1. Abstract

In this

investigation, the effect of four controllable input variables of EDM namely: peak

current, pulse on time, pulse off time and gap voltage on surface roughness

(Ra), is investigated. A Box-Behnken design matrix is used to conduct experiments

on Mild Steel using Copper electrode. RSM is used on experimental data to model

the response. Analysis of variance at 95% confidence interval is performed and

significant coefficients are obtained. From the ANOVA results it is observed

that peak current and pulse on time are most significant factors. Optimization

of input parameters is done to obtain minimum Surface Roughness (SR).

2. Introduction

2.1 Principle of EDM

Electrical

Discharge Machining is a non-traditional machining process in which the metal

is removing from the work piece due to erosion case by rapidly recurring spark

discharge taking place between the tool and work piece. There are three phases

occurred in electrical discharge machining process. In the initial phase the

ignition breaks down the high voltage to low. Then the peak current increases

the energy and the material is removed from the workpiece. In the last phase,

plasma channel collapses and flushing flushes away the removed particles. In

EDM the component produced is the exact replica of the electrode. Through EDM complex

shaped products are manufactured that cannot be produced by conventional

method. In this process both the workpiece and the tool have no physical

contact with each other. Both are immersed in the dielectric liquid which also

act as coolant.

2.2 Machining Parameters of

EDM

An

important consideration in Electrical Discharge machining (EDM), like other machining

operations, is the selection of machining parameters/conditions. The important input

parameters that are affecting performance parameters in EDM are (1) Pulse ON

time (2) Pulse OFF time (3) Arc gap (4) Discharge current (5) Voltage (6) Polarity

(7) Duty cycle (8) Diameter of electrode (9) Dielectric fluid

2.3 Performance Parameters of

EDM

The performance

of the electrical Discharge Machining is measured by the parameters as Overcut

(OC), Material Removal Rate (MRR), Tool Wear Rate (TWR) and Surface Roughness (SR).

3. Literature Survey

Balasubramanian and Senthilvelan 1 conducted the experiments on EN8

and D3 steel materials using Cast Copper and Sintered Powder Metallurgy Copper

(P/M Copper) electrodes on EDM. He used the RSM to analyze and optimize the

input parameters. Singh and Singh 2 analysed the effect of different

materials on surface roughness. The result shows that the surface roughness

increases with increasing pulsed current and pulse time. Santoki and Ashwin 3 reviewed the development done in

the EDM & the effects of machining parameters on performance parameters

with various DOE & Optimization Techniques. Kumar, Sivakumar 4 conducted the experiments on AISI

D3 steel using Taguchi’s L18 OA on EDM. The effect of input parameters

including pulse on time, pulse off time, current and voltage on the material

removal rate (MRR) and surface roughness (Ra) was analysed and then optimized. Bhaumik and Maity 5 performed the electrode discharge machining

of AISI 304 stainless steel by using the tungsten carbide electrode in order to

analyse the effect of peak current, pulse on time, gap voltage, duty cycle on surface

roughness (Ra). The effect of significant process parameters on the response

has been studied. Then regression analysis is done and mathematical model is

created to describe the correlation of parameters. The result shows that the

most influential parameter for surface roughness is peak current. Pradhan and Biswas 6 designed a face centred central

composite design matrix and used it to conduct the experiments on AISI D2 tool

steel with copper electrode. RSM is used on experimental data to make the

regression model. It is found that discharge current and pulse duration are

significant factors. Torres, Luis 7 studied the behaviour of input

parameters of current intensity supplied by the generator (I), duty cycle (?),

pulse time (ti), and polarity on INCONEL 600 alloy using electrical discharge

machining (EDM). The experimental results confirm that positive polarity leads

to higher MRR whereas negative polarity leads to lower Ra values. Khan, Rahman 8 studied the surface finish

characteristics of the machined surface in EDM on Ti-5Al-2.5Sn titanium alloy.

central composite design is used to analyze the effects of peak current,

pulse-on time, pulse-off time, servo voltage and electrode material. The result

shows that surface roughness (SR) increases with peak current and pulse-on time

and decreases with servo voltage. Besides, the effect of the process parameters

on surface roughness depends on electrode material.

4. Experimental Details

4.1 Procedure

In this work, experiments

are performed by electrical discharge machining on the mild steel workpiece by

copper electrode in different machining conditions. Experiments are designed in

order to investigate the effect of different input EDM parameters namely

discharge current, pulse ON time, pulse OFF time and gap voltage on the EDM

output parameter of the interest namely surface roughness Ra.

4.2 Machine Tool

A Neu-ar M50

die sinking EDM machine is used. It has Heidenhain EDM controller and 9 sets

coordinate memory. It contains Built-in origin and mold centre setting

function. It has the lowest machining depth display function. And electrode

consumption offset function. Also a built-in residue proofing feature to drive

out carbon residue is present. It is equipped with high precision Heidenhain 1?m

linear encoder. It has durable wear-resistant Teflon Slippery track in “V

shape” and “horizontal track”. It also contains multiple fire- proof detection

system.

