Astakhov V. Tribology of Metal Cutting

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Cutting Tool Wear, Tool Life and Cutting Tool Physical Resource 267

a = 5° a = 25°

10° 15° 20°

30 60 90 120 150

(mm)

Fig. 4.36. Shapes of the tool ﬂank surface for different ﬂank angles. Turning, work material –

steel AISI 1045, tool material M10 (92% WC, 8% Co), Cutting regime: cutting speed ν = 2.4 m/s,

feed f = 0.4 mm/rev, depth of cut d

= 2 mm. Magniﬁcation along the vertical axis × 40, along

the horizontal axis ×1000.

g = +10° g = +10° g = +10°

= −10°g

= −5°

= 0.18 f

= 0.18

11 122

10 20 30

250

(µm)

500

750

Fig. 4.37. Shapes of the tool ﬂank surface for different conﬁgurations of the rake surface.

Curve 1 – cutting time τ = 10 s, 2 – τ = 30 s, 3 – τ = 60 s. Turning, work material – steel AISI

1045, tool material P20 (79% WC, 15% TiC, 6% Co), cutting regime: cutting speed ν = 3.3 m/s,

feed f = 0.4 mm/rev and depth of cut d

= 2 mm.

268 Tribology of Metal Cutting

0 (mm)

= 0

= 0.5 mm

30 40 50 60

(mm)

Fig. 4.38. Plastic lowering of the tool point. Turning, work material – steel AISI 1045, tool

material P20 (79% WC, 15% TiC, 6% Co), Cutting regime: cutting speed ν = 3.3 m/s, feed

f = 0.4 mm/rev, depth of cut d

= 2 mm. Magniﬁcation along the vertical axis ×40, along the

horizontal axis ×1000.

This is an important conclusion since this point forms the diameter of the part being

machined.

The inﬂuence of the tool material on plastic lowering of the cutting edge can be

summarized as follows:

• The intensity of plastic lowering reduces when the cobalt matrix of a carbide tool

material is made harder by alloying it with tungsten. The smaller the percentage

of carbon in carbide, the higher the solubility of tungsten in cobalt, and lower the

plastic lowering.

• The intensity of plastic lowering increases with the decrease in the thermoconduc-

tivity of the tool material. It can be attributed to the changes in the tool–chip contact

length (discussed in Chapter 3) and to the shift of the regions of higher temperature

of the cutting wedge closer to the cutting edge.

• The intensity of plastic lowering in carbide tool materials increases with higher

cobalt content.

• The intensity of plastic lowering increases with the increase in the size of carbide

grains that relates to increasing the cobalt spacing between grains and reduction of

thermoconductivity.

When plastic lowering occurs, it changes the rake and ﬂank cutting tool angles that

leads to further increase in the tool wear rate. Chipping and then breakage of the cut-

ting wedge occur at the ﬁnal stage of creep. To slow down high temperature creep,

Cutting Tool Wear, Tool Life and Cutting Tool Physical Resource 269

the cutting edge, when it is possible, should be ground with radius or a small chamfer

(land) and a zero ﬂank angle should be ground on the tool ﬂank surface, the ﬂank angle

should be as small as possible. Cutting edge preparation, including honing the rake

and ﬂank surface adjacent to the cutting edge, is proven to be very useful in machining

difﬁcult-to-machine materials. Proper edge geometry affects tool performance in two spe-

ciﬁc ways. First, it heavily inﬂuences tool reliability. Properly honed tools can improve

the repeatability of machining operations. Second, proper edge preparations improve

tool life by reducing the common causes of failure, such as chipping and heat-induced

failures. Tool end users can realize dramatic cost reductions and productivity improve-

ments by applying state-of-the-art edge preparation to cutting tools, whether the tools

are a manufacturer’s generic line or an end-user’s speciﬁc tooling. The return on invest-

ment for proper edge preparation services is quite high for both new and reground

cutting tools.

4.9 Resource of the Cutting Wedge

As discussed in Chapter 2, the energy ﬂows to the zone of the fracture of the layer being

removed through the cutting wedge (deﬁned as a part of the tool located between the rake

and the ﬂank contact areas). Out of three components of the cutting system, namely, the

cutting tool, the chip and the workpiece, the only component that has an invariable mass

of material and which is continuously loaded during the cutting process, is the cutting

wedge. As such, the overall amount of energy, which can be transmitted through this

wedge before it fails, is entirely determined by the physical and mechanical properties

of the tool material.

