Explicit

Explicit

Available online at www.sciencedirect.com ScienceDirect Materials Today: Proceedings 18 (2019) 4531–4636 www.materialstoday.com/proceedings ICMPC-2...

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Available online at www.sciencedirect.com

ScienceDirect Materials Today: Proceedings 18 (2019) 4531–4636

www.materialstoday.com/proceedings

ICMPC-2019

Heat assisted machining of Inconel 718 Alloy using Abaqus/Explicit A Kiran Kumara*, P Venkataramaiahb a

Research scholar,Department of mechanical engineering, S.V.University,Tirupati,517502, India b Professor, Department of mechanical engineering, S.V.University,Tirupati,517502, India

Abstract Nickel-based alloys have superior properties like high strength, low thermal conductivity and extreme fatigue strength however these properties make machining very difficult. Since Inconel 718 alloy has extensive applications in the field of aerospace, we need to find the best ways to improve its machinability. Heat assisted machining is one technique which makes machining easier because it reduces the shear strength of the work piece when compare to machining at room temperature. In the present paper, Abaqus/explicit software is used to study the influence of pre heating temperature on surface roughness and cutting forces during machining of Inconel 718 alloy using coated and uncoated tools. Finally the results are compared at room temperature and preheating conditions. © 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the 9th International Conference of Materials Processing and Characterization, ICMPC-2019

Keywords:

Heat assisted machining, Abaqus/Explicit, Johnson Cook Model, Surface roughness, Inconel 718

1. Introduction Nickel based super have a key role in aerospace industry due to its exceptional mechanical, chemical and thermal properties at elevated temperatures. However these properties leads to difficult to machine and the surface quality of a machined component can be affected if proper machining conditions are not taken. In past studies, many researchers carried out the machining of difficult to cut materials using finite element simulation. The effect of nose radius on temperature distribution in the tool is analyzed and noticed increase of cutting force and thrust force with increase of nose radius at both room and pre heating conditions [1].

* Corresponding author. E-mail address: [email protected]

2214-7853© 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the 9th International Conference of Materials Processing and Characterization, ICMPC-2019

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Nomenclature A - Yield stress (MPa) B - Strain hardening parameter (MPa) n - Strain hardening exponent C - Strain rate sensitivity parameter m -Temperature exponent εp - Plastic strain .

 *  ( p * /  0 ) is dimensionless strain rate T*m = (T-T0) / (Tm –T0); T, T0 and Tm being the working temperature, room temperature and melting temperature respectively. εf = fracture strain D1 to D5 are coefficients of Johnson-Cook material shear failure initiation criterion σ*= σm / σeq is the stress σeq = equivalent stress σm =mean stress

The effect of different edge roundness on residual stresses in machining of AISI304 steel has been studied using FE model [2]. Surface roughness is predicted in terms of effective feed rate of the cutting force components during the face milling operation of titanium alloy [3]. Prediction of temperature and its measurement during the machining of Ni-based super alloys has been carried out as it is critical factor to control the machining process, avoiding the work piece damage [4]. It is recommended that J-C model is still the best model for conducting the simulation of machining process because of its robustness and simple to apply using FEM [5]. Generation and distribution of temperature during chip formation has been studied using Abaqus software and also analyzed the stresses in machining [6]. Selection of suitable J-C model parameters will play an important role in order to get the best fit between predicted and measured results [7, 12, and 13]. Chip morphology in orthogonal machining using numerical model is compared with experimental studies to validate the results [8]. The residual stress present in the machined component using different materials through simulation has been reported [9, 10]. The influence of nose radius in chip formation and stress distribution is studied using finite element simulation [11]. In past, most of the works in machining simulations focused on effect of different parameters like speed, feed, depth of cut and tool geometry on cutting forces and temperature distribution and residual stresses but very few works were found in heat assisted machining using FEM simulation . In this paper, the objective is to study the machinability of Inconel 718 alloy using Abaqus/Explicit software and also the influence of room temperature and preheating temperature conditions on surface roughness by keeping speed, feed and depth of cut constant. 2. Finite Element Modeling 3D model of work piece and cutting tool were created and Johnson-Cook Model (Eq.1) has been deployed to the model which can relate the material behavior at high temperatures, high strains and high strain rates. Fig.1 (a) and Fig.1 (b) show the 3D and FEM model of work piece and cutting tool. Johnson-Cook failure model (Eq.2) is employed to define the chip removal in simulation process. The J-C model parameters are very much appropriate in dynamic simulation applications.