Figure 1- Electrical Discharge Machine Model M50

4.3 Material

4.3.1 Workpiece

A square plate

of Mild steel having dimensions 20*12*0.5cm was taken. This has 14.30 g/cm3 of

density, 1240 HV10 hardness, 2597°C of melting point and 420 kgf/mm2 of

compressive strength.

4.3.2 Electrode

A Copper

electrode of cylindrical shape with 10 mm diameter and 100 mm length under

negative polarity was axially mounted within mild steel workpiece. The

properties of Cu electrode used in this work are the following: melting point

of 3500°C and density of 12.6 g/cm3.

4.4 DOE

In order to

reduce the number of experiments due to limited resources, Box-Behnken design

is used. Four factors each at three levels are taken. One block is made having

twenty-four factorial points and six centre points, so the total number of

experiments are 30. Design-Expert 7.0, 2005 is used to make the randomize

design. Machining was carried out to remove approximately 0.5mm from the top

surface. The different levels of factor considered for this study are

illustrated in Table 1.

Table 1 – Factors and Levels

S.No

Input

parameters

Level

Unit

-1

0

1

1

Peak

Current

1

5

9

Amp

2

Pulse

ON time

50

75

100

Microsec

3

Pulse

OFF time

80

100

120

Microsec

4

Gap

Voltage

40

50

60

Volts

4.5 Measurement of Response

Ra is a measure

of the surface finish quality of a product. It is defined as the arithmetic

value of the profile from the centreline along the length.

After

performing the machining operation, the surface roughness of each cut is

measured using a portable stylus type profilometer, Roughness measurement is

done in the traverse direction on the workpiece and the values of Ra parameter

are recorded.

Table 2 – Design Matrix

Run

Ip

Ton

Toff

V

Ra

1

1

50

120

40

2.39

2

1

50

80

40

2.15

3

9

100

120

60

7.08

4

9

100

80

60

7.64

5

9

100

80

40

7.43

6

5

75

100

50

5.41

7

9

50

80

40

6.23

8

1

100

120

40

2.09

9

1

100

80

40

1.65

10

1

100

80

60

1.74

11

9

100

120

40

8.66

12

9

50

120

40

6.01

13

5

75

100

50

5.22

14

1

50

80

60

2.11

15

9

50

120

60

6.24

16

1

100

120

60

2.15

17

5

75

100

50

5.29

18

1

50

120

60

2.45

19

5

75

100

50

5.36

20

9

50

80

60

5.83

21

9

75

100

50

6.48

22

5

75

100

50

5.6

23

5

100

100

50

5.81

24

5

75

100

50

5.53

25

1

75

100

50

1.98

26

5

75

80

50

5.54

27

5

75

100

40

5.97

28

5

75

100

60

5.52

29

5

50

100

50

4.77

30

5

75

120

50

5.77

5. Result and Discussion

5.1

ANOVA

Experiments are conducted to analyze the effect of machining

parameters on surface roughness. Design Expert Software was used to find out

the relationship between the input factors and the response Ra.

To decide the degree of the regression model, the R2 and

R2 adjusted values are summarized in Table 3 for various models. The

table shows that quadratic model is best with R2 = 99% Therefore,

the quadratic model is considered for regression analysis.

Table 3 – R2 and R2 adj test for surface roughness regression

model

Source

Std. Dev.

R-Squared

Adjusted R-Squared

Linear

0.73

0.89

0.87

2FI

0.69

0.92

0.88

Quadratic

0.28

0.99

0.98

Table 4 – Result of the ANOVA table for surface roughness

(Before elimination)

Source

Sum of Square

Df

Mean Square

F Value

p-value

Model

117.06

14.00

8.36

103.65

0.0001

A-Peak Current

102.20

1.00

102.20

1266.89

0.0001

B-Ton

2.05

1.00

2.05

25.37

0.0001

C-Toff

0.35

1.00

0.35

4.37

0.0539

D-Gap Voltage

0.18

1.00

0.18

2.28

0.1517

AB

3.97

1.00

3.97

49.21

0.0001

AC

0.02

1.00

0.02

0.25

0.6231

AD

0.18

1.00

0.18

2.27

0.1530

BC

0.04

1.00

0.04

0.44

0.5192

BD

0.07

1.00

0.07

0.89

0.3612

CD

0.07

1.00

0.07

0.92

0.3526

A^2

3.95

1.00

3.95

48.96

0.0001

B^2

0.08

1.00

0.08

0.98

0.3380

C^2

0.09

1.00

0.09

1.16

0.2977

D^2

0.20

1.00

0.20

2.52

0.1330

Residual

1.21

15.00

0.08

Lack of Fit

1.11

10.00

0.11

5.37

0.0387

Pure Error

0.10

5.00

0.02

Cor Total

118.27

29.00

Table 4 is an ANOVA summary which shows the F and P values for

different terms. The results show that in main effects ‘Voltage’ is

insignificant. Also all the quadratic terms except A2 and AB, are

insignificant. Thus, these terms are eliminated for the further analysis.

