Influence of regular and random cutting tool deformation on the cutting force of three-dimensional turning operation

Int. J. Machining and Machinability of Materials, Vol. 14, No. 4, 2013 311

Copyright © 2013 Inderscience Enterprises Ltd.

Influence of regular and random cutting tool deformation on the cutting force of three-dimensional turning operation

Samy E. Oraby Department of Manufacturing Engineering, College of Technological Studies, The Public Authority for Applied Education and Training, P.O. Box 42325 Shuwaikh 70654, Kuwait Fax: +965-24832761 E-mail: [email protected] E-mail: [email protected]

Abstract: The current work emphasises the impact of the various modes of cutting tool edge wear and failure on the different force components considering the three-dimension orthogonal continuous machining using multi-coated carbide tips. Edge force is usually attributed to the ploughing and rubbing actions on the tool-workpiece interface which, in turn are associated with the extent of the inevitable wear modes: nose, flank, and notch wear. Modelling of the experimental results using linear and non-linear regression analysis is established to qualitatively and quantitatively grasp the functional interrelation among the involved parameters. Results indicated that all force components are, to different extents, affected by all edge wear land modes. However, it is shown that each of the observed edge wear and failure has its own potential on specific force components and on specific cutting pressure.

Keywords: cutting tool; wear and deformation; carbide inserts; cutting forces; mathematical models; specific cutting pressure.

Reference to this paper should be made as follows: Oraby, S.E. (2013) ‘Influence of regular and random cutting tool deformation on the cutting force of three-dimensional turning operation’, Int. J. Machining and Machinability of Materials, Vol. 14, No. 4, pp.311–341.

Biographical notes: Samy E. Oraby is a Professor at Faculty of Engineering, Port Said University, Egypt and is currently at the College of Technological Studies, PAAET, Kuwait. He obtained his PhD in Mechanical Engineering from the University of Sheffield, England in 1990. He has many publications covering machining and manufacturing processes. He is a member and reviewer in many regional and international manufacturing journals and magazines.

1 Introduction

Machining processes stems its importance from being a major manufacturing method where some statistics (Astakhov, 2005) indicated that about 15% of all mechanical components manufactured worldwide are derived from machining operations.

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Productivity enhancement at lower power requirements usually represents the ultimate objective of a machining process. While productivity is achieved using higher levels of operating cutting parameters (speed, feed and depth of cut), the consumed power in the process depends to great extents on the environment tribological conditions at the tool-chip-workpiece interfaces. A proper manipulation of the technical junction between productivity enhancement and power reduction is still required since, as stated by many investigators, for example (Zemzemi et al., 2007), there is still lack of fundamental understanding of the phenomenon occurring at the tool-chip and the tool-workpiece interfaces. One of the most tribological parameters affecting both productivity and consumed power is the edge wear during machining.

Until early ‘90s of the last century, a tool change policy was entirely based on the accumulated experience and skills of the machine operators along with the total efficiency and capacity of the machine tool. Since then there was a transition from traditional to automated tool change strategy considering the possible in-process monitoring and/or control the developed wear level on the cutting tool edges. With the emerging and promising adaptive control AC technology (http://www.omative.com/173890/ACM), it became possible to optimise, monitor, and control CNC machine performance to achieve maximum productivity. This basically depends on the in-process monitoring of the tool wear through analytical and empirical modelling (Oraby et al., 2003).

Figure 1 Wear and force measurement system in three-dimensional orthogonal cutting (see online version for colours)

In practice, the cutting edge in machining deforms in an indeterministic fashion that requires in-process monitoring and/or control techniques to assess the tool performance during machining. In addition to the regular edge wear that usually develops at both the tool-chip and tool-workpiece interface surfaces, many random edge fracture types such as chipping, fracture, breakage, etc., are also common, Figure 1. In practice, many regular and random wear modes usually take place simultaneously on the cutting edge with the domination of one or more elements under certain operating conditions. This is expected to escalate the rate of increase of the cutting forces hence affects the power requirements,

Influence of regular and random cutting tool deformation 313

the system dynamic stability and the surface integrity of the machined product. The cutting force has been reported as sensitive, credible and reliable measure courier of the edge wear variations (Okashi and Sata, 1958; Zorev, 1966; Bayoumi et al., 1993; Oraby and Hayhurst, 2004; Oraby et al., 2005).

The main objective of the current work is to evaluate the impact of various possible modes of edge wear and deformation during thee-dimension turning process on the conventionally associated variations in the resulting cutting forces. This includes the evaluation of the individual and mutual influence of the cutting parameters; speed, feed and depth of cut. The isolation of the effect of individual and combined edge deformation mode(s) on forces and on the specific pressure is one of the main considered topics. This is achieved through the use of the most appropriate and, statistically adequate and significant non-linear modelling structures together with the relevant experimental data.

2 Orthogonal merchant’s model adaption considering edge wear

Orthogonal force system in metal cutting was first proposed by Merchant (1945), Figure 2. Merchant’s orthogonal model, assumes a perfectly sharp tool with no concentrated edge force on the cutting edge, a continuous chip, plane strain, uniform shear stress distribution on the shear plane, and equilibrium of the action of equal and opposite resultant force acting at the shear zone and tool-chip interface. The total force is represented by two equal, opposite forces (action and reaction) Rs and Rs′ which hold the chip in equilibrium. The force, Rs′, which the tool exerts on the chip, is resolved into the tool face-chip friction force F and normal force N. The force, Rs, which the workpiece exerts on the chip, is resolved along the shear plane into the shearing force, FS which is responsible for the work expended in shearing the metal, and into normal force FN, which exerts a compressive stress on the shear plane. Force Rs is also resolved along the direction of tool motion into Fcs, termed by merchant as the cutting force, and into Fst, the thrust force. Principles of the well-known merchant-type model are:

. . .cos( )sin .cos( )

ccs

τ b t γFγ

−=

+ −β

φ φ β (1)

. . .sin( )sin .cos( )

cts

τ b t γFγ

−=

+ −β

φ φ β (2)

arctan arctan ts

cs

Fμ γF

⎛ ⎞= = + ⎜ ⎟⎝ ⎠

β (3)

1 ( / ) cos cos( ) arctan4 2 1 ( / ) 1 sinπ t tc γ r γγ

t tc r γ⎧ ⎫ ⎛ ⎞= − − = =⎨ ⎬ ⎜ ⎟− −⎩ ⎭ ⎝ ⎠

φ β (4)

( )cos sin sin.

cs ts

c

F Fτ

b t−

=φ φ φ

(5)

As early stated by some pioneer studies (Merchant, 1945; Ernst and Merchant, 1941), the width of cut bc, the undeformed cut thickness t and the normal rake angle γ are usually considered as given geometrical quantities for a cutting process. However, the shear

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stress τ and the frictional angle β can be obtained from literature and the conventional sliding friction testing, while the shear angle φ is a computational parameter obtained from the specific shear angle relation.