A K. Kumar et al./ Materials Today: Proceedings 18 (2019) 4531–4636



 eq  A  B p

n

.   .* 1  C ln( )  1  T *m    







(1)

.

(2)

 f  [ D1  D2 exp( D3 * )][1  D4 ln( p * )[1  D5T * ]

Fig.1. (a)

Solid Model of work piece and tool

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Fig1. (b) FEM Model of work piece and tool

J-C model parameter values for Inconel 718 alloy considered are listed in Table 1. The element type (C3D8RT) is selected which is suitable for the study of both the mechanical and thermal aspects of work piece in machining simulation. The properties of Inconel 718 alloy and cutting tools (coated and uncoated) and the tool geometry are listed in Table 2 and 3. Table 1: J-C model parameters of Inconel 718 alloy A(MPa)

B(MPa)

n

m

Table 2: Geometry of cutting Tool Rake angle, α

C

980

1370

0.164

1.03

0.020

D1

D2

D3

D4

D5

0.11

0.75

-1.45

0.04

0.89

6

0

Clearance angle 6

0

Nose radius(mm) 0.8

Table 3: Properties of Work piece and Tool S. No

Parameter

Inconel 718

WC

TiN Coated

1

Density(kg/m3)

8195

15700

5220

2

Young’s Modulus(Gpa)

200

705

600

3

Poisson ratio

0.3

0.23

0.25

4

Thermal conductivity(W/m0C)

11.4

24

19

5

Specific heat(J/Kg/0C)

430

178

-

The interaction of work piece and tool during the chip formation process plays a key role in determining the surface finish [14]. The coefficient of friction of 0.6 is chosen and the interaction between tool and work piece is considered as general contact. The boundary conditions of work piece and tool are shown in Figure 2 as bottom

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portion of the work piece is fixed and the tool has given degree of freedom along x-direction. The cutting parameters used in simulation of hot turning of Inconel 718 alloy is illustrated in the Table 4. Among all the parameters speed, feed and depth of cut are kept constant in order to the study the influence of preheating temperature and also the type of tool on surface roughness and cutting force.

Fig.2: Boundary conditions of work piece and tool Table 4: Machining parameters S.No

Tool

Speed

Feed

DOC

(m/min)

(mm/rev)

(mm)

100

0.11

0.2

Temp(oC)

1

Uncoated

2

Uncoated

30

3

Uncoated

600

4

Coated

30

5

Coated

300

6

Coated

600

300

3. Results and Discussion Simulations performed in Abaqus/Explicit software at different heating conditions using coated and uncoated tools in order to study the influence on surface roughness and cutting forces. Cutting force plots of the simulations are shown in the Figure 3(a & b). Surface roughness is estimated based on the feed force, as the surface roughness is proportional to the feed force [3]. The cutting forces obtained in these simulations are listed in the Table 5. Due to

Figure 3(a): Cutting force plot with uncoated tool

Figure 3(b): Cutting force plot with coated tool

A K. Kumar et al./ Materials Today: Proceedings 18 (2019) 4531–4636

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Table 5: Results Table S.No

Tool

Speed

Feed

DOC

(m/min)

(mm/rev)

(mm)

Temp(oC )

Cutting Force(N)

Feed Force(N)

Radial Force(N )

1

Uncoated

30

195

136.7

144.5

2

Uncoated

300

137.3

93.4

160.1

3

Uncoated

4

Coated

5

Coated

300

147.5

91

131.3

6

Coated

600

137.3

85.8

86.6

100

0.11

0.2

600

132

48.53

98.8

30

175

56.63

167.

pre heating, the work piece gets soften which reduces the shear strength and because of this it is observed that the cutting forces are reduced at 600 0 C compared to room temperature. Similar trend is noticed during the use of uncoated and coated tool. The cutting force variation with respect to pre heating temperature and cutting tools are plotted in Fig. 4 (a &b). The influence on surface roughness can be represented in terms of feed force which shows the similar trend to surface roughness. Hence it can be observed that the surface roughness is also reducing with increase in pre heating temperature. It is also observed that cutting forces got reduced during the coated tool case.

