Mid-Sem Part 1

8/3/2019 Mid-Sem Part 1

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Mid Semester Project Report

MED 421

On

Tool Wear Model for Machining Of Titanium Alloy

Project No: P05

Submitted by

Niteesh Verma (Entry No: 2008ME20581)

Manish Mahi (Entry No: 2008ME20576)

Supervised by

Dr. Sudarshan Ghosh

Examiner

Prof. P.V Rao

Mechanical Engineering Department

Indian Institute of Technology Delhi

September 2011


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Contents

S.No. TOPIC PAGE

1) List Of Tables 32) Chapter 1: Introduction 4

3) Chapter 2: Literature Review 8

4) Chapter 3: Plan Of Work 13

5) Chapter 4 : Work Schedule 15

6) References 16

7) Appendix 17


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List of Tables

S.No. Tables Page

1 Average crater wear rates of various tool materials in turning of Ti-6Al-4V at

200sfpm

9

2 Estimated solubilities of tool materials in titanium at various temperatures 17

3 Reported solubilities of tool constituents 17

4 Predicted wear rates from the upper bound Diffusion Model (at 1400K) 18

5 Predicted Growth of TiC layer on Diamond 18


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1)Introduction1.1) Titanium

Titanium (Ti) is a chemical element with atomic number 22. It has a low density and

is a strong, lustrous, corrosion-resistant transition metal with a silver color. Titanium

can be alloyed with iron, aluminum, vanadium, molybdenum, among other elements,

to produce strong lightweight alloys for aerospace (jet engines, missiles, and

spacecraft), military, industrial process (chemicals and petro-chemicals, desalination

plants, pulp, and paper), automotive, agri-food, medical prostheses, orthopedic

implants, dental and endodontic instruments and files, dental implants, sporting

goods, jewelry, mobile phones, and other applications.

1.2) Salient Benefits of Using Titanium Alloys

Due to their high tensile strength to density ratio, high corrosion resistance, and

ability to withstand moderately high temperatures without creeping, titanium alloys

are used in aircraft, armor plating, naval ships, spacecraft, and missiles. For these

applications titanium alloyed with aluminium, vanadium, and other elements is used

for a variety of components including critical structural parts, fire walls, landing gear,

exhaust ducts (helicopters), and hydraulic systems. Ti also finds its usage in other

fields also such as consumer goods, architectural applications, automobile industries

and various industrial, aerospace, recreational, and emerging markets.

1.3) Types of Ti alloysTitanium alloys fall into four classes, depending on the structures present alloys,

near alloys, -alloys and alloys [1]

alloys contain -stabilizers. The alloy has excellent tensile properties and creepstability at room and elevated temperatures up to 300C.

Near alloys are highly -stabilized and contain only limited quantities of stabilizing elements. They behave more like alloys and are capable of operating

at greater temperatures of between 400 and 520C.


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- alloys contain addition of and stabilizers and they possess microstructuresconsisting of mixtures of and phases.

alloys contain significant quantities of -stabilizers and are characterized byhigh hardenability, improved forgeability and cold formability, as well as highdensity

1.4) Machining of titanium alloys

Although quite a bit of work has been done in machining of hard to machine

materials, but it has not kept its pace with the advancement of machinability of

titanium and its alloys due to their high temperature strength, very low thermal

conductivity, relatively low modulus of elasticity and high chemical reactivity. The

principle problems associated with machining of titanium alloys are as follows:

1.4.1) Generation of High cutting temperatureHigh cutting temperature act close to the cutting edge of the tool which is

principle reason of the rapid tool wear, according to Ezugwu and wang [2] a

large proportion (about 80%) of the heat generated when machining titanium

alloy Ti-6Al-4V is conducted into the tool because it cannot be removed with

the fast flowing chip into the work piece due to low thermal conductivity of

titanium alloys

1.4.2) Application of High cutting pressuresThe cutting forces recorded while machining of titanium alloys are similar to

machining of steels, while much higher mechanical stresses occur at the

cutting edge when machining titanium alloy. According to konig [3] stresses

in titanium alloy are three to four times than that in nickel alloy (Nimonic-105). This may be due to unusually small chip tool contact area on the rake

face. And high resistance of titanium alloy to deformation at elevated

temperatures which reduces only above 800C may also cause that much

difference in stresses.

