____________________ * Corresponding author: University of Brescia - Dept. of Mechanical & Industrial Engineering Via Branze 38, 25123 Brescia ITALY, phone: +39-030-3715584, fax: +39-030-3702448, attanasi@ing.unibs.it

ABRASIVE AND DIFFUSIVE TOOL WEAR FEM SIMULATION

A. Attanasio1*, D. Umbrello2

1University of Brescia - Dept. of Mechanical & Industrial Engineering - Italy 2University of Calabria - Dept. of Mechanical Engineering - Italy

ABSTRACT: In this paper, an adopted abrasive-diffusive wear model is proposed and implemented into a 3D Finite Element code to study the tool wear phenomenon. In particular, the Authors found that FE procedure based only on diffusive mechanism shown some problems when the extension on crater area was investigated. This can be related to the absence of the wear abrasion term on the utilized model. Therefore, in this work, the Authors improved the previous utilized tool wear model introducing into the sub-routine the abrasive term on the basis of Usuis model. A series of 3D FEM simulations were conducted in order to estimate the tool wear development in turning operations. The adopted abrasive-diffusive wear model will give the possibility of correctly evaluating the tool wear of actual turning operations during both the initial transient phase, where the abrasive mechanism is dominant, and the steady-state phase, in which the diffusion is the main wear mechanism. The FEM results were compared with experimental data, obtained turning AISI 1045 steel with WIDIA P40 inserts, showing a satisfactory agreement.

KEYWORDS: Cutting, Tool wear, 3D FEM 1 INTRODUCTION Tool wear is widely considered as one of the most important aspects causing poor quality of worked piece in cutting. Consequently tool wear prediction and tool substitution policy are regarded as very important tasks in order to maximize tool performance and minimize cutting costs. For this reason a relevant number of papers on tool wear can be recognized in literature [1-4]. In particular, according the technical literature, several wear mechanisms can be defined, namely abrasion (related to thermo - mechanical action), adhesion (related to micro welding and Built Up Edge formation and removal), diffusion (chemical alteration due to atomic migration at high temperature), and fatigue. The above phenomena are generally present in combination, even if only one or few of them result to be dominant as the cutting conditions, and consequently contact pressure and temperature, and the workpiece and tool materials change. Many efforts have been made in describing, through analytical models, the various wear mechanisms as function of process parameters [4-6], tool material and geometry and workpiece material [1, 2]. In contrast, only few regard the simulation of tool wear [7, 8] especially when 3D simulation is used [9] and within these, the utilized tool wear models were focused on some of the main wear mechanisms only. From a theoretical point of view, this assumption can be done when the implemented tool wear mechanism results very predominant respect to the other ones. In fact, as it is

well known diffusive wear mechanism [4] becomes predominant when low carbon steels are machined using uncoated WC tools and the temperatures higher than 700-800C are reached [10]. In contrast, when tool materials and workpiece are selected, abrasion wear mechanism [6] results predominant in the transient phase and in the steady-state region [9] where temperatures are lower than 700C. Therefore, in order to supply results more closer to the industrial needs (by covering a large range of situations and not only particular conditions), it is desirable to develop a 3D FE models able to simulate tool wear phenomena that take into account different tool wear mechanisms. The present paper was developed according to the described strategy. In fact, both abrasive and diffusive wear mechanisms were implemented into the 3D FE software adopting both abrasive and diffusive wear models. As shown in Figure 1, when the temperature of the tool rake surface is lower than the activation temperature of the diffusive phenomenon (light grey area in Figure 1), the wear rate is estimated applying the abrasive model proposed by Usui in [6]. Differently, in the tool area where the temperature is higher than the diffusive activation temperature (dark grey area in Figure 1) the wear rate is evaluated applying the equation describing the diffusive model [4, 9]. Moreover, a new 3D updating procedure for the dynamic prediction of the tool wear was developed. Finally, a series of three dimensional experimental tests was carried out in order to validate the simulation strategy.

Abrasive wear modelT700C

Diffusive wear modelT>700C

Figure 1: Tool wear model as function of tool temperature

2 3D EXPERIMENTAL TESTS Cylindrical bars with a diameter of 100 mm were cut using uncoated ISO P40 inserts with tool nose radius of 0.8 mm and clearance angle () of 6. Furthermore, the inserts was positioned into a tool holder in order to obtain a rake angle () of 0, an inclination angle () of 7 and, finally, an entering angle () of 90, as illustrated in Figure 2.

Figure 2: The experimental set-up for 3D tests

Figure 3: Observed flank (a) and crater wear (b) after 4 minutes (Vc=160m/min f=0.25 mm/rev)

Two tests were run changing the cutting velocity (between two values, namely 150 and 160 m/min) and the feed rate (also in this case between two values, namely 0.17 and 0.25 mm/rev). The depth of cut was fixed to 1.5 mm and the cutting operations were conducted in dry conditions. Both flank and crater wear were measured at different cutting times, using an optical microscope (50X) equipped with a motorized faceplate. All the experiments were repeated three times showing an uncertainty of +/- 6-10% (95% confidence interval). Figure 3 shows the typical flank and crater wear observed during the 3D cutting operations; while

Table 1 reports average tool wear data for the 3D experiments.

Table 1: Experimental tool wear in 3D cutting

VC m/min

f mm/rev

Time min

VB mm

KM mm

KT mm

1 0.134 0.389 0.027 2 0.148 0.476 0.038 4 0.184 0.554 0.074

150 0.17

6 0.199 0.497 0.095 1 0.122 0.548 0.02 2 0.143 0.558 0.048 4 0.194 0.686 0.099

160 0.25

6 0.247 0.693 0.110 3 3D NUMERICAL MODELLING 3.1 3D FE MODEL The 3D model, implemented in Deform 3D v6.1, is reported in Figure 4 where it is possible to see the workpiece with the growing chip and the tool. The tool, a rigid object meshed with more than 100,000 elements, is oriented according to the cutting angles set in experimental test and reported in Table 2 and it moves along a linear direction. The workpiece, considered as a rigid-plastic object meshed with more than 45,000 elements, is fully constrained on the lower and lateral sides so it cannot move.

Figure 4: The 3D model

On the same faces thermal boundary conditions are set to simulate the heat diffusion. The characteristic parameters set for both the tool and the workpiece are reported in Table 2. The friction was modelled considering a shear factor equal to 0.82. Finally, a physically-based model was adopted to describe the heat global exchange, h, at the tool-chip-workpiece interfaces. In particular, Attanasio et al. [9] related the coefficient h to the cutting parameters (cutting speed ,VC, and feed rate, f):

22CC f40600V0.0276f7950V2.36442h ++= (1)

and demonstrated the effectiveness of temperature predictions.

a) b)

Table 2: Geometry and material data

Parameter Values Tool angle 0 angle 7 angle 90 Material WC Conductivity [W/m K] 69 Heat Capacity [J/m3 K] 3.8106 Emissivity 0.45 Workpiece Material AISI 1045 (Oxley equation) Conductivity [W/m K] Function of temperature Heat Capacity [J/m3 K] Function of temperature Emissivity 0.75 3.2 3D SIMULATIVE STRATEGY The adopted simulation strategy is schematized in the flow chart of Figure 5. The iterative part of the simulation strategy allows to represent the wear development and growth in the FEM model.

Machining Steady-State (ALE)

Incremental Lagrangian Model

Force Steady State

Temperature Steady State

Wear Calculation Subroutine

Incremental Lagrangian Model

Time=tend?

Force and Temperature Steady State

End

No

Time=Fixed t

Yes

Figure 5: 3D simulation strategy

Before to apply the tool geometry updating procedure it is necessary to reach the thermo-mechanical steady state. In fact, as already discussed, temperature, pressure and sliding velocity at the interface between tool and chip are the parameters utilized for calculating the tool wear. So, a correct evaluation of their distribution and values on the insert rake and flank surfaces is fundamental for a correct tool wear analysis. For this reason an updated Lagrangian formulation, which allows to reach the mechanical steady state, is followed by an Eulerian formulation run for reaching the thermal steady state. By means of this simulation strategy the thermo-mechanical steady state is achieved in a shorter simulation time. The output database of the ALE simulation is the starting database for the tool wear simulation. As described in the loop of Figure 5, it consists of consecutive Lagrangian simulations, followed by the

application of the implemented wear subroutine and run for a constant simulation time t (1 minute) until reaching the total simulation time. Before applying the tool geometry updating sub-routine it is necessary to run the Lagrangian simulation in order to identify the correct temperature and force distributions as the tool wears. In fact, the tool wear sub-routine changes the tool geometry and this causes a change to temperature, pressure and sliding velocity distribution and values. The subroutine for tool geometry updating consists of three phases. In the first phase the tool wear rate is calculated, according to the adopted combined abrasive and diffusive wear model, for each node of the tool mesh boundary in contact with the chip. After that, the sub-routine identifies the mesh nodes movement direction finding, for each identified node, the connected elements and determining the values of their three versor components. At this point, the node movement direction is obtained as vectorial sum of all the vectors of the connected elements. The third phase initially updates the tool mesh moving each boundary mesh node along the corresponding movement direction for a distance equal to the calculated wear. After that the software rebuilds the tool geometry starting from the worn mesh. 4 RESULTS DISCUSSION The results provided by the 3D simulation strategy for tool geometry updating were compared with the experimental ones in order to validate the 3D FE model and simulation strategy. The attention was focused on crater and flank wear prediction at the varying of cutting velocity and feed rate for different cutting times. Figure 6 shows the worn tool geometry as calculated by the above described procedure. In particular, a section of the tool is reported and the simulated tool wear after 6 minutes of cut with a cutting speed of 160 m/min and a feed rate of 0.25 mm/rev is presented (VB: flank characteristic parameter; KT and KM: crater characteristic parameters).

A

A

A-A

VB

KM

KT

Figure 6: Worn tool with flank and crater wear parameters (VB, KT-KM).

Figure 7 reports the trend of simulated and experimental crater wear (KT/KM) for the analyzed cases at different cutting times. Observing these results it is evident the good agreement.

0.00

0.05

0.10

0.15

0.20

0 1 2 3 4 5 6

Flan

k To

ol w

ear,

VB [m

m]

Cutting Time [min]Vc=150m/min - f=0.17mm/rev - EXPVc=150m/min - f=0.17mm/rev - NUMVc=160m/min - f=0.25mm/rev - EXPVc=160m/min - f=0.25mm/rev - NUM

Figure 7: Simulated and experimental crater wear as function of cutting time

Furthermore, a better crater extension was obtained using this adopted abrasive-diffusive wear model (Figure 8a) instead of that observed when only the diffusive wear mechanism was implemented (Figure 9b). Therefore, as the present Authors stated in a recent work [12], both the wear mechanisms (i.e. abrasion and diffusive) must be considered and implemented in order to obtain a good prediction of crater extension.

Figure 8: Experimental and simulated crater wear: a) with the adopted abrasive-diffusive wear model b) only diffusive wear implemented; (VC=160m/min, f=0.25mm/rev, cutting time=6min)

0.00

0.05

0.10

0.15

0.20

0.25

0 1 2 3 4 5 6

Flan

k To

ol w

ear,

VB

[mm

]

Cutting Time [min]

Vc=160m/min - f=0.25mm/rev - EXPVc=160m/min - f=0.25mm/rev - NUM

Figure 9: Simulated and experimental flank wear as function of cutting time (VC=160m/min, f=0.25mm/rev)

Finally, Figure 9 shows the trend of simulated and experimental flank wear only for the case 160 m/min 0.25 mm/rev at different cutting times. It is important to

underline that it was not possible to define the flank wear for the second test. This is because the FEM software showed some limits in the correct definition of the tool-workpiece contact points along the tool flank surface. As observable in Figure 9 the results are satisfactory, even if improvements should be obtained calibrating the abrasive model parameters by means of specific experimental test and developing an ad-hoc sub routine for contact estimation.

5 CONCLUSIONS The paper reports the results obtained simulating the tool wear development using a 3D FE model. In particular, a new subroutine for tool wear calculation and tool mesh and geometry updating was implemented in a commercial 3D code. The obtained results showed a good agreement with the experimental tests proving the reliability of the developed procedure. For the future, new efforts will be spent to improve the flank wear prediction by developing an ad-hoc sub routine for contact estimation. REFERENCES [1] V.P. Astakhov. The assessment of cutting tool wear.

Int. J. Mach. Tools Manuf., 44: 637-647, 2004. [2] C.Y.H. Lim, S.H. Lim, K.S. Lee. Wear of TiC-

coated carbide tools in dry turning. Wear, 225-229: 354-367, 1999.

[3] R. Ghosh, P.X. Li, X.D. Fang, I.S. Jawahir. An investigation of the effects of chip flow on tool-wear in machining with complex grooved tools. Wear, 184/2:145-154, 1995.

[4] H. Takeyama, T. Murata. Basic investigations on tool wear. Trans. of the ASME - J. Eng. Ind., 85: 33-38, 1963.

[5] S. Shimada, H. Tanaka, M. Higuchi, T. Yamaguchi, S. Honda, K. Obata. Thermo-chemical wear mechanism of diamond tool in machining of ferrous metals. Annals of CIRP, 53/1: 57-60, 2004.

[6] E. Usui, T. Shirakashi, T. Kitagawa. Analytical prediction of three dimensional cutting process. Part 3. Cutting temperature and crater wear of carbide tool. Trans. ASME, 100: 236243, 1978.

[7] L. Filice, D. Umbrello, F. Micari, L. Settineri. Wear modelling in mild steel orthogonal cutting when using uncoated carbide tools. Wear, 262/5-6:545-554, 2007.

[8] K.-D. Bouzakis, I. Mirisidis, E. Lili, N. Michailidis, A. Sampris, G,.Skordaris, G. Pavlidou Erkens, I. Wirth. Impact resistance of PVD films and milling performance of coated tools at various temperature levels. Annals of CIRP, 55/1: 67-70, 2006.

[9] A. Attanasio, E. Ceretti, S. Rizzuti, D. Umbrello, F. Micari. 3D Finite Element Analysis of Tool Wear in Machining. Annals of CIRP, 57/1: 61-64, 2008.

[10] P. Mathew. Use of predicted cutting temperatures in determining tool performance. Int. J. Mach. Tools Manuf., 29/4:481-497, 1989.

a) b)