Milling analysis by 3D FEM and experimental tests.

Constantin, Corina ; Bisu, Claudiu-Florinel ; Croitoru, Sorin Mihai 等

1. INTRODUCTION

Milling is a common form of machining designated for creating a great variety of surfaces. It becomes very important to have an approach for predicting cutting forces, chip formation, thermal aspects, etc. The importance comes from the necessity of using optimum technological parameters for processing by milling different materials, and also for determining loads (forces and torque) during operation. They are useful for tool designing and also in tool functioning (damage and wear rate). The analysis by FEM modelling and simulation becomes very powerful in this field. It still needs for the confirmation of the method the support of experimental tests for validation.

Finite Element Method (FEM) permits prediction of cutting forces, stresses, tool wear, and temperatures of the cutting process so that the cutting tool can be designed. FEM has some advantages such as (Kirichek & Afonin, 2007 ): solves contact problems, uses bodies made from different materials, a curvilinear region can be approximated by means of finite elements or described precisely etc. There are two types of finite element formulations to describe a continuous medium: Lagrangian and Eulerian (Bareggi & O'Donnell, 2007). Based on the success of FEM simulations for different processes, many researchers developed their own FEM codes to analyze metal cutting processes (Cerenitti et al., 1996).

Applications of FEM models for machining can be divided in six groups: tool edge design, tool wear, tool coating, chip flow, burr formation plus residual stress, and surface integrity (H. Yanda et al., 2009).

The right choice of finite element software is very important in determining the scope and quality of the analysis that will be performed. The most important software codes used for simulation of metal cutting are: Abaqus, Deform 2D and 3D (Uhlmann et al., 2007), and AdvantEdge.

In this paper the Deform 3D commercial software is used to simulate the milling process (www.custompartnet.com).

2. FEM ANALYSIS AND EXPERIMENTAL

VALIDATION

The FEM analysis consists of three steps: pre-processor, simulation and post-processor (Deform 3D-V6.1, User's Manual). In the pre-processor the initial data for modelling and simulation must be set. The process parameters and cutting conditions are described in Table 1. The next steps are tool and workpiece setup, material choice, and mesh generation. For the studied process, a milling tool Sandvik R365-080Q27-S15M (www.sandvik.com) of 80 mm diameter with inserts was designed in Aut [degrees]AD and then imported in the software. $$ The software generates a workpiece based on the properties presented in Table 2. The tool is made of WC and the workpiece material is AISI1045 (Steel).

The mesh generation is very important for accuracy of the simulation. The mesh is reformulated at nearly every time step, in order to manage the material deformation. Fig. 1 shows an example of deformed workpiece mesh for the milling process.

The end of the pre-processor step contains the simulation controls and data base generation (Table 3). After completing these steps, the database can be generated. At this step, the simulation can be started. The simulation initiates a series of operations and generates a new mesh if necessary.

The last step is the post-processor. The user can check and use the simulation results after the data extraction.

The most important data obtained from the FEM simulation are: geometry of workpiece and tool after the simulation; tool movements and deformed mesh at each saved step (Fig. 1); distribution of state variables: stress, strain, temperature, wear, damage (Fig. 2); displacement and velocity; chip formation; predicted cutting forces and torque (Fig. 3).

[FIGURE 1 OMITTED]

For an assessment of the cutting simulations, experimental tests have been carried out. The experimental setup consisted of a vertical machining centre FIRST MCV 300, a Kystler dynamometer, an amplifier connected to the computer acquisition motherboard, a workpiece of pre-shaped of AISI 1045 steel and a Sandvik R365-080Q27-S15M milling head.

The cutting conditions were the same as those presented in Table 1. The difference between the simulation and experiment was the following: the simulation was conducted with a tool with one tooth and the tool used in experiments had 6 teeth.

The measured cutting forces are presented in Fig. 4: the feed force [F.sub.X] = 50 N, cutting force [F.sub.Y] = 110 N and axial force [F.sub.Z] = 60 N.

To be able to compare the calculated cutting forces with the measured ones, the user had to determine the simulated specific cutting forces. For this, the integral average was computed. After that, the quotient of the integral and the time fragment was calculated. The simulated and the measured cutting forces show small differences; this can be ascribed to problems concerning the model.

[FIGURE 2 OMITTED]

[FIGURE 3 OMITTED]

[FIGURE 4 OMITTED]

Besides model improvement, also the model validation vill have in view the friction parameter establishing for different tool-part material couples in high speed.

As a future research goal we can mention the use of 3D FEM analysis for inverse simulation to deduce the Johnson-Cook parameters that describe the material law (Shrot & Baker, 2010) used in machining simulation for high speed processes. This will be done on the basis of the adiabatic stress-strain curves obtained by FEM.

3. CONCLUSION

This paper proposed an overview of the approach of FEM analysis of a milling process considering 3D modelling and also an experimental validation. The simulation was conducted with a single tooth tool and the program generated the workpiece. The tool used in the experiment was a Sandvik milling tool with 6 inserts. The experimental results validate in a largely way the measured cutting forces but for a better agreement the model can be improved. Building improved models and further experiments on different materials will be among the main tasks for further work including material law parameter finding.

4. ACKNOWLEDGEMENTS

The work has been funded by the Sectoral Operational Programme Human Resources Development 2007-2013 of the Romanian Ministry of Labour, Family and Social Protection through the Financial Agreement POSDRU/88/1.5/S/61178.

5. REFERENCES

Bareggi A.; O'Donnell G.E. (2007). Modelling Thermal Effects in Machining by Finite Element Methods, Proceedings of the 24th International Manufacturing Conference, Vol. 1, 2007, pp. 263-272

Cerenitti E.; Fallbohmer P.; W.T. Wu & Altan T. (1996). Application of 2D FEM to Chip Formation in Orthogonal Cutting, Journal of Material Processing Technology, Vol. 59, 1996, pp. 169-180

Hendri Y.; Ghani J. A.; Hassan C. & Haron C. (2009). Effect of rake and clearance angles on the wear of carbide cutting tool, Eng. e-Transaction, Vol. 4, No. 1, 2009, pp. 7-13

Kirichek A.V.; Afonin A.N. (2007). Stress-Strain State of the Thread-Milling Tool and Blank, Russian Engineering Research, Vol. 27, No. 10, 2007, pp. 715-718

Shrot A.; Baker M. (2010). Is it possible to identify Johnson-Cook law parameters from machining simulations? Int J Mater Form, Vol. 3, Suppl 1, 2010, pp. 443-446

Uhlmann E.; Graf von der Schulenburg M.; Zettier R. (2007). Finite Element Modelling and Cutting Simulation of Inconel 718, Annals of the CIRP, Vol. 56, No. 1, 2007, pp. 61-64

*** Deform 3D-V6.1 User's Manual

*** www.custompartnet.com, Accessed on: 2010-08-20

*** www.sandvik.com, Accessed on: 2010-07-27

Tab. 1. Process and condition setup

Process and condition parameters Milling

Cutting speed 75.36 m/min
Feed 2.4 mm/sec
Depth of cut 0.5 mm
Shear friction coefficient 0.5
Interface heat transfer coefficient 45[degrees]C
Convection coefficient 0.02
Environment temperature 20[degrees]C

Tab. 2. Workpiece properties

Workpiece parameters

Geometry Modelled as plastic
Length 20mm
Material AISI1045 (Steel)

Tab. 3. Simulation controls

Simulation controls

Nr. of steps 10 000
Steps to save / steps def. 25
Tool wear calculation Usui's Model: