial number	Location	Wear mechanisms	α alloy	$α + β$ alloy	β-rich alloy
1	Tool face	Abrasion	Nonuniform	Uniform	Nonuniform
		Coating delamination	Rapid	Slow	Slow
		Average chip–tool contact length	201 µm	201 µm	210 µm
		Diffusion of alloying element	Diffusion of Sn	Diffusion of V	Diffusion of Mo
		Built-up edge formation	No	Yes	No
2	Tool flank	Abrasion	Nonuniform	Uniform	Nonuniform
		Chipping	Observed	Not observed	Observed
		Wear land	109 µm	210 µm	250 µm
3	Cutting edge	Integrity	Intact	Intact	Affected
4	Forces	Cutting forces	Highest fluctuation (±11 N)	Lowest fluctuation (±4 N)	Medium fluctuation (±5 N)
4	Forces	Thrust forces	Medium (75 ± N)	Low (70 ± 2.5 N)	High (90 ± N)

Conclusion

Based on the discussions of the experimental results, the following conclusions are drawn:

Machining of α alloy involves a higher magnitude of cutting forces and a higher intensity of fluctuation in the machining forces. Therefore, in the machining of α titanium alloy, delamination of coating occurs early. Thus, coating on the tool is relatively less effective in machining α alloy.

A uniform cutting and thrust forces were observed during machining of $α + β$ alloy. Therefore, machining $α + β$ alloy shows adherence of the work material on the tool face due to continuous contact between the tool and work. Therefore, formation of built-up edge was observed during its machining. Also, this encourages abrasion and diffusion of work elements on to the tool face during machining operation. Slow and uniform coating delamination underlines its effectiveness in machining of $α + β$ titanium alloys.

In the case of β-rich alloys, a higher magnitude of thrust forces was observed during machining. Therefore, machining β-rich alloy shows the deformation on some portion of the cutting edge. The damage to cutting edge causes both the face and the flank wear during machining operation. The coating delaminates at a lower rate while machining this alloy. Therefore, tool coating will help in improving the tool performance in machining of this titanium alloy.

Diffusion of major alloying element such as Sn from α alloy, V from $α + β$ alloy, and Mo from β-rich alloy is observed on the worn surfaces of cutting tools in machining of these alloys.

The chip–tool contact length measured from SEM images was almost the same in the case of α and $α + β$ alloys (201 µm). However, it is slightly higher in the case of β-rich alloy (210 µm). Lee and Shaffer’s and Tay et al.’s models predict chip–tool contact length closer to the experimental values as they are based on shear and friction angles.

Footnotes

Appendix 1

The average chip–tool contact length is evaluated analytically with Lee and Shaffer’s, Abuladze’s, Poletika’s and Tay et al.’s models. Various parameters used for the evaluation are determined from the experiments. A sample calculation showing evaluation of chip–tool contact length, L_c, using each model is described in the following. These calculations use orthogonal machining data of α alloy at 73 m/min cutting speed and 0.11 mm/rev feed rate.

Acknowledgements

This article is a revised and expanded version of article entitled “Evaluation of Tool Wear Mechanisms in Machining of Three Different Types of Titanium Alloys” presented at the 4th International and 25th AIMTDR Conference, Jadavpur University, Kolkata, 14–16 December 2012.

Declaration of conflicting interests

The authors declare that there are no conflict of interest.

Funding

The authors gratefully acknowledge the partial support provided for this work by the National Centre for Aerospace Innovation and Research—a collaboration of Department of Science and Technology, Government of India; The Boeing Company and IIT Bombay.

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