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2D Finite Element Thermo-Mechanical Model To Predict Machining Induced Residual Stresses Using ALE Approach
Available online at www.sciencedirect.com
ScienceDirect Materials Today: Proceedings 5 (2018) 11780–11786
www.materialstoday.com/proceedings
ICMMM - 2017
2D Finite Element Thermo-Mechanical Model To Predict Machining Induced Residual Stresses Using ALE Approach Prakash Marimuthu Ka*, Chethan Kumar C Sb, Thirtha Prasada H Pc a
Department of Mechancial Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, Amrita University, India b Department of Industrial Engineering Management, M S Ramaiah Institute of Technology, India c Department of Computer Aided Engineering, Visvesvaraya Institute of Advanced Technologies, Visveswaraya Technological University, India
Abstract Understanding the machining process in the microscopic level has been a challenge over the years. Machining process as such is very complex due to various factors, which is involved like friction, plastic deformation, material failure etc. The present works aims at developing a 2D FE model to predict the residual stresses induced after machining operation. Over the years’ lot of development has taken place particularly with the advent of high-end computers and FEM software packages. This works aims at incorporating the developments that has taken place in the field of Finite Element Analysis of machining processes and try to give an improvised model to understand the machining process in a better way. The work also aims at determining the residual stresses that are induced in the material after machining, its nature and magnitude. The influence of machining parameters on the machining induced residual stresses was studied with the help of commercially available software. Present work has been conducted on AISI 1045 steel. Simulations results are in good agreement with the experimental results. © 2017 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Materials Manufacturing and Modelling (ICMMM - 2017).
Keywords:Machining; Finite element analysis; Residual stresses;
1. Introduction Machining has been an area of research interest since long time. Components are produced either using material addition method or material removal method. Machining is primarily used to make the component to net shape after the primary processes such as casting, forming welding etc. Researchers have used many analytical as well as numerical methods to understand the machining process at a deeper level[1, 2]. The present work is an attempt to
* Corresponding author. Tel.: +91 9620626222 E-mail address:[email protected] 2214-7853© 2017 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Materials Manufacturing and Modelling (ICMMM - 2017).
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
11781
Nomenclature A B C n m D1-D5 ALE
Yield Stress Strain Factor Strain rate factor Strain exponent Temperature exponenet Johnson cook damage parameters Arbitrary Lagrangian Eulerian
predict the nature, magnitude of the residual stresses that are induced due to the machining processes. A thermomechanical model is developed to predict the residual stresses that are developed because of machining. Over the years, researchers have studied the different aspects of machining like, chip formation, forces induced, temperature distribution in the work piece as well as the tool, wear of the tools and so on[3-5]. In the recent years the study is shifting to understand the intricacies of residual stresses[6-9], because the amount and nature of residual stresses play a crucial part in the functional performance of the components when put into the working environment. Properties like fatigue, wear resistance, corrosion resistance are affected when residual stresses are present in the component[10-12]. Over the years Finite element analysis has gone a long way in helping the researchers in understanding the different processes in a microscopic level [13-17], be it a flow analysis or an industrial analysis[18, 19].Very few work have been carried out on the effect of sequential cuts on material [20]. Hence this work is an attempt to predict the residual stresses that are induced using a finite element model. The reason for going for finite element model, is that it is quick, reliable and cost effective because it eliminates the need to perform cost experiments. 2. Finite Element Modelling Over the year Finite Element, modelling has helped many researchers in understanding different processes be it flow analysis or structural analysis. Generally, Eulerian approach is used for flow analysis[21] and Lagrangian approach is used for structural analysis. Coupled Eulerian Lagrangian approach is used for problems which involve both flow and structural analysis [22]. The present work uses ALE approach has been used which combines the advantage of both Lagrangian and Eulerian approach. Johnson-Cook material model and Johnson-Cook damage model has been widely used by the researchers to finite element modelling on machining. The authors of this work have also used the same combination because the models give very reliable results. AISI 1045 steel has been used for the analysis. The Johnson- Cook model values for the said material is given in Table 1. Table 1. Johnson Cook material and Damage model values[23]. Parameter
Value
A
553.3 MPa
B
600.8 MPa
C
0.013
n
0.0234
m
1
D1
0.06
D2
3.31
D3
-1.96
D4
0.0018
D5
0.058
11782
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
Friction is one of the factors that highly influence such analysis. In this analysis a basic friction model is assumed. Coulomb friction model is being assumed for the current analysis and a friction coefficient of 0.3 is being assumed as the coefficient of friction. The materials properties, along with the friction coefficient that is being used in the analysis is give in Table 2. Table 2. AISI 1045 steel material properties Parameter
Value
Young’s Modulus
210 GPa
Poisson’s Ratio
0.3
Specific heat
432 J/kg/◦C
Thermal Conductivity
47.7 W/m◦C
Density
7800 kg/m3
Friction Coefficient
0.3
2.1. Modelling, Meshing and Loading A 2D thermo-mechanical model is considered for the present work. The work piece was modelled as 4 mm in length and 1 mm in height. Both the tool and work piece were modelled as deformable material. The tool was modelled with both positive rake and negative rake angles and the analysis were done. The meshed model that was used for the simulation along with the loading and boundary condition is shown is Fig.1.
Fig. 1. Meshed Model with Boundary conditions
In order to validate the model the cutting conditions that were used by Tugrul Ozel in his work [24] has been used, the cutting conditions are shown in Table 3. The results obtained using the cutting conditions used in the literature are given in Fig. 2. and Fig. 3. The stress distribution is shown in Fig. 2. and the temperature distribution is shown in Fig. 3. The results are in good agreement with the published results. Table 3. Cutting conditions as per literature. Cutting Condition
Value
Cutting Speed
300 m/s
Feed
0.1 mm/rev
Width of Cut
1 mm
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
11783
Fig. 2. Stress distribution
Fig. 3. Temperature distribution
After validating the model the different cutting condition were used to predict the residual stresses that are induced due the orthogonal machining of AISI 1045 steel. The cutting conditions that were used for the prediction of residual stressed in given in Table 4. Table 4. Cutting conditions for residual stress measurement. Cutting Condition
Value
Speed
100, 200 and 300 m/s
Feed
0.1, 0.15 and 0.2 mm/rev
Width of Cut
1 mm
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Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
3. Results and discussion Simulation were done using three different cutting speeds and three different feed rates and a constant width of cut, the details of which are given in Table 4. The Force variation is shown in Fig. 4. When the cutting speed was varied in increments of 100 m/s from 100 to 300 m/s. The Von Mises stress that develops during the machining process is shown in Fig. 5.
Fig. 4. Force variation for the different cutting speeds.
Fig. 5. Von Mises stress distribution ( Cutting speed= 100 m/s, Feed = 0.2 mm/rev and width of cut = 1mm).
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
11785
The residual stress was predicted for different cutting conditions. The induced residual stresses were compressive below the surface of the cut work piece for a few microns and thereon it becomes tensile. The trend of the residual shows for cutting speed of 100 m/s , feed of 0.1 mm/rev and width of cut of 1 mm shown in Fig. 6.
Fig. 6. Von Mises stress distribution ( Cutting speed= 100 m/s, Feed = 0.2 mm/rev and width of cut = 1mm).
4. Conclusion A thermo-mechanical model was developed using a commercially available software. The obtained results are in good agreement with the published results. Irrespective of the cutting condition the machining process induced a compressive residual stresses just beneath the cut surface and there upon becoming tensile in nature. The developed model can predict the temperature distribution as well. Under different cutting conditions the maximum temperature that developed the work piece was ranging from 600 to 750 degree Celsius. 5. Future Work The future work involves optimizing the cutting parameters that influence nature and magnitude of the residual stresses. Also the effect of sequential cuts on the machining induced residual stresses. Further research has to be done to determine the effect of the induced residual stresses on the functional performance of the components. References [1] A. Sahraie JahromiB. Bahr, An analytical method for predicting cutting forces in orthogonal machining of unidirectional composites, Composites Science and Technology.70 (2010) 2290-2297. [2] J. C. Outeiro, D. Umbrello, R. M’Saoubi, Experimental and numerical modelling of the residual stresses induced in orthogonal cutting of AISI 316L steel, International Journal of Machine Tools and Manufacture.46 (2006) 1786-1794. [3] B. ZhangA. Bagchi, Finite Element Simulation of Chip Formation and Comparison with Machining Experiment, Journal of Manufacturing Science and Engineering.116 (1994) 289-297. [4] M. R. Movahhedy, M. S. Gadala, Y. Altintas, Simulation of Chip Formation in Orthogonal Metal Cutting Process: An Ale Finite Element Approach, Machining Science and Technology.4 (2000) 15-42. [5] D. Umbrello, L. Filice, S. Rizzuti, F. Micari, L. Settineri, On the effectiveness of Finite Element simulation of orthogonal cutting with particular reference to temperature prediction, Journal of Materials Processing Technology.189 (2007) 284-291. [6] M. A. BalbaaM. N. A. Nasr, Prediction of Residual Stresses after Laser-assisted Machining of Inconel 718 Using SPH, Procedia CIRP.31 (2015) 19-23.