On the contrary, the material of the chip is not subjected to the same external force

because the chip is an ever growing component, i.e. a new section is added to the chip

during each cycle of chip formation while “old” sections move out of the tool–chip

interface and thus do not experience the external load. The same can be said about the

workpiece whose volume and thus mass changes during the cutting process as well as

the area of load application imposed by the cutting tool.

When the cutting wedge loses its cutting ability due to wear or plastic lowering of the

cutting edge (creep), the work done by the external forces that causes such a failure is

regarded as the critical work. As was established by Huq and Celis, a direct correlation

exists between wear and the dissipated energy in sliding contacts [27], so for a given

cutting wedge, this work (or energy) is a constant value. The resource of the cutting

wedge, therefore, can be represented by this critical work.

According to the principle of physical theory of reliability [19], each component of

a system initially has its resource and this resource is spent during operation time

at a certain rate depending on the operating conditions. This principle is valid for a

wide variety of operating conditions, provided changes from one operating regime to

another do not lead to any structural changes in material properties (reaching the critical

temperatures, limiting loads, chemical transformations, etc.). As such, the resource of a

cutting tool, r

can be considered as a constant, which does not depend on a particular

270 Tribology of Metal Cutting

way of its consumption, i.e.



(

τ, R

)

dτ =



(

τ, R

)

dτ, (4.29)

where τ

and τ

are the total operating times on the operating regime R

and R

respectively, till the resource of the cutting tool is exhausted.

The initial resource of the cutting tool can be represented by the above discussed critical

energy and the ﬂow of energy through the cutting tool exhausts this resource. The amount

of energy that ﬂows through the cutting tool depends on the energy to separate the layer

being removed, which, in turn, deﬁnes the total energy U

required by the cutting system

to exist (Chapter 2). Therefore, there should be a strong correlation between a parameter

(or metric) characterizing the resource of the cutting tool (for example, ﬂank wear VB

)

and the total energy U

To demonstrate the validity of the discussed principle, a series of cutting tests (bar

longitudinal turning) were carried out. The work material was steel AISI 52100: chemical

composition – 0.95% C, 1.5% Cr, 0.35% Mn, 0.25% Si; tensile strength, ultimate –

689 MPa, tensile strength, yield – 558 MPA, annealed at 780

◦

C to hardness 192 HB.

Cutting tool material – carbide P10 (cutting inserts SNMG 12 04 08).

The experimental results are shown in Table 4.8. It follows from this table that there is

a very strong correlation between the total work required by the cutting system and the

ﬂank wear. This correlation does not depend on a particular cutting regime, cutting time

and other parameters of the cutting process. Figure 4.39 shows the correlation curve [26].

The discovered correlation between the energy passed through the cutting wedge and

its wear can be used for the prediction of tool life and optimal cutting speed allowing

the avoidance of expensive and time-consuming tool life tests. Moreover, the multiple

experimental results, obtained in machining of different work materials using different

cutting tools, proved that this correlation holds regardless of the particular manner the

resource of the tool was spent.

The essence of the method can be described as follows:

The energy required by the cutting system during the time period corresponding to tool

life T

can be represented as

= W

, (4.30)

where W

is power required by the cutting system (W).

Note that U

, when selected for a given tool material using the correlation curve similar

to that given in Fig. 4.39 for the accepted tool life criterion, is the sole characteristic

of the tool material, i.e. its resource can be used for calculating the tool life in cutting

different work materials.

Cutting Tool Wear, Tool Life and Cutting Tool Physical Resource 271

Table 4.8. Conditions of tests and experimental results.