Figure 2 Orthogonal cutting model allowing for tool flank wear effect

Source: Wang et al. (2003)

As cutting continues, edge wear emerges along the tool clearance face (flank) as a result of the intimate contact between the cutting edge and the workpiece machined surface. Therefore, additional forces are inevitable and, a modified Merchant’s model should be required to consider the emerged situation.

According to many investigators (Kobayashi and Thomson, 1960; Thomson et al., 1962; Song, 2006), the friction mechanism on the rake face was hardly affected by the wear land changes at the tool flank. Zorev (1966) stated that the chip formation process was affected solely by the force on the rake face while the force acting on the flank did not take part in the process since it produced by the elastic reaction of the layer of the machined material lying under the tool. This implies that machining with a continuously developed edge flank wear does not affect the cutting quantities (shear angle, friction angle, shear stress, etc.), but produces only additional rubbing forces on the wear land on both the tool flank and workpiece surfaces. Shi and Ramalingam (1991) reported that flank wear land led to an increase in the cutting force on the flank surface and that was proportional to the plastic flow in the workpiece machined surface. Additionally, they studied the shearing and friction processes using a controlled chip breaker and, they found that these remained unaffected by flank wear.


As generally proposed by many researchers (Wang et al., 2003; Song, 2006; Milutinović and Tanović, 2011), further parameters should be introduced to merchant’s model to consider the concentrated force (edge force), or the rubbing and ploughing force Rw acting at the cutting edge. The edge force is developed as the wedge is not perfectly sharp and, is manifested by the positive force intercepts when the measured force versus cut thickness graphs are extrapolated to zero cut thickness. Armarego (1982) claimed that this was proportional to the engaged cutting edge length and it could be removed from the measured force data when evaluating the basic cutting quantities using the shin shear zone model. Consequently, the above equations to evaluate β and τ are modified to consider the existence of rubbing or ploughing force, Rw, Figure 2.

arctan arctan tm te

cm ce

F Fμ γF F

−⎛ ⎞= = + ⎜ ⎟−⎝ ⎠β (6)

( ) ( )[ ].cos sin .sin.

.cm ce tm te

c

F F F Fτ

b t− − −

=φ φ φ

(7)

where Fce and Fte are found from the intercepts of the measured force-cut thickness graphs. The total cutting force can be represented by:

. . .cos( ) .sin .cos( )

cc cs ce c c

τ b t γF F F k bγ

−= + = +

+ −β

φ φ β (8)


ct ts te t c

τ b t γF F F k bγ

−= + = +

+ −β

φ φ β (9)

The edge force intensity factors, kc and kt, are obtained from the orthogonal cutting tests. As shown in Figure 2, by taking into account the secondary rubbing or ploughing force on the tool wear land:

. . .cos( )sin .cos( )

cc cs ce ce c c cw

τ b t γF F F F k b Fγ

−= + + = + +

+ −β

φ φ β (10)


ct ts te te t c tw

τ b t γF F F F k b Fγ

−= + + = + +

+ −β

φ φ β (11)

As concluded by many investigators (Wang et al., 2003; Song, 2006; Milutinović and Tanović, 2011; Armarego, 1982; Huang and Liang, 2005; Waldorf et al., 1998), there were some common emerged facts suggesting that the flank wear land significantly increased the rubbing force on the cutting edge-flank interface, thus the overall cutting forces, but did not affect the forces required for shear process (chip formation) or the friction process on the tool-chip interface. In addition, it is claimed that with the existence of flank wear land, the conventional orthogonal model still applicable to determine the forces in the shear plane and at the tool-chip interface while the additional edge forces, rubbing and ploughing forces on the flank wear land are best considered independently. However, it is indicated (Astakhov, 2006; Popv and Dugin, 2013) that the predicted flank forces Fce and Fte are usually much higher than those found by extrapolation of the corresponding components of the cutting force on zero chip thickness. Also, the consideration of shear stress τ as the only mechanical properties to calculate the forces

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lacks reality since, in many cases; a material with higher shear stress tends to produce much lower wear rate and forces than that with lower shear stress.

3 Experimental procedures and setup

Parameters levels and ranges, Table 1, were selected to conform reasonably to practical rough turning operations. Five levels were specified for each of the cutting parameters; cutting speed v, federate f, and depth of cut ap. To insure modelling statistical adequacy and significance, these are arranged according to the central composite design (CCD) technique to constitute a total of 24-experiment, Table 2. Multicoated carbide inserts (Sandvik 435 – ISO P35) were employed to cut 709M40 (EN19) high tensile stress chromium alloy steel. Inserts coating consisted of three layers: the first is a TiN of 1 μm thickness followed by 3 μm layer of Al2O3 and finally 5 μm layer of TiC over the sintered carbide substrate. Inserts were of SPUN 12 03 12 configuration (thickness = 3.18 mm and rn = 1.2 mm and l = 12.7 mm). Inserts were clamped to a Sandvik CSTPRTMAX tool holder with seat configuration 6°, 5°, 0°, 60°, 30° normal rake, clearance, inclination, approach and side approach angles respectively. For each experiment, wear value at the tool-workpiece interface was measured sequentially at three regions: nose VBC, flank VBBmax, and notch VBN, Figure 1. For each subtest, three cutting force components: main (tangential) Ft, feed (axial) Fa and radial Fr, Figure 1, were measured using a three-component dynamometer that replaced the tool post of a Colchester Mascot 1600 turning lathe. Table 1 Abrasive material and shape properties

Level parameter Lowest Low Medium High Highest

Speed (v) [m/min] 50 72 104 145 206 Feed (f) [mm/rev] 0.06 0.12 0.2 0.3 0.6 DOC (ap) [mm] 1.5 2.0 2.25 2.5 3.0

Table 2 CCD of the entire set of experiments

Test seq.

Speed (v) m/min

Feed (f) mm/rev

DOC (ap) mm

Test seq.