11786
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
[7] J. E. WyattJ. T. Berry, A new technique for the determination of superficial residual stresses associated with machining and other manufacturing processes, Journal of Materials Processing Technology.171 (2006) 132-140. [8] Y. M. ArısoyT. Özel, Prediction of machining induced microstructure in Ti–6Al–4V alloy using 3-D FE-based simulations: Effects of tool micro-geometry, coating and cutting conditions, Journal of Materials Processing Technology.220 (2015) 1-26. [9] Y. Choi, A study on the effects of machining-induced residual stress on rolling contact fatigue, International Journal of Fatigue.31 (2009) 1517-1523. [10] T. Shiozaki, Y. Tamai, T. Urabe, Effect of residual stresses on fatigue strength of high strength steel sheets with punched holes, International Journal of Fatigue.80 (2015) 324-331. [11] C. J. LammiD. A. Lados, Effects of residual stresses on fatigue crack growth behavior of structural materials: Analytical corrections, International Journal of Fatigue.33 (2011) 858-867. [12] B. P. Dileep, V. Ravikumar, M. Prashanth, M. V. Phanibhushana, Effect of Zinc coating on Mechanical Behavior of Al 7075, Applied Mechanics and Materials.592-594 (2014) 255-259. [13] A. Laamouri, H. Sidhom, C. Braham, Evaluation of residual stress relaxation and its effect on fatigue strength of AISI 316L stainless steel ground surfaces: Experimental and numerical approaches, International Journal of Fatigue.48 (2013) 109-121. [14] A. Muñoz-Sánchez, J. A. Canteli, J. L. Cantero, M. H. Miguélez, Numerical analysis of the tool wear effect in the machining induced residual stresses, Simulation Modelling Practice and Theory.19 (2011) 872-886. [15] M. N. A. Nasr, E. G. Ng, M. A. Elbestawi, A modified time-efficient FE approach for predicting machining-induced residual stresses, Finite Elements in Analysis and Design.44 (2008) 149-161. [16] M. MandelL. Krüger, FE-simulation of Galvanic Corrosion Susceptibility of two Rivet Joints Verified by Immersion Tests, Materials Today: Proceedings.2 (2015) S197-S204. [17] K. S. Kumar, Numerical Modeling and Simulation of a Butt Joint Welding Of AISI 316L Stainless Steels Using a Pulsed Laser Beam, Materials Today: Proceedings.2 (2015) 2256-2266. [18] T. Mohanavelu, R. Krishnaswamy, P. Marimuthu, Simulation Modeling and Development of Analytic Hierarchy Process (AHP) based Priority Dispatching Rule (PDR) for a Dynamic Press Shop, International Journal of Industrial and Systems Engineering.In Press. [19] M. A. R. Junaidi, N. B. V. L. Kumari, M. A. Samad, G. M. S. Ahmed, CFD Simulation to Enhance the Efficiency of Centrifugal Pump by Application of Inner Guide Vanes, Materials Today: Proceedings.2 (2015) 2073-2082. [20] P. Krishnakumar, K. Prakash Marimuthu, K. Rameshkumar, K. I. Ramachandran, Finite element simulation of effect of residual stresses during orthogonal machining using ALE approach, Int. J. Machining and Machinability of Materials.14 (2013) 213-229. [21] R. Bharathwaj, P. Giridharan, K. Karthick, C. H. Prasath, K. P. Marimuthu, Computational study of Coanda based Fluidic Thrust Vectoring system for optimising Coanda geometry, IOP Conference Series: Materials Science and Engineering.149 (2016) 012210. [22] P. L. Meyappan, Akhila Roy, J. Abhijith, M. N. V. Ramesh, K. Prakash Marimuthu, Tsunami Wave Impact on Structures, International Journal of Applied Engineering Research.10 (2015) 1135-1139. [23] M. N. A. Nasr, Effects of Sequential Cuts on Residual Stresses when Orthogonal Cutting Steel AISI 1045, Procedia CIRP.31 (2015) 118123. [24] T. Ozel, Finite Element Method Simulation of Machining of AISI 1045 Steel With A Round Edge Cutting Tool, Proceedings of 8th CIRP International Workshop on Modeling of Machining Operations.(2005) 533-542.