Test Feed Depth of cut Operating time Flank wear (VB

) Energy of the

number (mm/rev) (mm) (s) (mm) cutting system (kJ)

1 0.07 0.1 8540 0.45 0.88

2 0.07 0.1 6680 0.41 0.63

3 0.07 0.1 4980 0.39 0.52

4 0.07 0.1 1640 0.29 0.25

5 0.07 0.1 9120 0.45 0.91

6 0.07 0.1 7660 0.42 0.68

7 0.07 0.1 6260 0.41 0.55

8 0.07 0.1 4900 0.37 0.41

9 0.07 0.1 3450 0.35 0.47

10 0.07 0.1 5380 0.38 0.65

11 0.07 0.1 4240 0.34 0.35

12 0.07 0.1 3150 0.30 0.33

13 0.07 0.1 2075 0.26 0.24

14 0.07 0.1 1036 0.20 0.15

15 0.07 0.1 2980 0.37 0.37

16 0.07 0.1 1940 0.32 0.30

17 0.07 0.1 1190 0.27 0.17

18 0.09 0.1 938 0.15 0.05

19 0.09 0.1 1874 0.18 0.10

20 0.09 0.1 2840 0.22 0.22

21 0.09 0.1 3820 0.25 0.17

22 0.09 0.1 4810 0.31 0.39

23 0.12 0.1 775 0.20 0.08

24 0.12 0.1 1520 0.23 0.18

25 0.12 0.1 2350 0.26 0.29

26 0.12 0.1 3220 0.27 0.30

27 0.14 0.1 675 0.20 0.18

28 0.14 0.1 1315 0.21 0.12

29 0.07 0.2 1295 0.21 0.13

30 0.07 0.2 2610 0.27 0.30

31 0.07 0.2 5420 0.44 0.82

32 0.07 0.8 1316 0.20 0.19

0.1

2468

×10

−5

(J)

(mm)

0.2

0.3

0.4

Fig. 4.39. Correlation curve (after Astakhov [25]).

272 Tribology of Metal Cutting

The power of the cutting system (W

) is determined as a product of the power component

of the cutting force (F

) and the cutting speed (ν), i.e.

= F

ν (4.31)

In turn, the cutting force F

can be determined experimentally depending upon the cutting

parameters as,

= C

, (4.32)

where C

is a constant of the work material and n

and k

are the exponents.

Substituting Eqs. (4.31) and (4.32) into Eq. (4.30) and expressing tool life, one can obtain

an equation which determines tool life for a given cutting regime.

. (4.33)

If it is necessary to know the cutting speed corresponding to the desired tool life, then

Eq. (4.33) can be expressed as,

ν =





(4.34)

It is obvious that U

selected depending on the tool ﬂank wear depends not only on the

properties of the tool material but also on the tool geometry. Therefore, the correlation

curve U

= f(VB) should be corrected accounting for the particular tool geometry. As a

result, there are countless number of possible combinations “cutting-tool material-tool

geometry” to account for the inﬂuence of the tool geometry. To avoid the consideration

of the inﬂuence of tool geometry, the volumetric or mass tool wear (m

) Eq. (4.2) can

be used instead of VB

The results of foregoing analysis suggest that the most prospective way to achieve

repeatability of cutting tool with inserts is the certiﬁcation of cutting inserts of stan-

dard shapes. The number of standard shapes of cutting inserts (including their geometry)

is relatively small so that each insert producer should be able to provide a correlation

curve U = f

(

)

for each shape and tool material. Table 4.9 presents some correlations

for different tool materials and for different shapes of cutting inserts obtained experi-

mentally using basic groups of the work material (low-, medium- and high-carbon steels,

low and high alloys including chromium- and nickel-based, titanium alloys). It has been

proven that the obtained correlation curves do not depend on the particular work mate-

rial, machine or any other cutting conditions, so they are properties of the considered

tool materials.

The correlations in Table 4.9 were obtained for VB

≤ 0.4 mm. The data presented in

Table 4.9 are valid under the condition that the tool material does not lose its cutting

Cutting Tool Wear, Tool Life and Cutting Tool Physical Resource 273

Table 4.9. Correlation curves for some tool materials.