Speed (v) m/min

Feed (f) mm/rev

DOC (ap) mm

1 72 0.12 2 13 206 0.2 2.25 2 145 0.3 2 14 50 0.2 2.25 3 145 0.12 2.5 15 104 0.6 2.25 4 72 0.3 2.5 16 104 0.06 2.25 5 104 0.2 2.25 17 104 0.2 3 6 104 0.2 2.25 18 104 0.2 1.5 7 145 0.12 2 19 206 0.2 2.25 8 72 0.3 2 20 50 0.2 2.25 9 72 0.12 2.5 21 104 0.6 2.25 10 145 0.3 2.5 22 104 0.06 2.25 11 104 0.2 2.25 23 104 0.2 3 12 104 0.2 2.25 24 104 0.2 1.5


4 Experimental, analysis, discussions, and evaluation

4.1 Effect of regular wear modes on force variation

Tool edge in machining is subjected to hostile conditions of high contact temperatures, high contact pressure, cyclic frequent chip-formation-separation mechanism, etc., at the tool-chip and tool-workpiece interfaces. Such aggressive environment usually leads to many edge deformation modes such as tool edge softening; diffusion, oxidation, abrasive, and adhesion wear; cracking due to thermal fatigue; fretting wear; chipping and breakage; slice fracture of the tool material; wear due to hammering chip, etc. However, most of the aforementioned wear and deformation mechanisms act simultaneously with predominant influence of one or more of them. Identification of the most influential and significant mechanism(s) is still highly subjective (Astakhov, 2006) and, in many situations a topological approach is widely accepted where the influence of cutting conditions, temperatures, contact stresses, relative cutting velocities, etc., is experimentally evaluated and interpreted.

4.1.1 Cutting speed considerations

The effect of the cutting speed on the tool life and on the cutting force may be explained through the comparison of the experimental results of the tests # 20, 12 and 13 in which the employed speed values were 50, 104 and 206 m/min respectively.

Figure 3 shows the SEM micrographs together with the experimental wear-time-force plots Force fluctuations are evident due to the frequent formation and separation of the built-up edge BUE. At the end of the test, a local edge fracture occurred at the edge nose leading to force increase especially in the feed and the radial components, Figure 3(b).

Figure 3 Experimental results of test #20 (v = 50 m/min, f = 0.2 mm/rev, ap = 2.25 mm), (a) SEM micrographs for entire flank edge chipping (b) Wear-force-time relationships (see online version for colours)

(a)

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Figure 3 Experimental results of test #20 (v = 50 m/min, f = 0.2 mm/rev, ap = 2.25 mm), (a) SEM micrographs for entire flank edge chipping (b) Wear-force-time relationships (continued) (see online version for colours)

(b)

Figure 4 Experimental results of test # 12 (v = 104 m/min, f = 0.2 mm/rev, ap = 2.25 mm), (a) SEM micrographs of regular edge wear (b) Wear-time-force relationships (see online version for colours)

(a)

(b)


For a moderate combination of cutting parameters: 104, 0.2 and 2 speed, feed, and depth of cut respectively, Figure 4, an almost equal gradual wear level developed over the edge length except for an early random fracture occurred on the notch area. At the end of the test, wear levels were insignificant enough to produce a noticeable increase in all the cutting force components.

Figure 5 Experimental results of test #13 (v = 206 m/min, f = 0.2 mm/rev, ap = 2.25 mm), (a) Edge failure due to plastic lowering (b) Softening reaching the tool face (c) Wear-time-force relationships (see online version for colours)

(a) (b)

(c)

The use of high speed of about 206 m/min., test #13, Figure 5, ended with a catastrophic plastic deformation failure after only about 5 minutes cutting. Deformed area was extended to include the secondary cutting edge, Figure 5(a), and the tool face, Figure 5(b). As a result, both the feed and the radial force components were enormously increased while the main cutting component showed a less response, Figure 5(c). Due to the resulting elevated force values, tool breakage eventually occurred at the

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tool-workpiece interface. As elaborately explained by Astakhov (2006), the plastic lowering of the cutting edge is the predominant reason behind such a premature edge failure at high speeds. Plastic lowering is the plastic deformation of the cutting wedge as a result of combined plastic flow and spreading of tool material over the chip and tool contact surfaces. Due to plastic lowering of the cutting edge, tool configuration, especially rake and clearance angles change leading to an increase in the tool wear rate. When such a geometrical variation due to plastic lowering reaches a certain limit, the breakage of the cutting wedge takes place globally or in the form of chipping and breakage.

To evaluate the effect of the cutting speed on tool life, it is observed that the cutting time to attain a 0.254 mm average wear (arithmetic mean of VBC, VBBmax and VBN) is experimentally recorded as 120, 36 and 4 minutes that produces corresponding wear rates of 2.12, 7.06 and 63.5 μm/min respectively. This indicates that, up to a cutting speed of 104 m/min, the process temperature was still lower or equal to its optimal range while for the cutting speed of 206 m/min, the resulting high wear rate implies that the process temperature is far higher than its optimal value (Astakhov, 2007). This was the onset of thermal lowering and plastic deformation of the cutting wedge which eventually ended with catastrophic failure and breakage.

Within the specified cutting interval for test #20, Figure 3(b), force increase was recorded to be 8.2%, 27.3% and 52.9% for the main, the feed and the radial force components respectively. Counterpart force increase values for test #12, Figure 4(b), were 15.2%, 32.8% and 35.2% while they were 4.4%, 18.9% and 10.6% for test #13, Figure 5(c). However, both wear and force rates were drastically increased for test #13 as thermal lowering and deformation mechanism is activated.

In all cases, the main force component Ft was observed to be the least affected by the edge wear and failure. The radial force component Fr proved to be the most sensitive to edge wear at low-to-moderate cutting speeds.

4.1.2 Cutting feed considerations

As explained by Astakhov (2007), the true influence of the cutting feed on tool wear and its rate should not be assessed in isolation of the entire context of the other parameters of the cutting process that contributes individually and mutually to the cutting temperature (Mackarow’s low).

Figure 6 shows SEM and wear-time-force for test #16 were the least feed value of 0.06 mm/rev was employed. Such a low feed value can affect wear rate due to the formation of the cold worked layer from the preceding pass (revolution) on the machined surface (Astakhov, 2007). When the cutting feed is smaller than the depth of cold working layer, the major cutting edge cuts a workpiece that is characterised by a greater strength and hardness leading to higher tool wear rate. As shown by the relevant experimental results shown by Figure 6, there was a low gradual wear rate that is accompanied by many random disturbances in terms of edge chipping, fracture, and cratering at the rake face.


Figure 6 Experimental results of test#16 (v = 104 m/min, f = 0.06 mm/rev, ap = 2.25 mm), (a) Edge fracture at tool edge (b) Cratering at the nose (c) Wear-time-force plots (see online version for colours)

(a)

(c)

When the highest feed of 0.6 mm/rev was employed in test #15, Figure 7, a purely regular edge wear developed with a local domination impact at the edge nose.