ScienceDirect Materials Today: Proceedings 5 (2018) 11780–11786
www.materialstoday.com/proceedings
ICMMM - 2017
2D Finite Element Thermo-Mechanical Model To Predict Machining Induced Residual Stresses Using ALE Approach Prakash Marimuthu Ka*, Chethan Kumar C Sb, Thirtha Prasada H Pc a
Department of Mechancial Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, Amrita University, India b Department of Industrial Engineering Management, M S Ramaiah Institute of Technology, India c Department of Computer Aided Engineering, Visvesvaraya Institute of Advanced Technologies, Visveswaraya Technological University, India
Abstract Understanding the machining process in the microscopic level has been a challenge over the years. Machining process as such is very complex due to various factors, which is involved like friction, plastic deformation, material failure etc. The present works aims at developing a 2D FE model to predict the residual stresses induced after machining operation. Over the years’ lot of development has taken place particularly with the advent of high-end computers and FEM software packages. This works aims at incorporating the developments that has taken place in the field of Finite Element Analysis of machining processes and try to give an improvised model to understand the machining process in a better way. The work also aims at determining the residual stresses that are induced in the material after machining, its nature and magnitude. The influence of machining parameters on the machining induced residual stresses was studied with the help of commercially available software. Present work has been conducted on AISI 1045 steel. Simulations results are in good agreement with the experimental results. © 2017 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Materials Manufacturing and Modelling (ICMMM - 2017).
Keywords:Machining; Finite element analysis; Residual stresses;
1. Introduction Machining has been an area of research interest since long time. Components are produced either using material addition method or material removal method. Machining is primarily used to make the component to net shape after the primary processes such as casting, forming welding etc. Researchers have used many analytical as well as numerical methods to understand the machining process at a deeper level[1, 2]. The present work is an attempt to
* Corresponding author. Tel.: +91 9620626222 E-mail address:[email protected] 2214-7853© 2017 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Materials Manufacturing and Modelling (ICMMM - 2017).
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
11781
Nomenclature A B C n m D1-D5 ALE
Yield Stress Strain Factor Strain rate factor Strain exponent Temperature exponenet Johnson cook damage parameters Arbitrary Lagrangian Eulerian
predict the nature, magnitude of the residual stresses that are induced due to the machining processes. A thermomechanical model is developed to predict the residual stresses that are developed because of machining. Over the years, researchers have studied the different aspects of machining like, chip formation, forces induced, temperature distribution in the work piece as well as the tool, wear of the tools and so on[3-5]. In the recent years the study is shifting to understand the intricacies of residual stresses[6-9], because the amount and nature of residual stresses play a crucial part in the functional performance of the components when put into the working environment. Properties like fatigue, wear resistance, corrosion resistance are affected when residual stresses are present in the component[10-12]. Over the years Finite element analysis has gone a long way in helping the researchers in understanding the different processes in a microscopic level [13-17], be it a flow analysis or an industrial analysis[18, 19].Very few work have been carried out on the effect of sequential cuts on material [20]. Hence this work is an attempt to predict the residual stresses that are induced using a finite element model. The reason for going for finite element model, is that it is quick, reliable and cost effective because it eliminates the need to perform cost experiments. 2. Finite Element Modelling Over the year Finite Element, modelling has helped many researchers in understanding different processes be it flow analysis or structural analysis. Generally, Eulerian approach is used for flow analysis[21] and Lagrangian approach is used for structural analysis. Coupled Eulerian Lagrangian approach is used for problems which involve both flow and structural analysis [22]. The present work uses ALE approach has been used which combines the advantage of both Lagrangian and Eulerian approach. Johnson-Cook material model and Johnson-Cook damage model has been widely used by the researchers to finite element modelling on machining. The authors of this work have also used the same combination because the models give very reliable results. AISI 1045 steel has been used for the analysis. The Johnson- Cook model values for the said material is given in Table 1. Table 1. Johnson Cook material and Damage model values[23]. Parameter
Value
A
553.3 MPa
B
600.8 MPa
C
0.013
n
0.0234
m
1
D1
0.06
D2
3.31
D3
-1.96
D4
0.0018
D5
0.058
11782
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
Friction is one of the factors that highly influence such analysis. In this analysis a basic friction model is assumed. Coulomb friction model is being assumed for the current analysis and a friction coefficient of 0.3 is being assumed as the coefficient of friction. The materials properties, along with the friction coefficient that is being used in the analysis is give in Table 2. Table 2. AISI 1045 steel material properties Parameter
Value
Young’s Modulus
210 GPa
Poisson’s Ratio
0.3
Specific heat
432 J/kg/◦C
Thermal Conductivity
47.7 W/m◦C
Density
7800 kg/m3
Friction Coefficient
0.3
2.1. Modelling, Meshing and Loading A 2D thermo-mechanical model is considered for the present work. The work piece was modelled as 4 mm in length and 1 mm in height. Both the tool and work piece were modelled as deformable material. The tool was modelled with both positive rake and negative rake angles and the analysis were done. The meshed model that was used for the simulation along with the loading and boundary condition is shown is Fig.1.
Fig. 1. Meshed Model with Boundary conditions
In order to validate the model the cutting conditions that were used by Tugrul Ozel in his work [24] has been used, the cutting conditions are shown in Table 3. The results obtained using the cutting conditions used in the literature are given in Fig. 2. and Fig. 3. The stress distribution is shown in Fig. 2. and the temperature distribution is shown in Fig. 3. The results are in good agreement with the published results. Table 3. Cutting conditions as per literature. Cutting Condition
Value
Cutting Speed
300 m/s
Feed
0.1 mm/rev
Width of Cut
1 mm
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
11783
Fig. 2. Stress distribution
Fig. 3. Temperature distribution
After validating the model the different cutting condition were used to predict the residual stresses that are induced due the orthogonal machining of AISI 1045 steel. The cutting conditions that were used for the prediction of residual stressed in given in Table 4. Table 4. Cutting conditions for residual stress measurement. Cutting Condition
Value
Speed
100, 200 and 300 m/s
Feed
0.1, 0.15 and 0.2 mm/rev
Width of Cut
1 mm
11784
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
3. Results and discussion Simulation were done using three different cutting speeds and three different feed rates and a constant width of cut, the details of which are given in Table 4. The Force variation is shown in Fig. 4. When the cutting speed was varied in increments of 100 m/s from 100 to 300 m/s. The Von Mises stress that develops during the machining process is shown in Fig. 5.
Fig. 4. Force variation for the different cutting speeds.
Fig. 5. Von Mises stress distribution ( Cutting speed= 100 m/s, Feed = 0.2 mm/rev and width of cut = 1mm).
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
11785
The residual stress was predicted for different cutting conditions. The induced residual stresses were compressive below the surface of the cut work piece for a few microns and thereon it becomes tensile. The trend of the residual shows for cutting speed of 100 m/s , feed of 0.1 mm/rev and width of cut of 1 mm shown in Fig. 6.
Fig. 6. Von Mises stress distribution ( Cutting speed= 100 m/s, Feed = 0.2 mm/rev and width of cut = 1mm).
4. Conclusion A thermo-mechanical model was developed using a commercially available software. The obtained results are in good agreement with the published results. Irrespective of the cutting condition the machining process induced a compressive residual stresses just beneath the cut surface and there upon becoming tensile in nature. The developed model can predict the temperature distribution as well. Under different cutting conditions the maximum temperature that developed the work piece was ranging from 600 to 750 degree Celsius. 5. Future Work The future work involves optimizing the cutting parameters that influence nature and magnitude of the residual stresses. Also the effect of sequential cuts on the machining induced residual stresses. Further research has to be done to determine the effect of the induced residual stresses on the functional performance of the components. References [1] A. Sahraie JahromiB. Bahr, An analytical method for predicting cutting forces in orthogonal machining of unidirectional composites, Composites Science and Technology.70 (2010) 2290-2297. [2] J. C. Outeiro, D. Umbrello, R. M’Saoubi, Experimental and numerical modelling of the residual stresses induced in orthogonal cutting of AISI 316L steel, International Journal of Machine Tools and Manufacture.46 (2006) 1786-1794. [3] B. ZhangA. Bagchi, Finite Element Simulation of Chip Formation and Comparison with Machining Experiment, Journal of Manufacturing Science and Engineering.116 (1994) 289-297. [4] M. R. Movahhedy, M. S. Gadala, Y. Altintas, Simulation of Chip Formation in Orthogonal Metal Cutting Process: An Ale Finite Element Approach, Machining Science and Technology.4 (2000) 15-42. [5] D. Umbrello, L. Filice, S. Rizzuti, F. Micari, L. Settineri, On the effectiveness of Finite Element simulation of orthogonal cutting with particular reference to temperature prediction, Journal of Materials Processing Technology.189 (2007) 284-291. [6] M. A. BalbaaM. N. A. Nasr, Prediction of Residual Stresses after Laser-assisted Machining of Inconel 718 Using SPH, Procedia CIRP.31 (2015) 19-23.
11786
Prakash Marimuthu K et al./ Materials Today: Proceedings 5 (2018) 11780–11786
[7] J. E. WyattJ. T. Berry, A new technique for the determination of superficial residual stresses associated with machining and other manufacturing processes, Journal of Materials Processing Technology.171 (2006) 132-140. [8] Y. M. ArısoyT. Özel, Prediction of machining induced microstructure in Ti–6Al–4V alloy using 3-D FE-based simulations: Effects of tool micro-geometry, coating and cutting conditions, Journal of Materials Processing Technology.220 (2015) 1-26. [9] Y. Choi, A study on the effects of machining-induced residual stress on rolling contact fatigue, International Journal of Fatigue.31 (2009) 1517-1523. [10] T. Shiozaki, Y. Tamai, T. Urabe, Effect of residual stresses on fatigue strength of high strength steel sheets with punched holes, International Journal of Fatigue.80 (2015) 324-331. [11] C. J. LammiD. A. Lados, Effects of residual stresses on fatigue crack growth behavior of structural materials: Analytical corrections, International Journal of Fatigue.33 (2011) 858-867. [12] B. P. Dileep, V. Ravikumar, M. Prashanth, M. V. Phanibhushana, Effect of Zinc coating on Mechanical Behavior of Al 7075, Applied Mechanics and Materials.592-594 (2014) 255-259. [13] A. Laamouri, H. Sidhom, C. Braham, Evaluation of residual stress relaxation and its effect on fatigue strength of AISI 316L stainless steel ground surfaces: Experimental and numerical approaches, International Journal of Fatigue.48 (2013) 109-121. [14] A. Muñoz-Sánchez, J. A. Canteli, J. L. Cantero, M. H. Miguélez, Numerical analysis of the tool wear effect in the machining induced residual stresses, Simulation Modelling Practice and Theory.19 (2011) 872-886. [15] M. N. A. Nasr, E. G. Ng, M. A. Elbestawi, A modified time-efficient FE approach for predicting machining-induced residual stresses, Finite Elements in Analysis and Design.44 (2008) 149-161. [16] M. MandelL. Krüger, FE-simulation of Galvanic Corrosion Susceptibility of two Rivet Joints Verified by Immersion Tests, Materials Today: Proceedings.2 (2015) S197-S204. [17] K. S. Kumar, Numerical Modeling and Simulation of a Butt Joint Welding Of AISI 316L Stainless Steels Using a Pulsed Laser Beam, Materials Today: Proceedings.2 (2015) 2256-2266. [18] T. Mohanavelu, R. Krishnaswamy, P. Marimuthu, Simulation Modeling and Development of Analytic Hierarchy Process (AHP) based Priority Dispatching Rule (PDR) for a Dynamic Press Shop, International Journal of Industrial and Systems Engineering.In Press. [19] M. A. R. Junaidi, N. B. V. L. Kumari, M. A. Samad, G. M. S. Ahmed, CFD Simulation to Enhance the Efficiency of Centrifugal Pump by Application of Inner Guide Vanes, Materials Today: Proceedings.2 (2015) 2073-2082. [20] P. Krishnakumar, K. Prakash Marimuthu, K. Rameshkumar, K. I. Ramachandran, Finite element simulation of effect of residual stresses during orthogonal machining using ALE approach, Int. J. Machining and Machinability of Materials.14 (2013) 213-229. [21] R. Bharathwaj, P. Giridharan, K. Karthick, C. H. Prasath, K. P. Marimuthu, Computational study of Coanda based Fluidic Thrust Vectoring system for optimising Coanda geometry, IOP Conference Series: Materials Science and Engineering.149 (2016) 012210. [22] P. L. Meyappan, Akhila Roy, J. Abhijith, M. N. V. Ramesh, K. Prakash Marimuthu, Tsunami Wave Impact on Structures, International Journal of Applied Engineering Research.10 (2015) 1135-1139. [23] M. N. A. Nasr, Effects of Sequential Cuts on Residual Stresses when Orthogonal Cutting Steel AISI 1045, Procedia CIRP.31 (2015) 118123. [24] T. Ozel, Finite Element Method Simulation of Machining of AISI 1045 Steel With A Round Edge Cutting Tool, Proceedings of 8th CIRP International Workshop on Modeling of Machining Operations.(2005) 533-542.