Tool material ISO code of the shape Correlation curve Critical

temperature (

◦

TS332 (99% Al

1% MgO–2300HV)

SNMN 120404M U = exp



9.6 VB



1200

VOK60 (60% Al

40% TiC 94 HRA)

SNMN 120404M U = exp



10.91 VB



1200

Silinit-P (Si

, 96 HRA)

SNMN 120404M U = 573VB

1200

TN20 (75% TiC,

15% Ni, 10% Co,

90 HRA)

SNMN 120404M U = 434.46 ×10

−3

780

Kiborit (96% CBN,

KNH 32–36GPa)

RNMM1200404M U = 50 VB

1400

properties due to excessive temperature. For example, the data for Silinit–P is valid

if the cutting temperature does not exceed that in the cutting of steel with feed

f = 0.07 mm/rev, depth of cut d

= 0.1 mm and cutting speed ν = 3.3m/s. If the

cutting speed is increased to ν = 4m/s, this material loses its cutting ability hence the

correlation curve presented in Table 4.9 is no longer valid.

It has to be pointed out that the limiting work is a complex integral index of the cutting

tool resource and intensity of its “spending.” This work is not the same for two geo-

metrically alike cutting inserts made of different tool materials as their application for

the same work material at the same machining regime results in different works of chip

formation deﬁned by the chip compression ratio (Chapter 2). It is explained by different

contact processes at the tool–chip and tool–workpiece interfaces. As a result, tool lives

for the inserts with close relationships U

= f(VB

) (Fig. 4.39) but made of different

tool materials may not be the same or even close.

The foregoing analysis suggests that using the established correlation U

= f(VB

it is possible to choose the limiting tool wear and then using this selected value to

calculate the limiting work. Using this limiting work, one can calculate tool life under a

given cutting regime or the cutting speed for the desirable tool life using the following

steps:

Calculation of tool life

• Select the maximum allowed tool wear (VB).

• Using correlation formulas similar to that shown in Table 4.9, calculate the limiting

work.

• Conduct a short cutting test for the chosen cutting regime to determine the cutting

force P

and the maximum cutting temperature.

• Calculate tool life as T = U/

(

)

. If the accuracy of the cutting force determination

is insufﬁcient, then the cutting energy can be determined using the chip compression

ratio (see Chapter 2) or direct measurements of the power of the driving motor.

274 Tribology of Metal Cutting

• Compare the maximum cutting temperature obtained from the test and the limiting

temperature for the selected tool material to assure that the former is lower than the

latter.

Calculation of the cutting speed for a given tool life

• Choose the critical wear (VB

) and the desired tool life (T ).

• Using correlation formulas similar to that shown in Table 4.9, calculate the limiting

work.

• Conduct a short cutting test establishing correlations P

= C

and θ = f

(

)

• Calculate the cutting speed as ν =





T × C



• Compare the maximum cutting temperature obtained from θ = f

(

)

and the limiting

temperature for the selected tool material to assure that the former is lower than

the latter.

In the author’s opinion, new reference books on cutting tool, cutting inserts and tool

materials issued and published by The National Institute of Standards and Technology

and by ISO should contain similar tables to help end users to make meaningful selection

of the cutting tool and tool materials for speciﬁc applications.

References

[1] Schey, J.A., Tribology in Metalworking, American Society for Metals, Metals Park,

Ohio, 1983.

[2] Olson, M., Stridh, B., Söderberg S., Sliding wear of hard materials – the importance of a

fresh countermaterial surface, Wear, 124 (1988), 195–216.

[3] Stephenson, D.A., Agapiou, J.S., Metal Cutting Theory and Practice, Marcel Dekker,

New York, 1996.

[4] Trent, E.M., Wright, P.K., Metal Cutting, Butterworth-Heinemann, Boston, 2000.

[5] Childs, T.H.C., Maekawa, K., Obikawa, T., Yamane, Y., Metal Machining. Theory and

Application, Arnold, London, 2000.

[6] Jawahir, I.S., Van Luttervelt, C.A., Recent developments in chip control research and

applications, Annals of the CIRP, 42 (1993), 659–693.

[7] Loladze, T.N., Strength and Wear of Cutting Tools (in Russian), Mashgiz, Moscow, 1958.

[8] Gordon, M.B., The applicability of binomial law to the process of friction in the cutting of

metals, Wear, 10 (1967), 274–290.

[9] Usui, E., Shirakashi, T., Mechanics of metal cutting – from “description” to “predictive”

theory. In On the Art of Cutting Metals – 75 Years Later, Vol. 7, Production Engineering

Division (PED), ASME, Phoenix, USA, 1982, pp. 13–15.

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and future trends in modelling of machining operations. Progress report of the CIRP Working

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[11] Shuster, L.S.H., Adhesion Processes at the Tool-Work Material Interface (in Russian),

Moscow, Machinostroenie, 1988.

[12] Marinov, V., Experimental study on the abrasive wear in metal cutting, Wear, 197 (1996),

242–247.

[13] Taylor, F.W., On the art of cutting metals, Transactions of ASME, 28 (1907), 70-350.

[14] Makarow, A.D., Optimization of Cutting Processes (in Russian), Machinostroenie, Moscow,

1976.

[15] Granovsky, G.E., Granovsky, V.G., Metal Cutting (in Russian), Vishaya Shkola, Moscow,

1985.

[16] Astakhov, V.P., Metal Cutting Mechanics, CRC Press, Boca Raton, USA, 1998.

[17] Astakhov, V.P., The assessment of cutting tool wear, International Journal of Machine Tools

and Manufacture, 44 (2004), 637–647.

[18] Atkins, A.G., Mai, Y.W., Elastic and Plastic Fracture: Metals, Polymers. Ceramics,

Composites, Biological Materials, John Wiley & Sons, New York, 1985.

[19] Komarovsky, A.A., Astakhov, V.P., Physics of Strength and Fracture Control: Fundamentals

of the Adaptation of Engineering Materials and Structures, CRC Press, Boca Raton, 2002.

[20] Zorev, N.N., Metal Cutting Mechanics, Pergamon Press, Oxford, 1966.

[21] Silin, S.S., Similarity Methods in Metal Cutting (in Russian), Moscow, Machinostroenie,

1979.

[22] Kronenberg, M., Machining Science and Application. Theory and Practice for Operation and

Development of Machining Processes, Pergamon Press, Oxford, 1966.

[23] Gorczyca, F.Y., Application of Metal Cutting Theory, Industrial Press, New York, 1987.

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Russian), Machinostroenie, Moscow, 1992.

[25] Astakhov, V.P., Outeiro, J.C., Modeling of the contact stress distribution at the tool–chip

interface. In Proceeding of the 7th CIRP International Workshop on Modeling of Machining

Operations, ENSAM, Cluny, France, 2004.

[26] Astakhov, V.P., Tribology of metal cutting, in Mechanical Tribology. Material Charac-

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Wear, 252 (2002), 375–383.

CHAPTER 5

Design of Experiments in Metal Cutting Tests

5.1 Introduction

Although metal cutting is one of the oldest manufacturing processes, most essential

characteristics and outcomes of this process such as tool life, cutting forces, integrity of

the machined surface and energy consumption can only be determined experimentally.

As a result, any further improvement in the tool, machine and process design, and

implementation of new cutting tool materials are justiﬁed through a series of experimental

studies. Unfortunately, experimental studies in metal cutting are very costly and time

consuming requiring sophisticated equipments and experienced personnel. Therefore,

the proper test strategy, methodology, data acquisition, statistical model construction and

veriﬁcation are of prime concern in such studies.

Metal cutting tests have been carried out for at least 150 years, in tremendously increasing

volume. However, most of the tests carried out so far have been conducted using a vast

variety of cutting conditions and test methods having a little in common with each other.

It is understood that test results are meaningless if the test conditions have not been

speciﬁed in such a way that the different factors, which affect the test results, will be

under a reasonable and practical degree of control. Though this sounds simple and logical,

the main problem is to deﬁne and/or determine these essential factors.

Unfortunately, there is lack of information dealing with test methodology and data

evaluation in metal cutting tests. Some information about setup and test conditions can

be found in most of the reported experimental studies. On the contrary, it is rather

difﬁcult to ﬁnd corresponding information about test methodology and answers to the

questions why the reported test conditions or design parameters of the setup were

selected at the reported levels, what method(s) was (were) used for experimental data

evaluation, etc.

Although the cost of testing in metal cutting is high, there is no drive to improve or gener-

alize the experimental results up to the level of National and International Standards. For

example, the standard ANSI/ASME Tool Life Testing with Single-Point Turning Tools

276