1.4.3) Chatter During Machining of Titanium AlloysPrincipal cause of the chatter during machining is due to the low modulus of

elasticity of titanium alloys. When subjected to cutting pressure, titanium


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deflects nearly twice as much as carbon steel the greater spring-back behind

the cutting edge resulting in premature flank wear, vibration and higher cutting

temperature. The appearance of chatter may also be partly attributed to the

high dynamic cutting forces in the machining of titanium

1.4.4) High Chemical Reactivity of the Titanium AlloyTitanium and its alloys react chemically with almost all tool materials

available at cutting temperature in excess of 500C due to their strong

chemical reactivity. The tendency for chips to pressure weld to cutting tools,

severe dissolution-diffusion wear, which rises with increasing temperature,

and this demand additional criteria in the choice of cutting tool materials

1.5) Project focus

Considering the extensive use of titanium and its alloys in the aerospace due to its

excellent combination of high specific strength (strength to weight ratio) which is

maintained at elevated temperature, its fractional resistant characteristics and its

exceptional resistance to corrosion. Even a lot of research going on the machinability

of the titanium alloys from past 60 years, but still there do not exist a reliable tool

wear/tool life model. So we realized to predict a suitable and close tool wear model

which would be a phenomenal achievement in the research field of titanium and will

solve the problem of major industrial giants who are using titanium very extensively

like G.E, Boeing etc. Due to very ambiguous properties of titanium scientists and

researchers have tried a lot to derive a tool wear model but practically one or the other

property of titanium countered the attempts so far. Researchers have selected

particular tool and workpiece and tried to predict the model although they derived

mathematical equations but either they given wrong results or they were only

applicable for a particular tool-workpiece combination and not for any other, unlike in

the case of nickel alloy machining or HSS machining where scientists have

successfully come up with a tool wear model way back in past and also applicable for

wide range of parameters and materials.


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1.6) Approach

Since scientists started their research regarding the prediction of tool wear model by

considering all the properties of titanium and their effect on the tool life and comparedtitanium alloys with different materials and alloys that pertain similar properties and

tried to get solution out of that comparison. Similarly we will be looking at the

already proposed tool wear models for nickel alloys or HSS or titanium itself and try

to consolidate all of them and try to get as close as possible to the tool wear for

titanium alloys, will propose a model which will account all the parameters and will

validate the model with the help of set of experiments.

Our present work was to focus on the behavior of titanium and its alloys, on their

machinability, understanding various parameters that are related to tool wear or tool

life and complexity behind it. We understood the development of mathematical model

for different outputs of turning operations its dependency on basic parameters of

speed (V), feed (f) and depth of cut (d).

Friedman and Field [4] suggested a relation which sometimes called as extended

Taylor`s equation

T =

For p independent variables corresponding to wear parameters (properties)

R = c [ ]

Where Ej are the natural machining variables, c and j are model parameters and isa multiplicative random error

The above relation will help in deriving a true mathematical relation considering all

the machining variables and now the focus is to point out those variables and touch all

the aspects of machining of titanium which lead to a true or close tool wear model

which could be a work of great success.


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2) Literature Review

The purpose of the present study is to determine the wear mechanisms in titanium

machining by comparing the predictions from various theoretical models of tool wear

with experimental results. Generally, WC based compositions employed to machine

titanium react with the workpiece material to form titanium carbide. This reaction

layer has high deformation resistance at cutting temperatures and adheres strongly to

both tool and the chip. The only tool material which was found to both wear resistant

and more deformation resistant then WC is polycrystalline diamond. Since diamond is

essentially pure carbon, the formation of TiC layer at the interface is also promoted in

this case.

2.1) Tool Wear model Based on Solubility

2.1.1) Experiment Results:

Hartung [5] carried out turning tests on Ti-6Al-4V with the conventional C-2 grade

(Carbloy 820) and C-3(Kennametal k68) grade of cemented carbide at cutting speed

from 200-400 sfpm. This attributes that crater wear limits the tool life; flank wear is

stable and does not contribute to tool failure until crater wear weakens the edge in

plastic deformation of cutting edge causes acceleration of the wear at the flank. At

400sfpm and more leads to plastic deformation of the cutting edge and is responsible

for tool failure.

To determine the relative wear rate various potential tool materials in the machining

of Ti-6Al-4V, turning tests were performed at 200sfpm. The average crater wears of

various tool materials are shown in table 1.


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Tool material Wear rate()ZrC-Coated Kennametal K7H(C8) 56

HfC coated Kennametal k68 (C2) 52

Cemented TiC 43CBN 30

TiC coated WC(carboloy 523) 30

HfC coated WC 22

TiN coated WC 11

Diamond 1.4

Table1: Average crater wear rates of various tool materials in turning of Ti-6Al-4V at

200sfpm

2.1.2) Theoretical analysis:

Since crater wear is dominant form of tool wear in the machining of titanium alloy,

the first assumption was that the tool wear might be explained by the chemical

dissolution of the tool material in titanium. If the mechanism of chip flow is assumed

to be similar for different tool materials cutting under identical conditions, the relative

wear rate can be written as

Relative wear rate= =

= Wear rate of tool material i

Vi = Molar volume of tool material i

Ci= Solubility of tool material i in the work material at the cutting temperature.

