Investigation of dry cutting and mist cutting in ball end milling based on response surface analysis

Channarong Rungruang Department of Industrial Engineering

Chulalongkorn University Bangkok, Thailand

chan_pe20@yahoo.co.th

Somkiat Tangjitsitcharoen Department of Industrial Engineering

Chulalongkorn University Bangkok, Thailand

somkiat.ta@chula.ac.th

Abstract— In order to reduce the use of cutting fluid and the environmental hazard, this paper presents the investigation of the machinability of ball-end milling process with the dry cutting and the mist cutting for carbon steel on 5-axis CNC machining center. The relations of the surface roughness, the flank wear, and the cutting parameters, which are the spindle speed, the feed rate, and the depth of cut, are examined and analyzed based on the experimental results by using the Response Surface Analysis with the Box-Behnken design and the analysis of variance. The in-process cutting force is also monitored to analyze the relations of the surface roughness, the flank wear, and the cutting parameters. The dynamometer is installed on the table of 5-axis CNC machining center to measure the in-process cutting forces. The proper cutting condition for the dry cutting and the mist cutting can be determined easily referring to the minimum surface roughness of the surface plot, which is calculated by the surface roughness model obtained from the Response Surface Analysis. The effectiveness of the obtained surface roughness model has been proved by utilizing the analysis of variance at 95% confident level.

Keywords- ball end milling; dry cutting; mist cutting; surface roughness; flank wear; response surface analysis; box-behnken desigh

I. INTRODUCTION In order to realize the waste in the cutting processes, there

has been a continuing worldwide trend to minimize or eliminate the use of cutting fluids. This trend leads to the practice of minimum quantity lubrication (MQL) with major benefits such as reducing the cost of machining operations and the disposal of cutting fluids.

Nowadays, the steel family such as carbon steel (AISI 1050) is most popularly used for the mechanical parts. The ball-end milling process is one of the important cutting processes, which is used to cut those materials in order to obtain the shape as required. However, the tool wear is still the main problems in the ball-end milling process because it deteriorates not only the machined surfaces but also geometry and accuracy as well as causing the low productivity due to the interruptions of the machining operations to change the new cutting tools [1]. Hence, the surface finish of machined part and the tool life of ball end mill is hence considered to determine the suitable cutting condition.

The statistical design of experiment (DOE) has been used in many researches to obtain the optimum cutting condition. The Response Surface Analysis (RSA) is the one method to use in an empirical study of the relationship and the optimization, where several independent variables influence a response [2]. The extensive researches have used the RSA in the metal cutting process to optimize the parameters of the process. Noordin et al. [3] used a Central Composite Design (CCD) to describe the performance of the coated carbide tools in turning process. Alaudin et al. [4] analyze the effect of machining variables influence the life of tooling by response surface methodology. Yang and Tarng [5] applied the Taguchi method to find the optimal solution for turning process. Chiang et al. [6] evaluate the effect of machining parameters in hard turning with ceramic tool based on the response surface methodology. Fuh and Chang [7] used the surface response design to analyze the effect of various work piece materials in the milling operation. Moreover, the response surface methodology is adopted to find the optimal solution in any fields of engineering [8-9]. Therefore, the RSA is adopted in this research to develop the surface roughness and tool wear models by using the Box-Behnken design.

It is already known that the cutting force can be used to examine and analyze the surface roughness, the tool wear and the cutting temperature [10]. The in-process monitoring of cutting forces is hence proposed to investigate the cutting performance of the dry cutting and the mist cutting.

Hence, the aim of this research is to investigate the cutting conditions with the dry cutting and the mist cutting to obtain the proper cutting conditions for the carbon steel with the ball end milling based on the consideration of the surface roughness of the machined parts and the life of the cutting tools by utilizing the response surface analysis (RSA). The DOE is used to prove the main effect of the models with the 95% confident level.

II. EXPERIMENTAL PROCEDURE

A. Equipment and material In this research, the cutting experiments are carried out with

two different cooling strategies, which are the dry cutting and the mist cutting in order to obtain the suitable cutting conditions of them. The cutting tests are performed by using

the coated carbide ball end mills (TiAlN) with the diameter of 6 mm, two cutting edges, 30° helix angle.