The effect of feed on tool wear and tool life can be evaluated in the light of wear-force variations curves, Figures 4(b), 6(c) and 7(b) for tests 16, 12 and 15 in which the employed feed values were 0.06, 0.2 and 0.6 mm/rev respectively. Cutting time to attain a 0.254 mm average wear was found to be 98, 36 and 10 minutes respectively with corresponding wear rate values of 2.95, 7.06 and 25.4 μm/min. Within that cutting interval for test #16, Figure 6(b), force increase was recorded to be 27.5%, 34.7% and 58.5% for the main, the feed and the radial force components respectively. Counterpart values for test #12, Figure 4(b), were 15.2%, 32.8% and 35.2% while they were 11%, 32.9% and 46.3% for test #15, Figure 7(b). Again, the radial force component showed the highest sensitivity to the edge wear while the main force component Ft was the least affected.

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Figure 7 Experimental results of test #15 (v = 104 m/min, f = 0.6 mm/rev, ap = 2.25 mm), (a) Entire wear on both tool flank and face (b) Wear-time-force plots (see online version for colours)

(a)

(b)

Figure 8 Effect of feed and edge wear of the various force ratios (see online version for colours)


The employed level of the cutting feed may affect the dynamic stability of the cutting process. Astakhov (2007) indicated that increasing feed improved the dynamic rigidity of the machining process through changing the ratio of the radial and the axial force components. Verification of the effect of increasing feed on the ratios of the three considered force components is shown in Figure 8 considering the tests # 16, 12 and 15 which use 0.06, 0.2 and 0.6 mm/rev feed values respectively. Evaluation includes two cases: the first at the beginning of the test, where zero wear is assumed, and the second at the considered 0.254 mm criterion average wear level. At both cases the radial-to-axial (Fr / Fa) force ratio increases with increasing the cutting feed. This may lead to an improvement in the dynamic rigidity and this reduces the wear rate of the cutting edge. However, an opposite attitude is observed for each of the radial-to-tangential (Fr / Ft) and the axial-to-tangential (Fa / Ft) force components. At a criterion wear level of 0.254 mm, all considered ratios are of higher levels than those at zero wear. This is expected since the radial and the axial force are frictional, rather than power (tangential), components that are more sensitive to edge wear. At zero wear, the (Fr / Ft) is of smaller amplitude than the (Fa / Ft) counterpart. As wear increases, it increases to reach, and may cross, the level of the corresponding axial-to-tangential one. This indicates that the radial force is the most sensitive component to edge wear (Oraby and Hayhurst, 2004).

4.1.3 Depth of cut considerations

Figure 9 shows the SEM micrographs and wear-time-force plots of test #24 where the lowest depth of cut of 1.5 mm was employed. The test ended with a local nose fracture that tremendously increased the radial force component Fr, Figure 9(b). However, when the highest depth of 3 mm was employed in test #23, edge wear was of almost a regular nature except for a tiny edge fracture at about 10 minutes cutting, Figure 10.

Figure 9 Experimental results of test #24 (v = 104 m/min, f = 0.2 mm/rev, ap = 1.5 mm), (a) Edge chipping, breakage and wedge thermal lowering fracture (b) Wear-time-force plots (see online version for colours)

(a)

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Figure 9 Experimental results of test #24 (v = 104 m/min, f = 0.2 mm/rev, ap = 1.5 mm), (a) Edge chipping, breakage and wedge thermal lowering fracture (b) Wear-time-force plots (continued) (see online version for colours)

(b)

For tests # 24, 12 and 23, a 0.254 mm average wear was attained at 48, 35 and 27 minutes respectively. Within such a cutting interval, Figure 9(b), force increase for test #24 is found to be 23.6%, 44.9% and 39.6% for main, feed and radial force components respectively. Counterpart force increases values for test #12, Figure 4(b), are 15.2%, 32.8% and 35.2% while they are 6.8%, 25.2% and 21.2% for test #23, Figure 10(c). This clearly indicates that increasing the depth of cut reduces the resulting cutting variations due to the edge wear. For test #24, depth of cut was 1.5 mm which approaches the nose radius rn = 1.2 mm. This restricts the contact length to the round part of the primary and the secondary cutting edge. Accordingly, high normal stresses results on the tool-work and tool-chip interfaces, probably associated with high temperatures and plastic flow. This complex environment invoked the chipping, breakage and thermal lowering of the cutting wedge that eventually led to the global plastic catastrophic failure of the cutting edge. At such a multistage failure mechanism (chipping – breaking – softening) at the nose zone, force change was accurately reflected as a 260% increase in its original value prior to failure. A corresponding value for the axial force component was about 100% while it was just 16% for the tangential component.

In test #23 where the depth was increased to 3 mm, an early edge fracture occurred at the flank zone, Figure 10. After an instantaneous response to the edge fracture that was entirely absorbed due to the relatively longer contact length hence, lower stresses.


Figure 10 Experimental results of test #23 (v = 104 m/min, f = 0.2 mm/rev, ap = 3.0 mm), (a) Wear at flank and rubbing at tool face (b) Edge fracture (c) Wear-time-force plots (see online version for colours)

(a) (b)

(c)

4.2 Effect of irregular (random) wear modes on cutting force variations

Irregular edge fracture was observed during test #1 where a low cutting speed v value of 70 m/min was employed in combination with low levels of feed and depth of cut of 0.12 mm/rev and 2 mm respectively, Figure 11. Tool edge exhibited local chipping and fracture on both the nose and the notch regions after about 120 minutes cutting time. All force components were clearly responded as an increase of 21%, 41.6% and 63.2% for the main, the feed and the radial force components respectively, Figure 11(c).

In test #3, Figure 12, random wear disturbances were observed in two occasions. An early edge fracture occurred at the notch region, Figure 12(a), as a result of using a relatively high depth of cut ap of 2.5 mm. However, following an interval of gradual nose and flank wear modes, a sudden high rate edge wear occurred at the nose area at cutting time of 17 minutes, Figure 12(b). This continued until the edge eventually failed four minutes later due to the accompanied high temperatures and stresses.

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Figure 11 Experimental results of test #1 (v = 72 m/min, f = 0.2 mm/rev, ap = 2.0 mm), (a) Nose a flank wear (b) Notch wear (see online version for colours)

(a) (b)

(c)

At the first occasion, the radial force component increased about 15% as it was the most sensitive to the random wear at the notch area, Figure 12(c). The second stage initiated as the cutting edge was subjected to a plastic thermal lowering which instantaneously decreased the depth of engagement depth leading to a force decrease in all components. As contact area increased at the end of the experiment, the edge failed at the nose area. Accordingly, both axial and radial force components reflected the effect of the edge failure as an about 77% increase in their amplitude than that just before failure. However, tangential force component exhibited only a 19% increase within the same interval.

For test #4, Figure 13, due to the relative high levels of feed and depth of cut associated with low cutting speed, a local edge breakage at the nose area initiated after 19 minutes of cutting and continued until the edge failed after 33 minutes cutting, Figures 13(a) to 13(c). At the end of the first stage, a 49.2% nose wear increase led to force increase of 10.3%, 30.11% and 37.5% for the main, the feed and the radial force components respectively. Within the last four minutes of the experiment, the nose wear increased by 266% and, this escalated the force by 9.95%, 60.5% and 89.7% for main, feed and radial force components, Figure 13(d).


Figure 12 Experimental results of test #3 (v = 145 m/min, f = 0.12 mm/rev, ap = 2.5 mm), (a) Notch and nose wear (b) Catastrophic softening failure (c) Wear-time-force plots (see online version for colours)

(a) (b)

(c)

Figure 13 Experimental results of test #4 (v = 72 m/min, f = 0.3 mm/rev, ap = 2.5 mm), (a) Edge softening at nose (b) Entire flank deformation (c) Wear-time radar distribution (d) Force-time radar distribution (see online version for colours)

(a) (b)

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Figure 13 Experimental results of test #4 (v = 72 m/min, f = 0.3 mm/rev, ap = 2.5 mm), (a) Edge softening at nose (b) Entire flank deformation (c) Wear-time radar distribution (d) Force-time radar distribution (continued) (see online version for colours)

(c) (d)

The experimental results indicated that the common edge failure took place over the region of the edge that surrounds the edge nose starting from the flank at the primary edge and extends to the secondary cutting edge. This was basically due to the thermal softening of the cutting wedge as a result of the high temperatures and pressure in the tool-chip and tool-workpiece interfaces. This substantially affected the frictional force components especially the radial component. The tangential force, as a power component, was the least affected by the edge wear and deformation. Edge deformation at the nose usually affects the dimensional accuracy of the produced part (larger diameter) and, this is undesirable in finish machining. This is the reason behind the concern (Astakhov, 2004) to suggest the use of the radial wear parameter normal to the cutting direction as an alternative wear criterion measure.

Whenever the edge wear is evenly distributed over the entire flank contact area, an almost equal response was observed for the radial and the axial force components. However, when the cutting edge is randomly deformed, the type of the deformation is found to differently affect the various force components. Notch wear, for instance, basically affects the axial force component.

Deformation of the cutting edge is inevitable as a result of the interaction of the thermal, mechanical and tribological features involved in the process. It is practiced in forms of regular wear and irregular random modes and, in reality; both modes cannot be dealt with individually but, should be simultaneously considered in the general context of the regime under study. For instance, the effect of the cutting feed on the emerged edge wear and deformation should be considered taking the level of the employed cutting speed as a cutting heat generation prime factor. The cutting speed, as an input parameter, may be judged without the consideration of the expected process variations as cutting continues. While it is known that the cutting forces decreases marginally as speed increases when the cutting edge is primarily sharp, the situation is reversed at advanced stages when edge wear increases. Too many parameters affect the process and its symptoms and, these are associated with the effect of each of system elements


(tool-workpiece-machine tool). Among the workpiece influential parameters affecting the process are the material properties as well as the geometry of the workpiece and its relative dimensions. Among the geometrical parameters of the workpiece that causes variability in machining is the workpiece diameter. For a given surface speed in turning, decreasing diameter requires more rotational speed and, this affects the dynamic characteristics of the process. Also, it is shown (Al-Khalid et al., 2012) that material hardness varies as different diameters of the same workpart. While hardness slightly decreased at smaller diameters of AISI 4140 and AISI 1020, an opposite outcome was observed for AA 6082 aluminium alloy. Moreover, it is explained (Astakhov, 2007) that thermal and deformation waves interaction usually takes place during machining. For given cutting speed and feed, the time elapsed for one revolution affects such an interaction in such a way that a bigger workpiece diameter pumps less residual thermal energy from the past pass then, reduces tool wear and its rate.

Due to the complexities involved in metal cutting, the tool state diagnosis through the symptoms associated with the problem under study has been adopted. The symptoms are linked to the associated phenomena through the examination of an easy response. Edge deformation in machining usually represents the symptoms of the problems involved in the cutting process.

Cutting parameters (speed – feed – depth of cut) have long been considered to evaluate and analyse the state of the cutting edge. Due to the unexpectedly edge random deformation modes, the dependence on only cutting parameters is insufficient strategy to in-process monitor and/or control policies recently required in adaptive control systems. One approach is to relate the immeasurable process symptoms (wear and deformation) to measurable parameters. Cutting force variations may represent smart and credible information carrier about the instantaneous state of the cutting edge. The challenge, however, is to approach a versatile technique that is universal and material properties independent. The current study is just a step forward toward that direction.

5 Empirical force-wear models considering edge, rubbing and ploughing force elements

As indicated by equations (10) and (11), the overall cutting forces can be attributed to three independent fundamental elements each of which have its own individual source and features. The first depends on cutting configuration and work material properties; the second (edge force) depends on edge configuration and specific cutting pressure while the third represents the extra wear influence imposed on the process. The first two elements may be combined to represent a wear-independent force component Fwi that may be expressed as:

. .( . ) [ ]wi o c oF a ap f N= =β β (12)

βo is the cut coefficient that depends on specific cutting pressure (N/mm2), ac is the cut area (mm2), ap is the depth of cut (mm) and f is the feed (mm/rev). As wear propagates on the flank face, an additional rubbing and ploughing force component Frp evolves:

( )1 1. . . .cot [ ],rp c i r iF b VB ap κ VB N= =β β (13)

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β1 is the wear land intensity coefficients per unit wear land area, bc is the cut width, κr is the approach angle, and VBi is the wear land height. Combining equations (12) and (13) yields the total force model for the worn edge Fi:

( )1( . ) .cot . [ ]i VBi rp o r iF F F ap f ap κ VB N= + = +β β (14)

( ) . [ ]i o c j jF a ap VB N= + ∑β β (15)

where suffix i refers to the type of force component: main Ft, feed (axial) Fa, radial Fr or thrust Far force components while suffix j that refers to the type and the mode of the edge wear: nose wear VBC, flank wear VBBmax and notch wear VBN. The natural form of equation (15) takes the form:

( ) ( ) ( ) ( )1 2 3. . max .i o c C B NF a apVB apVB apVB= + + +β β β β (16)

Mathematical models were established using the experimental data according to model (16). Multiple regression procedures are used to estimate the equations’ coefficients (predictors) β’s. Results of all possible models structures along with their statistical and significance measures are as follows:

5.1 Main (tangential) cutting force component Ft

( ) ( ) ( ) ( )2,178.13 ( ) 177.16 261.02 max 269.18t c C B NF a ap VB VB VB⎡ ⎤= + + +⎣ ⎦ (17a)

( ) ( ) ( )2,186.03 ( ) 227.42 459.0 maxc C Ba ap VB VB⎡ ⎤= + +⎣ ⎦ (17b)

( ) ( ) ( )[ ]2,193.95 ( ) 263.81 407.87c C Na ap VB VB= + + (17c)

( ) ( ) ( )2,187.18 ( ) 405.95 max 327.84 c B Na ap VB VB⎡ ⎤= + +⎣ ⎦ (17d)

( ) ( )[ ]2,243.44 ( ) 550.3c Ca ap VB= + (17e)

( ) ( )2,200.71 ( ) 715.50 maxc Ba ap VB⎡ ⎤= + ⎣ ⎦ (17f)

( ) ( )[ ]2,230.20 ( ) 683.7c Na ap VB= + (17g)

Models set (17) indicate the all-possible force-wear interrelationships using multiple regression analysis using ‘ENTER’ technique where the required parameters are forced into the final model. The adequacy and the significance are examined throughout many statistical criteria as indicated in Table 3. These include the adjusted correlation factor Adj. R2, the F_ratio and the standard error of estimate SE in addition to the partial standard error and the corresponding t_value for the individual coefficients. All statistical criteria confirm the significance and the adequacy of all models. Models coefficients indicate that the main cutting force Ft is affected, to different extents, by the various wear modes with the highest impact of the flank wear VBB while it is least affected by the nose wear VBC. This is further examined with STEPWISE regression routine, which uses some statistical measures to specify the merit and the priority of each variable to include in the final model. According to ‘stepwise’ routine, all wear modes deserved the inclusion in the final model (17a) with the significance inclusion sequence: the flank wear followed


by the notch wear and finally the nose wear. This is supported by the statistical criteria for individual models (17e) to (17g). However, all models indicate that the main force component Ft, as a power rather frictional component, is strongly associated to the shearing process which, is represented by the cut area ac. Table 3 Statistical criteria and measures for models of main force component

Model statistical criteria Partial predictors t_value(3) Model no. Adj. R2(1) F_ratio(2) Model (SE)

t_βo t_β1 t_β2 t_β3 (17a)(4) 99.5% 35,564 85.10 154.0 6.92 6.50 7.85 (17b) 99.5% 43,374 88.95 148.6 8.75 13.94 - (17c) 99.5% 44,615 87.71 153.0 11.7 - 14.8 (17d) 99.5% 44,228 88.10 150.0 - 11.4 9.53 (17e) 99.4% 50,143 101.0 139.6 40.9 - - (17f) 99.4% 58,295 93.94 142.6 - 45.0 - (17g) 99.4% 55,414 96.34 145.3 - - 43.8

Notes: (1)Adj. R2 = [1 – (Residuals Sum Squares / Total Sum Squares)] (2)F_ratio = [Regression Mean Squares / Residuals Mean Squares] (3)t_value = [Predictor Value / Predictor Standard Error] (4)STEPWISE estimation for Ft.

The Ft-wear relations may be simplified, without affecting their predictability by using the average wear VBav as the arithmetic mean of the three wear modes.

Additionally, the notch wear mode VBN is observed to have the least influential impact on the cutting force and is thought to use the average wear considering only the nose and the flank wear.

( ) ( )1

2

2,179 649.923 .

99.5%, 85.65, 70,185, 160, 51o

t c avF a apVB

R SE F t t

= +

= = = = =⎡ ⎤⎣ ⎦β β (18)

( ) ( )1

max

2

2,192.51 657.67 .

99.5%, 92, 60,782, 152.5, 46.5C B

o

t c av VB VBF a apVB

R SE F t t− −= +

= = = = =⎡ ⎤⎣ ⎦β β (19)

5.2 Feed (axial) force component Fa

Models set (20) represent the estimation procedures for the feed force component Fa. Stepwise procedures, model (20c), indicate that the nose wear VBC is the most influential factor with better statistical criteria and measures, Table 4.

( ) ( ) ( ) ( )338.3 ( ) 739.76 0.672 max 82.11a c C B NF a ap VB VB VB⎡ ⎤= + − +⎣ ⎦ (20a)

( ) ( ) ( )341.24 ( ) 754.95 59.72 maxc C Ba ap VB VB⎡ ⎤= + +⎣ ⎦ (20b)

( ) ( ) ( )[ ]338.79 ( ) 739.54 81.75c C Na ap VB VB= + + (20c)

( ) ( ) ( )376.50 ( ) 602.98 max 326.43c B Na ap VB VB⎡ ⎤= + +⎣ ⎦ (20d)

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( ) ( )[ ]348.71 ( ) 796.96c Na ap VB= + (20e)

( ) ( )389.98 ( ) 911.20 maxc Ba ap VB⎡ ⎤= + ⎣ ⎦ (20f)

( ) ( )[ ]440.410 ( ) 855.01c Na ap VB= + (20g)

Table 4 Statistical criteria and measures for models of feed force component

Model statistical criteria Partial predictors SE and t_value Model no. Adj. R2 F_ratio Model (SE)

t_βo t_β1 t_β2 t_β3 (20a) 95.1% 3,157 127.5 16.0 19.0 –.011 1.6 (20b) 95.1% 4,198 127.6 16.2 20.2 1.26 - (20c)(1) 95.1% 4,216 127.4 16.3 22.5 - 2.04 (20d) 92.3% 2,610 159.5 14.3 - 9.33 5.24 (20e) 95.1% 6,290 127.7 17.2 47.0 - - (20f) 92.0% 3,751 162.7 14.6 - 33.3 - (20g) 91.3% 3,422 169.6 16.3 - - 31.1

Note: (1)Stepwise estimation for Ft.

Models considering the average wear; either VBav or max ,C Bav VB VBVB − − are as follows:

( ) ( )1

2

326.87 925.85 .

93.0%, 151.7, 4,360, 15.8, 37o

a c avF a apVB

R SE F t t

= +

= = = = =⎡ ⎤⎣ ⎦β β (21)

( ) ( )1

max

2

321.78 900.996 .

93.2%, 149.6, 4, 492, 16.6, 37.8C B

o

a c av VB VBF a apVB

R SE F t t− −= +

= = = = =⎡ ⎤⎣ ⎦β β (22)

5.3 Radial force component Fr

Models (31) to (37) represent the estimation procedures for the radial force component Fr with statistical measures listed in Table 5. Stepwise procedures, model (23), indicate that the radial force is affected by all wear elements. Data show an opposite action for each of the flank and the notch wear modes to that imposed by the nose wear VBC.