After elimination of insignificant terms, ANOVA is performed. The

result of ANOVA is summarized in Table 5. After elimination of non-significant

terms, the values of R2 and R2adj are 98.1% and 97.8%, respectively. The main

and interaction effects, that are significant, are Ip, Ton, Toff, Ip2, and

Ip×Ton.

Table 5 – The ANOVA table for the fitted model

Source

Sum of Square

Df

Mean Square

F Value

p-value

Model

116.07

5.00

23.21

253.78

0.0001

A-Peak Current

102.20

1.00

102.20

1117.25

0.0001

B-Ton

2.05

1.00

2.05

22.38

0.0001

C- Toff

0.35

1.00

0.35

3.86

0.0612

AB

3.97

1.00

3.97

43.40

0.0001

A^2

7.50

1.00

7.50

82.03

0.0001

Residual

2.20

24.00

0.09

Lack of Fit

2.09

19.00

0.11

5.34

0.0361

Pure Error

0.10

5.00

0.02

Cor Total

118.27

29.00

From this analysis, the simplest model obtained is stated in the

following equation.

Ra = 1.605 + 0.8601*Ip – 0.0114*Ton +0.007*Toff – 0.063Ip2

+0.005*Ip*Ton

Normal probability plot of the residuals is displayed in Fig. 2. It

can be seen that the residuals are almost falling on a straight line, which

indicates that the errors are normally distributed.

Figure 2

– Normal probability plot of residuals

Figure 3 – Predicted vs. experimental surface roughness

Fig. 3 depicts the comparison of experimental observations verse

the predicted response values. It can be examined that the regression model

likely fits the experimental values.

5.2 Influence of Input Parameter

On Response

Figure 4 – Effect of factors on Ra

Fig. 4 depicts

the plots of main effects on Ra. The plot shows that peak current is the most

influential factor. As the peak current increases the surface roughness increases

rapidly. Also with the increase in Ton, Ra also increases. Trend for Toff is

same i.e. Ra increases with the increase in Toff.

5.3 Model Graph

Fig. 5 represents contour plot and response surface for Surface

Roughness in relation to input parameters of peak current and pulse ON time. It

can be concluded that the at any value of Ton, the Ra increases rapidly with

the increase in Ip. Hence, in order to obtain minimum Ra, peak current should

be at low level (1A) and pulse on time on (50?s).

Fig. 6, depicts the contour plot and response surface for Ra in

relation to Ip and Toff, where Ton remains constant at the level of 75?s. It

can be seen that, when Ip increases Ra also increases. However, Ra drops slowly

decreases with the increase in Toff at lower Ip, and at higher Ip Ra increases

with Toff. However, the influence of Toff on Ra is very low as compared to Ip

and Ton.

Figure 5 – Contour & Response surface plot depicting the

effect of Ip and Ton on Ra

Figure 6 – Contour & Response surface plot depicting the

effect of Ip and Toff on Ra

Figure 7 – Contour & Response surface plot depicting the

effect of Ton and Toff on Ra

Finally, Fig.7 depicts the contour plot and response surface for Ra

in relation to Ton and Toff, where Ip remains constant at the level of 5 A.

From these plots, it can be concluded for the given range of experiments

conducted for this test, that peak current and pulse ON time are directly

proportional to the Ra and for pulse OFF time the effect is very less as

compared to the other parameters.

6. OPTIMIZATION

EDM is a useful

and valuable tool tom make complex shape parts that cannot be machined by

traditional machining processes. In order to increase the quality and rate of

production, the process parameters have to be optimised. Also, especially in

case of EDM, it is very essential to optimize the input parameters to yield

minimum SR. In single objective optimization only one solution has been

obtained. it has been observed that low Peak current, low Pulse on time, low

pulse off time and marginal Voltage gives minimum Surface roughness.

Table 6 – Optimization Table

S. No

Input /output Parameters

Optimized value

Units

1

Peak current

1

Amps

2

Pulse on time

100

Microsec

3

Pulse off time

80

Kg/Cm2

4

Voltage

56

V

5

Surface Roughness

1.77801

?m

7. Conclusion

In this study

the effect of most significant input parameters of EDM on the surface roughness

has been studied for Mild steel. A Box-Behnken design with factors of discharge

current, pulse on time pulse off time and gape voltage, is used for

experimentation. The ranges of these parameters are chose from the literature

review. Using the Response Surface Methodology (RSM), the regression mode

(quadratic) is formed using the Design-Expert 7.0 software.

The analysis

shows that the output response is significantly affected by the input

parameters of discharge current, pulse on time, pulse off time and gap voltage

with 95% confidence interval. The results also reveal that the value of

discharge current, pulse on time and pulse off time should be set as low as

possible, in order to get a good surface finish on mild steel. For the best

setting of Ra, the discharge current of 1 A, pulse on time of 100?s and off

time should be 50?s, which yields the best value Ra of 1.778?m. The regression

model developed for surface roughness can be effectively used for the optimal

selection of input parameters in EDM to achieve good surface finish for Mild

steel workpiece. These findings will be helpful to manufacturing engineers in

selecting the appropriate parametric combinations for EDM processes to

accomplish desired levels of Ra.

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