The solubility estimates comes out to be given in Appendix table 2. The value in table

may be taken as the maximum possible solubilities based on chemical properties

alone which may be quite accurate when predicted solubilities are small. Otherwise

when large concentration the physical and geometrical defects become significant, it

is assumed that the solubility of tool material in titanium will not be greater thansolubility of its least soluble component.


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Appendix Table 3 lists the solubilities [6] of tool constituents of titanium obtained

from phase diagrams; comparing table 2 and 3 reveals that most of the tool materials

have solubilities in titanium greater than that of one of their least soluble component.

It may be seen that predictions based on solubility argument do not agree well with

test results. In particular the analysis does not explain the high wear rates of HfC and

ZrC coated tools related to that of WC. Unlike the HSS and Nickel alloys there was

not a significant difference in the tool wear property for coated and uncoated tool in

the case of titanium machining coated tool wore at about 20 times the rate of identical

uncoated tool and that cant be explained due to the diff. solubilities of the tool

materials.

Hence the tool wear in machining of titanium is fundamentally different from that of

steel and nickel alloys.

2.2) Upper Bound Calculations of the Diffusion Flux

It is possible that the diffusion of tool constituent materials within the chip controls

the wear. It has been assumed that no deformation occurs in the chip as its light across

the tool chip interface. This model provides an upper bound for the wear rates of the

tool materials in the machining of titanium due to diffusion.

= - KC( )

Where

= Wear rate of the tool material.

K= Ratio of molar volumes of tool material and the chip material

C= Equilibrium conc. of the tool material in the chip.


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D= Diffusion coefficient of the slowest diffusing tool constituent in the chip.

t= Time it takes for the chip tool move from the edge of the tool to the centre of the

crater

The value of t was estimated from chip thickness measurements and was found to be

approximately 3.2x sec and the molar volume of titanium is 10.64/mole [7].The predicted wear rates of various potential tool materials are shown in Appendix 1

table 4.

Comparison of predicted results with the actual measured wear rates reveals that this

model not only gives a gross overestimate of wear rate but also does not rank the

materials properly in order of their wear resistance.

2.3) Auger Experiment:

The existence of 100nm thick layer of TiC on the surface of the diamond to suggests

that the wear rate of the tool might be calculated from the rate of diffusion of carbon

through the TiC layer.

Formation of TiC layer on graphite from molten titanium follows a parabolic growth

law of the form [8]:

=t

=0.2 exp (-61800/RT) /sec

Where

x= Layer thickness, cm

= Parabolic Growth constant /sect= Carburization time, sec

T= Temperature, K

R= Universal gas constant


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The rate of growth of TiC layer is predicted at 1300, 1400 and 1500 K under the

assumption that the parabolic growth law holds at temperature under the melting point

of titanium.

Calculation of the wear rate of diamond in the machining of titanium

= - D = -

(

)

Where

y=

= the wear rate of the tool (cm/sec)=the molar Volume of the tool material /mole) = the concentration of carbon in the tool material (moles/mole) = the molar volume of titanium carbide at points i in the titanium carbide reactionlayer ( /mole)Ci= the concentration of carbon at point i in the titanium carbide reaction layer

(moles/mole)

b = the reaction layer/chip boundary

0 = the reaction layer/tool boundary

D = the diffusion coefficient of carbon in the titanium carbide reaction layer

(/sec)t = the thickness of the titanium carbide reaction layer (cm)

The reaction layer thickness, t, was assumed to be 100 nm, which was the

approximate measured value in the AES study. All concentrations are from phase

diagram data.

Putting the Values of above Parameters the predicted Wear rate of diamond agrees

quite well with test results. The wear rate of WC Predicted at 1300, 1400 and 1500K

is average out, which also approximately agrees with observed rate of cemented WC.


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2.4) Tool life model for hastelloy (Nickel based super alloy)

Tool life can be estimated = CD/Where CD is total cutting distance to reach flank wear criterion of 0.3mm is feedrate in mm/min. for KC520M model tool insert [9], the tool life estimated from therelation

Tool life = - 44.85 - 0.07461.7711.29 Where This relation is derived from the large experiments conducted, and using regression

method. This shows tool life decreases with increasing cutting speed, feed rate, and

axial depth.

3)Plan of Work Literature review :The first and very important part of our project

is to review the research being done so far and what was there

approach and how could we correct them or do better, consolidating

the previous efforts and efforts which will be put in this project. We

will look for proposed models for titanium and their drawbacks and try

to find out the common potential failure mode and then will take a

preventive action to go in the right direction

Objective formulation :- Our objective would be to identify asuitable model which will include every parameter that is responsible

for the ambiguous behavior for the tool wear in machining of titanium

alloy

Formulate and modeling: - after identifying a similar model we willtry to formulate it according to our tool and workpiece specification

and properties, will propose a analytical model.

