1. International Journal of Advanced Engineering Applications, Vol.5, Iss.3, pp.22-27 (2012)
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Finite element simulation in machining of Inconel 718 nickel
based super alloy
E. Muthu1
, K. Senthamarai2
, S.Jayabal3
Department of Mechanical Engineering,
1, 3
A. C. College of Engineering and Technology, Karaikudi.
2
Mookambigai College of Engineering, Kalamavur.
muthuaccetkkdi@yahoo.in1
, ksentha75@yahoo.co.in2
, jayabalsubbaian@rediffmail.com3
Abstract - This paper is focussed on the finite element analysis (FEA) of machining of Inconel 718 superalloy using
DEFORM 2D. Orthogonal cutting experiments are carried out on cylindrical workpiece of Inconel 718 with cutting speed of
50 m/min, feed rate of 0.1 mm/rev. and nose radius of 0.6, 0.8 & 1.0 mm. The Johnson-Cook constitutive equation is
implemented in the finite element code to study the deformation behaviour of Inconel 718 during the machining process. The
simulation results showed that the chip segmentation is not occurred at the low cutting speed and the stress on the machined
surface is residual in nature while stress value is decreased around the uncut surface and the deformed chip. The plastic
strain is higher at the primary zone followed by the secondary shear zone and least at the free end of the chip.
Keywords - Constitutive equation, orthogonal cutting,finite element analysis, Deform 2D.
1 INTRODUCTION
The use of Nickel-based super alloy in aerospace was begun in the 1930’s. Need for the more creep
resistant material than the available austenitic stainless steel propelled research for the development of new
superalloy. The principal characteristics of nickel as an alloy base are highly phase stability of face centered
cubic (FCC) nickel matrix and outstanding strength retention upto 0.7 Tm (melting point).these characteristics
encourage use of nickel base superalloys in vast number of applications subjected to high temperatures1
.
Commercially available nickel base superalloys include Inconel, Nimonic, Rene, Udimet and Pyromet. Inconel
718 is the most frequently used nickel based superalloys; hence this study is focused on an investigation into the
mechanics of machining Inconel 718. Some of the applications of nickel based superalloys are in aircraft gas
turbines (eg. disks, combustion chamber, casings, shafts, exhaust system, blades, vanes, burner, cans, stack gas
reheaters), reciprocating engines (eg. turbochargers, exhaust valves hot plugs, valve seat inserts), metal
processing (eg. hot work tools and dies), space vehicles (eg. aerodynamically heated skins, rocket engine parts)
heat treating equipments (eg. trays, fixtures, conveyor belts, baskets, fans, furnace mufflers), nuclear power
plants, chemical and petrochemical industries and heat exchangers.
High temperature gradients are localized in narrow bands along shear plane due to poor thermal properties
of Inconel 718, leading to weakening the material in the deformation zone. When the rate of thermal softening is
greater than that of strain hardening, material deforms locally, termed as adiabatic shear failure. The type of
chips formed under these conditions is termed as shear localized chips. Oscillations in cutting forces and high
temperatures on the rake face in the contact area can cause rapid tool wear. High pressures developed during
segmented chip formation retards further machining and increase power requirements of the process. Ezugwu et
al.(1999) summarized the properties of nickel based superalloys, contributing to poor machinability. Finite
element analysis has revolutionized the quality of metal cutting research since it was first proposed by Tay et
al.(1974).
Usui et al.(1982) developed the first two dimensional FE model to simulate orthogonal machining which
was based on an elasto-plastic material model using the iterative convergence method for steady state cutting.
Klamecki (1973) explained the initial stages of chip formation in metal cutting by three dimensional models.
Iwata et al. (1984) used a rigid plastic material model with plane strain conditions to the orthogonal cutting
process. Strenkowski et al.(1985) used an updated Lagrangian model to simulate machining without a pre-
formed chip. The phenomenal growth in computing technology has accelerated the use of finite element
methods which has helped to improve the quality of tooling and productivity for the manufacturing industries.
The last two decades has seen a phenomenal rise in the number of FE models and codes used by various
researchers. Deform-2D has been the most popular of the FE codes amongst the researchers due to its superior
simulating capabilities.
Recently, some researchers presented their finite element simulations in machining with new and
inadequacy of the J-C law in modeling due to the absence of thermal softening phenomena, lack of thermo-
dynamical term in the equation and lack of shear localization term, respectively. Lalwani et al.(2009) extended
the Oxley predictive machining theory of the J-C flow stress model by studying the effect of strain in addition to
strain rate and temperature in machining. Sima et al.(2010) developed a modified material model for modelling

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the serrated chip formation in titanium alloys. Umberllo et al. (2008) employed three different J-C models to
simulate high speed machining of titanium alloys and presented good results.