250 200 150 100 50 0

Cutting Force(N) Feed Force(N) Radial Force(N) 30 Deg. C 300 Deg.C 600 Deg.C

Fig 4a: Variation of cutting Force with uncoated tool at different temperatures 200 150 Cutting Force(N)

100

Feed Force(N) 50

Radial Force(N)

0 30(Deg. C) 300(Deg.C) 600(Deg. C)

Fig 4b Variation of cutting Force with coated tool at different temperatures:

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4. Conclusions From the simulation s of heat assisted machining of Inconel 718 alloy the following conclusions are drawn. 1. 2. 3. 4. 5.

The machining of Inconel 718 alloy at room temperature (300C), 3000C and 6000C were simulated in Abaqus/Explicit by considering uncoated and coated tool. Cutting forces got reduced at 6000C pre heating temperature compared to room temperature condition. Surface roughness variation is predicted in terms of Feed force which is also reduced at pre heating temperature compared to room temperature condition. Machining with coated tool is resulting less cutting forces compared to uncoated tool at different pre heating temperatures. Hence it is clear that the machinability of hard to cut materials like Inconel 718 alloy can be improved with aid of pre heating during machining.

5. References [1] Asit Kumar P, K Maity, 2016, Effect of nose radius on forces, and process parameters in hot machining of Inconel 718 using finite element analysis. Engineering Science and Technology, an International Journal 20 (2017) 687–693 [2] Liu and Guo, Finite element modeling the influence of edge roundness on the stress and temperature fields induced by high-speed machining. The international journal of advanced Manufacturing technology, pp.255-267, 2006 [3] Moaz H. Ali, Basim A. Khidhir, M.N.M. Ansari, Bashir Mohamed, 2013, FEM to predict the effect of feed rate on surface roughness with cutting force during face milling of titanium alloy. HBRC Journal (2013) 9,263-269 [4] Diaz-Alvarez J, Cantero J L, Miguelez H, Soldani X, Numerical analysis of thermo mechanical phenomena influencing tool wear in finishing turning of Inconel 718. Int. J. Mech. Sci. 2014, 82, 161-169. [5] Muthu Elagovan, K Senthamarai, S Jayabal, Finite element simulation in machining of Inconel 718 nickel based super alloy. International Journal of Advanced Engineering Applications, Vol.5, Iss.3, pp.22-27(2012) [6] B.V.R.M Kumar, K Hemachandra Reddy, Ch. R. Vikram Kumar, Finite Element Model Based On Abaqus / Explicit To Analyze The Temperature Effects Of Turning. International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, November 8(2016) pp 5728-5734 [7] Abhushawashi Y, Xiao. Astakhov V. FEM Simulation of Metal cutting using a New Approach to model chip formation. Int. J. Adv. Mach. Form. Oper2011; 3:71-92 [8] Arvind J, Raja Hussain, process modeling, simulation and experimental validation for prediction of chip morphology during high speed machining of Al 2024-T3. SAS TECH Journal volume 13, Issue1, April 2014 [9] M. H. Miguelez, R. Zaera, A. Molinari, R. Cheriguene, and A. Rusinek, Residual stresses in orthogonal cutting of metals: The effect of thermo mechanical coupling parameters and of friction. Journal of thermal stresses, 2009, vol.32, n. 3, p.269-289 [10] M. Nasar, E.G Ng, and M.A. Elbestawi, Modeling the effects of Tool-Edge Radius on Residual stresses when orthogonal cutting AISI316L. International Journal of Machine Tools Manufacturing, vol. 47, pp. 401-411, 2007 [11] Keng Soon Woon, Mustafizur Rahman, The effect of tool edge radius on the chip formation behavior of tool-based micromachining. October 2010. International Journal of Advanced Manufacturing Technology 50(9):961-977 [12] Ng, E.-G., Tahany I. E.W., Dumitrescu, M., and Elbastawi, M.A., 2002, Physics-based simulation of high speed machining. Machining science and technology, 6/3,301-329 [13] Guo,Y.B and Yen, D.W., 2004, A FEM study on mechanisms of discontinuous chip formation in hard turning. J. Materials Processing Technology, 155-156, 1350-1356 [14]W. Grzesik, P. Nieslony, M. Bartoszuk, 2005, “Finite element modeling of temperature distribution in the cutting zone in turning processes with differently coated tool”, Journal of Materials Processing Technology 164-165, pp. 1204-1211