( ) ( ) ( ) ( )300.88 ( ) 1,082.19 142.25 max 166.79r c C B NF a ap VB VB VB⎡ ⎤= + − +⎣ ⎦ (23a)

( ) ( ) ( )295.99 ( ) 1,051.34 264.93 maxc C Ba ap VB VB⎡ ⎤= + +⎣ ⎦ (23b)

( ) ( ) ( )[ ]292.26 ( ) 1,035.22 242.37c C Na ap VB VB= + + (23c)

( ) ( ) ( )356.00 ( ) 740.83 max 190.64c B Na ap VB VB⎡ ⎤= + +⎣ ⎦ (23d)

( ) ( )[ ]262.86 ( ) 864.98c Ca ap VB= + (23e)

( ) ( )363.87 ( ) 920.38 maxc Ba ap VB⎡ ⎤= + ⎣ ⎦ (23f)


( ) ( )[ ]434.52 ( ) 840.05c Na ap VB= + (23g)

Table 5 Statistical criteria and measures for models of radial force component


t_βo t_β1 t_β2 t_β3 (23a)(1) 93.3% 2,272 150.8 12.0 23.8 -2.0 -2.7 (23b) 93.2% 2,998 151.6 11.8 23.7 -4.72 - (23c) 93.3% 3,015 151.2 11.8 26.6 - -5.1 (23d) 87.5% 1,524 206.0 10.5 - 8.9 2.4 (23e) 93.0% 4,345 154.0 10.7 42.3 - - (23f) 87.4% 2,268 206.8 10.7 - 26.5 - (23g) 86.0% 2,008 217.9 12.5 - - 23.8

Note: (1)Stepwise estimation for Fr.

Models considering the average wear are as follows:

( ) ( )1

2

281.833 956.388 .

90.5%, 179, 3,130, 10.7, 33.9o

r c avF a apVB

R SE F t t

= +

= = = = =⎡ ⎤⎣ ⎦β β (24)

( ) ( )max

2

259.158 949.849 .

91.4%, 170.4, 3,493, 11.1, 36.6C B

o t

r c av VB VBF a apVB

R SE F t t− −= +

= = = = =⎡ ⎤⎣ ⎦β β (25)

5.4 Thrust force component Far

As shown in Figure 1, the thrust force Far is the component normal to the cutting edge and, is considered as the resultant of the feed and the radial components. Models (26) indicate the global and the individual influence of wear modes on the thrust force variation with statistical criteria listed in Table 6. Model (26b) is selected by the stepwise procedures with only the nose and the flank wear modes to enter into the final equation.

( ) ( ) ( ) ( )451.80 ( ) 1,310.95 112.62 max 70.21ar c C B NF a ap VB VB VB⎡ ⎤= + − −⎣ ⎦ (26a)

( ) ( ) ( )449.74 ( ) 1,297.96 164.26 maxc C Ba ap VB VB⎡ ⎤= + −⎣ ⎦ (26b)

( ) ( ) ( )[ ]444.97 ( ) 1, 273.76 130.05c C Na ap VB VB= + − (26c)

( ) ( ) ( )518.56 ( ) 957.13 max 362.77c B Na ap VB VB⎡ ⎤= + +⎣ ⎦ (26d)

( ) ( )[ ]429.19 ( ) 1,182.42c Ca ap VB= + (26e)

( ) ( )533.54 ( ) 1, 299.66 maxc Ba ap VB⎡ ⎤= + ⎣ ⎦ (26f)

( ) ( )[ ]620.01 ( ) 1,201.8c Na ap VB= + (26g)

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Table 6 Statistical criteria and measures for models of thrust force component


t_βo t_β1 t_β2 t_β3 (26a) 94.6% 2,873 189.8 14.4 23.9 –1.25 –0.92 (26b)(1) 94.6% 3,832 189.77 14.3 23.4 –2.33 - (26c) 94.6% 3,827 189.87 14.4 26.0 - –2.2 (26d) 90.3% 2,030 254.70 12.3 - 9.3 3.6 (26e) 94.6% 5,706 190.42 14.2 46.7 - - (26f) 90.1% 2,983 257.00 12.6 - 30.0 - (26g) 89.0% 2,657 270.73 14.4 - - 27.4

Note: (1)Stepwise estimation for Ftr.

Models considering the average wear are as follows:

( ) ( )1

2

429.331 1,336.69 .

92.3%, 227, 3,915, 13.4, 36.6o

ar c avF a apVB

R SE F t t

= +

= = = = =⎡ ⎤⎣ ⎦β β (27)

( ) ( )1

max

2

408.82 1,315.269 .

92.9%, 218.4, 4, 251, 14, 38.7C B

o

ar c av VB VBF a apVB

R SE F t t− −= +

= = = = =⎡ ⎤⎣ ⎦β β (28)

The developed models present qualitative and quantitative evaluation of the wear-force interrelations. This is a necessity in any computerised monitoring and/or control of the machining process especially the assessment of the tool performance. In addition to that, the models are used to analyse and evaluate many of the cutting quantities. In the following sections, two different, but technically related, topics are discussed: the specific cutting pressure and the friction at the tool-workpiece interface.

6 Effect of edge wear on the specific cutting pressure

Performance of the machining process and the quality of the machined surface are largely dependent on the geometrical stability of the cutting edge. This, to great extent, is influenced by the continuous variation of the cutting force and temperature. The specific cutting pressure or, the nominal cutting stress gives a direct indication of the state of the tool wedge. It is defined as the main cutting force, Ft, divided by the cross section area of the undeformed chip. For sharp edge, the specific cutting pressure depends on the cutting parameters specially cutting speed (Thakur et al., 2009). The specific cutting pressure is affected as wear increases on the cutting edge:

( ) 1 2 max 3. . .C B Nt o c VB VB VBF a a a a= + + +β β β β (29)

In which βo is the nominal specific cutting pressure (stress) due to shearing process (rubbing and ploughing actions) while β1, β2 and β3 represent the individual added pressure due to nose wear, flank wear and notch wear elements respectively. Accordingly, the instantaneous state of the specific pressure β can be represented as:


( ) ( ) ( ) ( ) ( )1 2 3max. . ..

t t C NBoc

F F VB VBVBa ap f f f f= = = + + +β β β β β (30)

Equation (30) explains that the extra pressure imposed on the process depends mainly on the wear land-feed ratio. This ratio introduces a controlling variable of the process to indicate that more pressure is expected as wear land height exceeds the employed cutting feed.

The individual impact of each wear mode on the specific pressure is explained in the light of the wear-time-force experimental results of test #16 which are earlier presented by Figure 6. The cutting edge attained a low gradual wear rate along with random chipping, fracture at both the tool-chip and tool-workpiece interfaces. Due to the sudden nose deformation from 0.218 to 0.284 mm (≈30%), Figure 6(a), a corresponding increase in the pressure from 4,133 to 5,192 N/mm2 (≈26%) was resulted. As indicated by Figure 14, the initiation of edge nose deformation is very well detected as the pressure increases reaching a high value at wear level of 0.226 mm after which it remains constant retaining most of its rise gain. At later stage, the tool edge experienced chipping and fracture at both the flank and the notch areas with almost constant level of nose wear VBC, Figure 6. This has led to a sudden increase of about (10%) in the value of specific pressure, Figure 14, revealing that only 20% pressure increase should be attributed to the effect of the nose wear. Again, both flank and notch disturbances are well detected by the increase in the specific pressure, Figure 14. However, it is observed that the onset of all deformation modes occurred at an almost similar wear-feed factor of about (4).

Figure 14 Experimental data for specific pressure-wear-feed for test #16 (see online version for colours)

In test #3, where a low feed of 0.12 mm/rev is used in association with high values of cutting speed and depth of cut of 145 m/min and 2.5 mm respectively. As shown in Figure 12, an early edge fracture at the notch zone occurred, Figure 12(a). At later stages, however, a sudden high edge wear rate occurred at the nose area that eventually led to the edge failure, Figure 12(b). As show by Figure 15, the early notch deformation increased the specific pressure by about 6% and then kept constant until it was strongly invoked by

336 S.E. Oraby

the sudden increase at the edge nose at the end of the test. Although the early notch disturbance is detected, Figure 15, the overwhelming increase in the pressure of about 20% at the end support the existence of a strong impact of the edge nose deformation mode. While the wear-feed ratio at ultimate edge nose fracture was found to be around the value (3.5), a less values were observed considering the notch and flank modes, Figure 15.



As shown by Figure 4, a moderate speed-feed-depth combination was employed in test #12 where an almost equal gradual wear level developed over all edge zones except for an early random fracture occurred on the notch area. At the end of the test, wear levels were insignificant enough to produce a noticeable increase in either of the pressure


or the wear-feed ratio. Nevertheless, the early notch fracture was noticed to increase the specific pressure by about 8%, Figure 16.

As indicated in Figure 5, a catastrophic failure due to the use of high cutting speed occurred at the nose area without affecting any of the flank or the notch edge zones. As shown in Figure 17, an increase of about 24% in the specific pressure as a result of attaining a wear-feed ratio of about 4.9, 1.2 and 1.2 for nose, flank and notch wear modes respectively.


Experimental results for test #4, Figure 13, give additional evidence that the wear domination along the nose area, including the partial extension along the secondary cutting edge, may have the most impact on the specific cutting pressure. It is observed that, Figure 18, about 27% increase in the specific pressure corresponds to a wear-feed ratio of 2.33, 0.65 and 0.65 for nose, flank and notch wear level respectively.


338 S.E. Oraby

Non-linear regression procedures using the entire experimental data have led to relate the specific cutting pressure to all constituents as:

( ) ( ) ( )0.345 0.332 0.1141,991.003 950.406 maxC B Nβ VB f VB f VB f= + (31)

Nose wear-feed ratio indicates a slight bigger impact on the specific cutting pressure than that of the flank wear-feed ratio while the notch wear-feed ratio showed the least influence. During machining, the machined work surface is plastically recovered (Astakhov, 2006) imposing an extra frictional pressure on the cutting edge. To reduce computational complication without affecting modelling accuracy, the average wear, as the mean value of the three edge wear modes, may be used in the form:

( )0.8282,037.5 904.63 avVB f= +β (32)

Figure 19 Response surface and contours of the specific pressure-feed-average wear (see online version for colours)


In Figure 19, the response surface pressure-wear-feed interrelation is illustrated in both three-dimensional and surface contours graphs. The response surface shows three distinguished functional regions considering the wear-feed ratio (VBav / f). The customised practical domain may be determined as (VBav / f) ≥ 1. At this technically feasible region, the cutting parameters, which are represented by feed and depth of cut, may be optimised according to a certain objective function and operational constraints. Lower values of cutting feed usually are accompanied by higher levels of specific cutting pressure especially at elevated wear values. Additionally, for a criterion wear level, the metal removal rate (productivity) and the specific pressure can be enhanced through increasing the cutting feed. At the other side, for a given feed value, increasing pressure through decreasing depth of cut may lead to higher wear scars especially at the nose area. This information may be exploited in any proposed adaptive control strategy to increase productivity of a rough turning operation using the measured cutting forces as an indirect way to assess, monitor and/or control tool wear (Liang et al., 2004).

7 Conclusions

The wear and deformation on the cutting edge is the result of a complex mechanical-thermal-chemical process involved in metal cutting. The edge deformation is usually developed in different modes each of them is attributed to one or more of the aforementioned, usually correlated causes. It has long been accepted to use the cutting parameters in machining (speed-feed-depth of cut) as a prior input to design and optimise the machining process, and to prior judge the state of the cutting edge and its performance. Although the cutting parameters may produce a general vision of the relationship between the deformation causes and its symptoms, the functional interaction among these parameters makes it even more difficult to determine the individual influence of a parameter in isolation of the effect of the others. For instance, the effect of the cutting feed on the emerged edge wear and deformation should be evaluated taking the level of the employed cutting speed as a cutting heat generation prime factor into consideration. Also, the effect of the cutting speed, as an input parameter, should be judged considering the expected process variations as cutting continues.

The experimental results indicated that the common edge failure takes place over region of the edge that surrounds the edge nose initiated at the primary edge and extends to the secondary cutting edge. This was basically due to the thermal softening of the cutting wedge as a result of the high temperatures and pressure in the tool-chip and tool-workpiece interfaces. This affected the frictional force components especially the radial component. The tangential force, as a power component, was the least affected by the edge wear and deformation. Random wear disturbances were found to have a localised influence and sometimes changed the radial-to-axial force ratio.

Robust non-linear mathematical models were established to isolate the effect of different wear and deformation modes on the cutting force components. Most the aforementioned experimental findings were grasped by the developed models. Also, wear-feed ratio was mathematically related to the cutting pressure producing a good measure to determine the onset of edge failure as well as other random wear types.

340 S.E. Oraby

Acknowledgements

The author would like to thank the Public Authority for Applied Education and Training PAAET, KUWAIT for supporting this study under the research support agreement: TS-11-11.

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