The J-C model is still the most popular model for simulating machining due to its robustness and its ease of
application in the FE codes, in the present work, the J-C constitutive equation have been used to represent the
flow stress behaviour of Inconel 718 alloy.
2 MATERIAL CONSTITUTIVE MODEL
The flow stress behaviour of Inconel 718 was modeled using Eq.(1), which was proposed by Johnson-
Cook (1983) and describes the flow stress of the material as a function of strain, strain rate and temperature
effects .The three terms represent the individual effects of strain hardening, strain rate hardening and thermal
softening on the flow stress of the material undergoing deformation. The limitations of the JC model are
inability to predict the flow stress at deformations below room temperature, lack of insight into interactions
between strain, strain rate and temperature and lack of thermal softening phenomena. The JC model has been
popularly employed to characterize the material deformation behaviour of various materials due its suitability
for use in FE codes.
σ = [A+Bε n
] [1+ C ln (ε'/ ε'o)] [1 – {(T – T room) / (T melt – T room)} m
] (1)
where σ is the flow stress, ε is the equivalent plastic strain, ε' is the strain rate, ε'o is the reference plastic
strain rate, T is the temperature of the work material, Tmelt is the melting temperature of the work material and
Troom is the room temperature. Coefficient A is the yield strength, B is the hardening modulus, C is the strain rate
sensitivity coefficient, n is the hardening coefficient and m is the thermal softening coefficient. The strain rate ε'
is normalized with a reference strain rate ε'o. The material parameters of the Johnson-Cook model (1983) are
listed in Table 1.
Table 1 Johnson-Cook material model parameters
A[MPa] B[MPa] C n m
1029.100 1477.500 0.060 0.330 1.440
3 FINITE ELEMENT MODELING AND SIMULATION OF ORTHOGONAL CUTTING
3.1 FE model
The finite element modeling was performed in Deform 2D which is based on an updated Lagrangian
formulation that considers the mesh to be attached to the work piece during deformation. The chip shape
develops as a function of deformation process, process parameters and material properties and hence need not to
be predetermined. The work material was highly constrained while tool material was allowed movement in the
X- axis. The thermo-physical properties of the work and tool materials and the flow stress data of Inconel 718
alloy calculated from the material models incorporated into the FE model. The work piece was modeled as
plastic and the tool as rigid materials.
A 10 × 2.5 rectangular cross section was considered for the work piece geometry and meshed with 5000
four noded isoparametric quadrilateral elements with an elemental width of 0.04775 mm and the aspect ratio of
1 to ensure a high density mesh. The tool geometry incorporating the rake and clearance angles of the tool used
in the experiments was meshed with 750 elements. The simulation was carried out with plane strain assumption
and the cutting conditions were identical to the experiments. An automated remeshing algorithm integrated in
the FE code ensures the continuity of the chip formation. The simulated results were viewed through the post
processor and the results are noted at near steady state conditions. Experimental conditions for machining
Inconel 718 are in the Table 2.
Table 2 Experimental conditions for machining Inconel 718
Workpiece Inconel 718
Tool material PCBN
Inserts Model Number CNMG 120408 MP, KC 5010
Tool rake angle -5⁰
Tool clearance angle +5⁰
Tool nose radius(mm) 0.6, 0.8 & 1.0
Feed rate (mm/rev.) 0.1
Cutting speed (m/min) 50

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Depth of cut (mm) 0.5
Cutting condition Dry
3.2 Fracture criterion
The Cockroft and Latham (1968) criterion given in Eq. (2) was employed in the FE code to account for
the fracture phenomena which cause segmented chips typical of titanium alloys even at low cutting speeds. It
states that fracture occurs when the integral of the largest tensile principal stress component over the plastic
strain path reaches the critical damage value, D.
(2)
where εf is the effective strain, σ1 is the maximum principal stress and D is a material constant. The critical
damage value is computed for every element at each time step and initiates a crack when this value is reached in
two steps:
(i) the element is deleted with all parameters related to it and
(ii) the rough boundary produced by element deletion is smoothed by cutting out the considered rough
angle and adding new points.
3.3 Friction modeling
The constant coulomb friction model given in Eq. (3) was employed in the FE code to model the friction
characteristics of Inconel 718 alloy machining. The simple friction law was chosen since it has been proved that
coefficient of friction is more relevant to frictional modeling than the law on which it is based and the forces
data are sufficiently reliable and less sensitive over a wide range of frictional values from 0.2 to 0.8. Filice et
al.(2007).
τ = μσn
(3)
where τ is the shear stress, μ is the coefficient of friction and σn is the normal stress. The shear stress is
expressed as a product of Coulomb friction coefficient with the normal stress. The FE simulation is performed
with available μ and D values [Deform User manual] and the cutting force and chip morphology compared with
experiments. The μ and D values are modified till there is no appreciable change in the cutting forces and chip
morphology outputs measured. In this work a μ value of 0.6 and D value of 100 was employed for the
comparative study.
4 RESULTS & DISCUSSION
The finite element results for effective stress, strain, temperature distribution and damage with the input
material model for different tool nose radius are presented in this chapter. The analysis is presented for cutting
speed of 50 m/min and feed rate of 0.1 mm/rev for all different tool nose radius values (0.6, 0.8 & 1.0 mm).the
cutting speed and feed rate at constant in this study. The FE output was observed at nearly steady state
conditions in this study.
4.1 Stress Analysis
The von mises stress plot for effective stress distribution for 0.6, 0.8 & 1.0 mm tool nose radius are shown
in Fig. 1. The negative rake angle causes the greater stress on the work material and the tool at the point of
contact. The stress on the machined surface is residual in nature while stress value is decreased around the uncut
surface and the deformed chip.

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Fig. 1 Effective stress distribution plot for different nose radius values
4.2 Strain Distribution
Fig. 2 shows the predicted effective strain distribution for 0.6, 0.8 & 1.0 mm tool nose radius values. The
plastic strain is higher at the primary zone followed by the secondary shear zone and least at the free end of the
chip. The simulated models for the three nose radius presented similar patterns. There appears to be minor
variations in the primary and secondary deformation zones. The higher stress near the shear plane for radius
1.0mm and 0.8mm should suggest higher deformations, but only 0.8mm replicates this proposition. 1.0mm and
0.8mm shows higher deformation at the shear plane tool chip contact respectively.
Fig. 2 Effective strain distribution for different nose radius values
4.3 Temperature Distribution
Fig. 3 shows that the temperature distribution for the various nose radius heat transfers in the machining
process takes place primarily in the shear zone was the plastic work is converted into heat and the chip tool
interface where the frictional heat is generated. Some heat is lost to the ambience through convection and some
transfer to the outgoing chip and the cutting tool through conduction. The low thermal conductivity of nickel
alloy ensures poor heat dissipation, resulting in rapid tool wear and reduction in the tool life. Hence cutting fluid
and the cryogenic coolants are necessary to quickly remove the latent heat.
In the FE model the work material is treated as plastic and the tool as rigid to facilitate better
understanding of the heat transfer due plastic deformation of the nickel alloy during machining. Hence, the
thermal analysis is concentrated on work material alone. The temperature reaches steady state quickly after the
initial increase in the primary and the secondary deformation zone. The experimental temperature is usually the
highest at the chip tool interface (secondary deformation zone) followed by the shear plane zone and least in the
uncut surface. The simulated maximum temperatures are more within the chips due to the low thermal
conductivity which does not allow quick heat dissipation form the deformed chip. The temperature distribution
in the primary and tertiary zones is as expected in the machining process.
The effect of cutting speed and friction modelling also has an effect on the temperature distribution.
Generally the FE prediction for temperature are likely to show lesser than normal values (as observed in

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literature), because of the short cutting process simulation which prevents the temperature form reaching steady
state.
Fig.3 Temperature distribution plot for different nose radius values
4.5 Damage Distribution
Fig. 4 shows that damage value distribution in the chip during cutting of Inconel 718. The location of a
larger damage value is correctly corresponding to the above discussed stress state in chip segmentation. It can be
seen that high damage value is located at a different region as the nose radius changes.
Fig.4 Damage distribution plot for different nose radius values
5 CONCLUSION
The present study was focused on the finite element simulation of turning process of Inconel 718 material
for various nose radius values. The Johnson-Cook material constitutive model was used to represent material
behaviour in the present investigation. The following observations were made from the study.
(i) Chip segmentation is not occurred in low cutting speed. In this case upto 50 m/min no chip segmentation
was observed.
(ii) Negative rake inserts produces compressive stress while positive rake inserts give tensile stress.
(iii) The nose radius increases the contact length between the tool and chip interface is increase and the
compressive stress decreases. The residual stress in the machined surface is residual in nature while the
stress value decreases in the deformed chip and uncut surface.
(iv) The plastic strain is higher at the primary zone followed by the secondary shear zone and least at the free
end of the chip. This chip shows regions of high and low strain across the chip thickness.
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