mid-sem part 1
TRANSCRIPT
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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