The 5-axis machining center of Mazak Variaxis 500 is employed for the cutting tests. The workpiece material is carbon steel (AISI 1050) with the size of 64 mm x 64 mm x 45 mm. The values of cutting parameters are selected from the recommended values in the cutting tool manual [11].

A Castrol clearedge EP 690 is used for the cutting fluid of the wet cutting and mist cutting with a dilution of 6%. It is free from phenol and nitrite, suitable for metal cutting. The coolant is simultaneously applied at the rate of 90 ml/min in the mist cutting with the air pressure of 0.5 MPa. The dry cutting is performed without any air blow or internal cooling system. The limited flank wear (VB) is chosen here to be 0.2 mm. The digital microscope of Keyence (model: VHX 600) is utilized to measure the flank wear of the cutting tool of the coated carbide ball end mill.

The machined surface roughness is measured by using a surface roughness tester (TSK surfcom 1400D-2). The arithmetic mean deviation of surface roughness Ra (µm) with a sampling length lr=2.5 mm (evaluation length ln=12.5 mm) is applied as a surface finish evaluation criterion. The Ra, which is less than 1.6 µm (ISO 4287-1997), will be considered for the proper cutting condition.

A quartz three component tool dynamometer (Kistler 9257B) has been installed onto the table of the 5-axis machining center. The feed direction of the ball end mill is shown in Fig. 1.

B. Experimental design

The response surface analysis (RSA) is employed for the modeling and the analysis of cutting parameters in ball-end milling process in order to obtain the suitable cutting parameters for the minimum surface roughness and the minimum flank wear. The values of the cutting parameters are selected from the recommended values in the cutting tool manual.

Figure 1. Illustration of the experimental setup.

The effects of cutting parameters on the surface roughness and the tool wear which are, the spindle speed, the feed rate, and the depth of cut, are examined and analyzed based on the experimental results by using the response surface analysis with the Box-Behnken design and the analysis of variance (ANOVA). The above three cutting parameters are set as the independent input variables and the responses are surface roughness and the flank wear.

The relationship between the response and the independent input variables can be expressed in the following equation:

Y = F (n, f, d) (1)

where Y is the response and F is the response surface function in the terms of cutting parameters which are the spindle speed (n), the feed rate (f), and the depth of cut (d), respectively.

The approximation of Y is proposed by using the fitted second-order polynomial regression model which is the quadratic model [2]. The quadratic model of Y can be shown as below equation:

Y = β0+Σi βiXi+Σi βijX2i+Σi<j βijXiXj+ε (2)

where β0 is the constant, βi, βii, and βij represent the coefficients of linear, quadratic and cross product terms, respectively. The Xi,i=1,2,3 represent the coded factors that correspond to the cutting parameters.

The values of β coefficients used in the above model can be obtained by using the box-behnken technique. The analysis of variance is utilized to prove the effect of the cutting parameters at the 95% confident level.

The design of experiment has an effect on the number of experiments required. The box-behnken design consists of 15 runs for three variables as shown in Fig. 2, and provides three levels which are low, center, and high for each indenpent variable as shown in Table I.

TABLE I. FACTORS AND LEVELS FOR RESPONSE SURFACE OF THE CUTING PARAMETERS

Parameters Unit Levels-1 0 +1

Spindle speed (n) rpm 8,000 10,000 12,000 Feed rate (f) mm/rev 0.02 0.04 0.06 Depth of cut (d) mm 0.3 0.5 0.7

Figure 2. Box-behnken design for three variables.

TABLE II. DESIGN LAYOUT AND EXPERIMENTAL RESULTS

Run Coded factors Actual factors Response variables Dry cutting Mist cutting

X1 X2 X3 Spindle speed Feedrate Depth of cut Ra (µm) VB (mm) Ra (µm) VB (mm) 1 0 0 0 10,000 0.04 0.5 2.8944 0.14 0.1634 0.10 2 -1 -1 0 8,000 0.02 0.5 1.3471 0.18 0.5417 0.08 3 0 1 -1 10,000 0.06 0.3 1.2335 0.10 0.3950 0.13 4 -1 1 0 8,000 0.06 0.5 0.6441 0.11 0.6398 0.11 5 -1 0 1 8,000 0.04 0.7 1.1884 0.14 0.5126 0.09 6 1 1 0 12,000 0.06 0.5 2.1993 0.11 0.7329 0.09 7 0 -1 1 10,000 0.02 0.7 3.0499 0.14 0.3931 0.08 8 1 0 1 12,000 0.04 0.7 3.5796 0.11 0.4770 0.10 9 1 0 -1 12,000 0.04 0.3 2.4571 0.14 0.2986 0.13