Carry out Experiments: - We will carry out experiments On Ti-6Al-4V a - alloy and our tool material TiAlN, and try to support the

analytical model. It will help us in determining various coefficients and

constants. Ultimately it will lead to a mathematical tool wear model for

the specified workpiece-tool material combination.

Validate the model: - After proposing a mathematical model for Ti-6Al-4V and TiAlN, we carry out series of experiments on the above


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combination which will find out exact values and try to support the

proposed model. The experiments help us to rectify problems in model

and will give us real time data to deal with model accordingly.

Analysis: - After getting experimental results we will analyze the realtime practical results and try to find its application over the model. If

they match will be a great success, otherwise we will try to find out the

major drawback or error in the proposed model

Conclusion and Modification: - If the proposed model will be wellsupported by the experiments done on the combination mentioned

above, will conclude our results and proceed, else will try to modify

the results and conclude after getting a satisfactory model compatible

with the real time situation.

Our work deals with computation as well as experimentation, about a half of this

semester we will be doing analytical calculations and study to come up with a

mathematical model and will perform few experiments for development, next

semester will do more experiments to validate the proposed model and modify it.

Experiments will be performed together in our group and the analytical calculation

and formulation we will do independently with the supervision on each other and

consolidate our work to reach a common conclusion.


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4)GANTT CHARTWork\Week 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Literature review

Objective formulation

Formulate and modeling

Carry out Experiments

Validate the model

Analysis

Conclusion and

Modification

Work\Week 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

Literature reviewObjective formulation

Formulate and modeling

Carry out Experiments

Validate the model

Analysis

Conclusion and

Modification


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References

[1] LB. Borradile, R.H. Jeal, Titanium and Titanium Alloys, vols. I-3, 1981.

[2] E.O Ezugwo and Z.M Wang Journal of Materials processing technology 68 (1997)

262-274, School of Engineering Systems and Design, South Bank University,

London SEI OAA, UK

[3]W. Konig, Proc. 47th Meeting of AGARD Structural and Materials Panel,

Florence, Sept. 1978, AGARD, CP256, London, 1979, pp. 1.1-1.10.

[4] M. Y. FRIEDMAN and M. FIELD, Building of tool life models for use in a

Computerized numerical machining data bank. Proc. Int. Conf. Prod. Enono.,

Tokyo, Part 1 (1974).

[5] P. D. Hartung, Tool Wear in Titanium Machininq, S.M. Thesis, Department of

Mechanical Engineering, M.I.T., June 1981.

[6] W. G. Moffatt, The HandDook of Binary Phase Diagrams, General Electric

Company, Schenectady, New York, 1981.

[7]B. M. Kramer, Ph.D. Thesis, Department of Mechanical Engineering, M.I.T.1979.

[8] L. M. Adelsberg and L. H. CadofE, "The Reactions of Liquid Titanium and

Hafnium with Carbon," Transactions of the Metallurgical Society of -AIME,

Volume 239, June 1967, pp. 933-935.

[9] I.A. Choudhurya, M.A. El-Baradie, Machinability assessment of inconel 718 by

factorial design of experiment coupled with response surface methodology, J.

Mater. Process. Technol. 95 (1999) 3039.


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Appendix:

Table2: Estimated solubilities of tool materials in titanium at various temperatures

Tool material Solubility (mole %)

1300K 1400K 1500K

HfC 1.27 1.41 1.53

TiC 7.75 7.75 7.75

WC * * *

ZrC 4.23 4.42 4.58

HfN 10.92 12.80 13.35

. 0.033 0.076 0.16*= chemical reaction occurs

Table3:Reported solubilities of tool constituents

Tool constituent Solubility

1300K 1400K 1500K

Al 15 19 28

Hf * * *

N 23.6 23.5 23.2

Ta * * *

Ti 100 100 100

W * * *

Zr * * *

*= these constituents are soluble over a wide range of temperature and conc.


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Table4: Predicted wear rates from the upper bound Diffusion Model (at 1400K)

Tool

material

Ratio of molar

volumes*

Diffusion

coefficients+()Solubility

(mole %)

Predicted

wear rate

(m/min)

Diamond 0.321 2.28x 0.6 176TiC 1.147 4.83x 0.6 28.8WC 1.165 1.05x 0.6 9.48ZrC 1.472 1.40x 0.6 63TiN 1.080 4.82x 23.5 1063

Table5: Predicted Growth of TiC layer on Diamond.

Temperature

(K)

Parabolic growth

constant(cm2/sec)

Time(min) Layer

thickness

Time for layer

thickness of

500A 750A 1000A

1300 9.51*(-12) 1/20 0.239/1.068 2.63 5.92 10.52

1400 5.19*(-11) 1/20 0.358/2.497 0.48 1.08 1.93

1500 2.26*(-10) 1/20 1.165/5.210 0.11 0.25 0.44

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