Tool shear strees and temperature distributions prediction using FEM simulation.

Patrascu, Gabriela ; Carutasu, Nicoleta Luminita

1. INTRODUCTION

Computer simulation has been an expanding field being used in research studies and increasingly used in industrial applications for tool wear (Carutasu 2007). Many companies have software on the market to simulate tool wear for a wide variety of machining operations. These simulations provide information on how the cutting tool will react and respond to the workpiece properties. The simulation outcome depends largely on the model and laws it follows (Oxley 1998).

Many of the simulations use finite element analysis as a base to evaluate the phenomena (Jawahir 1991).

In the recent decades, with the emergency of more and more powerful computer and the development of numerical technique, numerical methods such as finite element method (FEM), finite difference method (FDM) and artificial Intelligence (AI) are widely used in machining industry (Kalhori 2001). Among them, FEM has become a powerful tool in the simulation of cutting process because various variables in the cutting process such as cutting force, cutting temperature, strain, strain rate, stress, etc can be predicted by performing chip formation and heat transfer analysis in metal cutting, including those very difficult to detect by experimental method (Huang et. al., 2003). Therefore a new tool wear prediction method may be developed by integrating FEM simulation of cutting process with tool wear model (Jawahir et. al., 1993).

Cutting tools are subjected to an extremely severe rubbing process. They are in metal-to-metal contact, between the chip and work piece, under conditions of very high stress at high temperature. The situation is further aggravated due to the existence of extreme stress and temperature gradients near the surface of the tool.

Interfacial friction on the tool rake face is not continuous and is a function of the normal and frictional stress distributions.

According to Zorev, the normal stress is greatest at the tool tip and gradually decreases to zero at the point where the chip separates from the rake face. The frictional shearing stress distribution is more complicated. Over the portion of the tool-chip contact area near the cutting edge, sticking friction occurs, and the frictional shearing stress is equal to the average shear flow stress at tool-chip interface in the chip. Over the remainder of the tool-chip contact area, sliding friction occurs, and the frictional shearing stress can be calculated using the coefficient of friction.

2. CASE STUDY

This paper presents the current modelling capabilities available in AdvantEdge 4.5 software to simulate metal cutting environment in turning process.

AdvantEdge machining modelling software is a central difference explicit finite element code using a Lagrangian mesh. The material model accounts for elastic-plastic strains and has an isotropic power law for strain hardening. The strain rate also affects the flow stress.

The material properties are temperature dependent and thereby it also accounts for thermal softening. A staggered method for coupled transient mechanical and heat transfer analysis is utilized. First an isothermal mechanical step is taken followed by a rigid transient heat transfer step with constant heating from plastic work and friction. Both steps have identical meshes. The central difference scheme is also used for the time integration in the thermal analysis. A six-node quadratic triangle element is used. The mesh, which becomes much distorted around the cutting edge, is periodically updated both refining large elements and coarsening small elements.

For turning process simulation it was used a plane strain deformation model. The insert and a part of work piece were meshed in order to have a practical number of elements for calculations. Work piece was made of Romanian OLC45 steel (AISI 1045). The TNMG 332 insert with PF chip breaker geometry (figure 1) were made available in STL form, generated from CATIA V5R8 system (Patrascu, 2007).

The cutting process parameters were:

* Cutting depth: 0.635 mm.

* Feed: 0.254 mm/rot.

* Cutting speed: 200 ... 400 m/min.

For the proposed orthogonal machining model, cutting conditions and the material properties of the workpiece are the inputs. The outputs are process related variables, such as tool stress distributions, tool wear and temperature distribution in the chip and along the tool-chip interface (Patrascu, 2007).

[FIGURE 1 OMITTED]

[FIGURE 2 OMITTED]

[FIGURE 3 OMITTED]

Our FEM results provided a good estimation of temperature and shear stress values. The simulation is good for observing the influence of cutting conditions (speed, feed and depth of cut) and tool geometry. Comparison of computed values and the values from other studies on shear stress and temperature show a good agreement, even if FEM results overestimate the temperature levels.

The FEM results indicate a greater region of the tool to be above 1100[degrees]C, and maximum shear stress above 4900 MPa.

The results of our study prove the effectiveness of FEM simulation of turning process in order to select the optimum cutting process parameters.

3. CONCLUSION

This paper introduces a predictive modelling technique to determine forces, stresses, and temperature distributions in machining while considering influence of tool flank wear. The technique introduced in this paper combines oblique moving band heat source theory with nonuniform heat intensity at tool-chip interface and modified Oxley's parallel shear zone theory with ploughing effects due to tool flank wear to predict cutting forces, stress, and temperature distributions.

The proposed technique has been applied to machining of AISI-1045 steel using a carbide tool, and promising results have been obtained. The results have helped explain the heat partition behaviour of the tool-chip and tool-workpiece interfaces as width of flank wear increases.

Further studies are underway for improving the model to study the effects of chip-groove parameters on the natural contact length, fracture, the tool temperature and contact stress distribution, etc.

Acknowledgments: The authors would like to thank Prof. Jawahir I.S. from University of Kentucky for his support and Mr. Luis Zamorano--Applications Engineer from Third Wave Systems for the use of five months free evaluation license of AdvantEdge 4.5 software and for his support in using this license.

4. REFERENCES

Carutasu, N.L. (2007). Contribution Regarding Designing Machines-Tools Structure Elements for High Speed Machining, Ph.D. Thesis, University POLITEHNICA of Bucharest, Bucharest, Romania.

Huang, Y., & Liang, S.Y. (2003). Modelling of the Cutting Temperature Distribution Under the Tool Flank Wear Effect, Proc. Inst. Mech. Eng., Part C: J. Mech. Eng. Sci., 217, pp. 1195-1208.

Jawahir, I.S. (1991). An Investigation of Three-Dimensional Chip Flow in Machining of Steels with Grooved Chip Forming Tool Inserts, Transactions of NAMRI/SME, Vol. XIX, pp. 222-231, 1991.

Jawahir, I.S. & van Luttervelt, C.A. (1993). Recent Developments in Chip Control Research and Applications, Annals of the CIRP, Vol. 42 (2), 1993, pp. 659-693.

Kalhori, V. (2001). Modelling and Simulation of Mechanical Cutting, Ph.D. Thesis, Lulea University of Technology, Sweeden.

Oxley, P. (1998). Development And Application Of A Predictive Machining theory, Proc. CIRP International Workshop on Modeling of Machining Operations, Atlanta, GA, USA, May 1998, ISBN 0-9666706-0-4, University of Kentucky.

Patrascu, G. (2007). Research Concerning the Optimization Through Simulation of the Cutting Process, Ph.D. Thesis, University POLITEHNICA of Bucharest, Bucharest, Romania.