10 0 -1 -1 10,000 0.02 0.3 3.6822 0.18 0.2585 0.09 11 1 -1 0 12,000 0.02 0.5 3.8691 0.14 0.6195 0.09 12 0 0 0 10,000 0.04 0.5 2.1005 0.14 0.3413 0.11 13 0 1 1 10,000 0.06 0.7 1.7253 0.14 0.8121 0.09 14 0 0 0 10,000 0.04 0.5 2.5773 0.13 0.2121 0.09 15 -1 0 -1 8,000 0.04 0.3 1.9080 0.12 0.3576 0.12

III. RESULTS AND DISCUSSION The cutting tests for the dry cutting and the mist cutting are

conducted by using the cutting conditions in the coded form as shown in Table II.

The experimentally obtained results of the surface roughness and the flank wear from the cutting tests are shown in Table II. The experimental data are used for establishing the quadratic models of the surface roughness and the flank wear. The analysis of variance is usually applied to check the effects of the parameters in the models.

A. Effects of cutting parameters on the surface roughness and the flank wear

The in-process cutting forces can explain the relations of the surface roughness, the flank wear and the cutting parameters as shown Figs. 3 to 6.

Fig. 3 shows that the relation between the spindle speed and the cutting force, an increase in the spindle speed, the cutting forces will be decreased because of the softening of material which leads to the lower flank wear [10].

Fig. 4 shows that the effects of the feed rate on the surface roughness in the mist cutting. The surface roughness will be

increased when the feed rate is large which corresponses to the surface roughness theorem. The surface roughness also increases when the cutting time is longer due to the larger flank wear as shown in Fig. 5.

Figure 3. Illustration of the the effect of spindle speed and cutting force in the dry cutting and the mist cutting at the spindle speed of 10,000 rpm.

Figure 4. Example of the experimentally obtained flank wear in the mist cutting at the spindle speed of 10,000 rpm.

Figure 5. Example of the experimentally obtained flank wear in the mist cutting at the spindle speed of 10,000 rpm.

Fig. 6 clearly shows the effect of the depth of cut on the surface roughness in the dry cutting and the mist cutting. For the mist cutting, the surface roughness will be increased on the larger depth of cut, but not in the dry cutting. It is understood that the different depths of cut do not affect the surface roughness in the dry cutting because of the suitable cutting temperature. Since the mist of cutting fluid will reduce the cutting temperature which causes the workpiece harder and difficult to cut. Hence, the surface roughness become higher at the higher depth of cut in the mist cutting.

Figure 6. Illustration of the effect of the depth of cut and the surface roughness in the dry cutting and the mist cutting at the spindle speed of

10,000 rpm.

B. Response surface analysis on surface roughness and tool wear The statistically fitted quadratic models for the surface

roughness and the flank wear are evaluated by the ANOVA with the p-value of and the R2 at the 95% confident level.

The models of the surface roughness and the flank wear for the dry cutting are expressed in (3) and (4) with the R2 of 85.56% and 92.43%, respectively. It is understood that the spindle speed and the feed rate have the significant effect on the surface roughness and the flank wear, while the depth of cut also has the significant effect on the flank wear.

Ra = – 11.7244 + 0.0023n + 60.2684f – 8.2683×10-8n2 – 478.2070f2 – 0.0060nf (3)

VB = 0.2578 + 2.5000×10-6n – 6.1250f + 0.1063d + 0.0003nf – 3.1250×10-5nd + 5fd (4)

For the mist cutting, the models of the surface roughness and the flank wear are shown in (5) and (6) with the R2 of 87.06% and 89.52%, respectively. It is understood that the feed rate and the depth of cut are significant on the surface roughness and the flank wear, while the spindle speed also the significant effect on surface roughness.

Ra = 4.8181 – 8.3230×10-4n – 40.7587f + 0.5719d + 4.1760×10-8 n2 + 569.4130f2 (5)

VB = 0.0021 + 8.1250×10-6n + 5.3509f – 0.17648d – 25.4808f2 + 0.1827d2 – 1.8750×10-4nf – 1.8750fd (6)

The experimentally obtained contour plot of surface roughness and the experimentally obtained surface plot of the flank wear in the dry cutting and the mist cutting are shown in Figs. 7 and 8, respectively.

Fig. 7 shows the effects of the spindle speed and the feed rate on the flank wear in the dry cutting. It is understood that an increase in the spindle speed and the feed rate causes the decrease in the flank wear. While Fig. 8 indicates that the surface roughness will be low if the feed rate is selected at the center and the depth of cut is set at low level.

Referring to the criteria of the minimum surface roughness and flank wear, the suitable cutting parameters are obtained from the (3) to (6), which are the spindle speed of 8,000 rpm, the feed rate of 0.06 mm/rev, at the depth of cut of 0.3 mm for the dry cutting, and the spindle speed of 10,000 rpm, the feed rate of 0.04 mm/rev, at the depth of cut of 0.3 mm for the mist cutting.

Figure 7. Example of the experimentally obtained contour plot of flank wear in the dry cutting.

Figure 8. Example of the experimentally obtained surface plot of surface roughness in the mist cutting.

C. Confirmation test In order to verify the adequacy of the model developed, the

four confirmation experiments are performed. The experimentally obtained results compared with the predicted values for the surface roughness and the flank wear as shown in

Tables III and IV for the dry cutting and the mist cutting, respectively.

The experimentally obtained results show that the percentage error ranges between the actual values and the predicted values for Ra and VB in the dry cutting lie within -5.54% to 7.30% and -7.14% to 9.10%, respectively. For the mist cutting, the percentage error ranges between the actual values and the predicted values for Ra and VB lie within -8.34% to 5.88% and 0.00% to 9.10%, respectively. It is interpreted that the empirical models developed are reasonably accurate and can be used to estimate the surface roughness and the flank wear.

IV. CONCLUSIONS In order to realize the environmental hazard, this paper

presents the models of the surface roughness and the flank wear to obtain the suitable cutting conditions for ball-end milling process with the dry cutting and the mist cutting.

The relations of the surface roughness, the flank wear and the cutting conditions can be well explained by the in-process cutting forces.

The Response Surface Analysis (RSA) with the Box-Behnken design and the ANOVA are utilized to develop the models in the second-order form. The suitable cutting conditions for the dry cutting and the mist cutting can be obtained based on the consideration of the minimum surface roughness and flank wear.

It is proved by the experiments that the proposed and developed quadratic models are reasonably accurate and can be used to predict the surface roughness and the flank wear within the limits of the investigated cutting parameters at the 95% confident level.

ACKNOWLEDGMENT This work was supported by Office of National Research

Council of Thailand, Thailand from October 2008 to September 2010.

TABLE III. THE EXPERIMENTAL RESULTS OF CONFIRMATION TESTS FOR THE DRY CUTTING

No.

Cutting parameters Surface roughness (Ra) Flank wear (VB)

n f d Actual Predicted Error (%) Actual Predicted Error (%)

1 8,000 0.02 0.3 1.5512 1.4379 7.30 0.18 0.19 -5.55 2 10,000 0.04 0.5 2.1426 2.2529 -5.17 0.14 0.15 -7.14 3 12,000 0.06 0.7 1.6511 1.5438 6.50 0.16 0.16 0.00

4 8,000 0.06 0.3 0.3775 0.3984 -5.54 0.11 0.1 9.10

TABLE IV. THE EXPERIMENTAL RESULTS OF CONFIRMATION TEST FOR THE MIST CUTTING

No. Cutting parameters Surface roughness (Ra) Flank wear (VB) n f d Actual Predicted Error (%) Actual Predicted Error (%)

1 8,000 0.02 0.3 0.4317 0.4164 3.54 0.09 0.09 0.00 2 10,000 0.04 0.5 0.2196 0.2376 -8.34 0.11 0.1 9.10

3 12,000 0.06 0.7 0.8542 0.8483 0.69 0.07 0.07 0.00

4 10,000 0.04 0.3 0.1310 0.1233 5.88 0.1 0.12 7.69

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