Analysis the Effect of Process Parameter on EDM of η...

International Journal of Engineering Technology, Management and Applied Sciences

www.ijetmas.com October 2016, Volume 4, Issue 10, ISSN 2349-4476

89 Krishna Kumar Sharma, Sanchaya Goyal, Sanjay Goyal, Gaurav Bhadoria

Analysis the Effect of Process Parameter on EDM of η-WC-

10%Co by Taguchi Method

Krishna Kumar Sharma Sanchaya Goyal Sanjay Goyal Gaurav Bhadoria

M.Tech. Students Asst. Professor Asst. Professor Asst. Professor

MPCT Gwalior MPCT Gwalior MPCT Gwalior Modi University

M.P., INDIA M.P., INDIA M.P., INDIA Niwai, Rajasthan, INDIA

Abstract

In this research paper, attempts have been made for optimizing process parameters in Electro-Discharge Machining

(EDM) of nano tungsten carbide (η-WC-10%CO) using Graphite electrodes to machining mode based on taguchi

techniques. Four independent input parameters discharge current (Amp), pulse-off time (μs), open circuit voltage (Volt)

were selected to assess the EDM process performance in terms of material removal rate (MRR: mm3/min) has been used

to design and examine the experiments. For each process response, a suitable second order decline equation was set up

applying analysis of variance (ANOVA) and student F-test procedure to check modeling goodness of fit and select proper

forms of influentially significant process variables (main, two-way interaction). The MRR increases by selecting higher

discharge current and higher off time which capitals providing greater amounts of discharge energy inside gap region.

In this paper we conduct the experiment on maximum possible combination of process parameter (Discharge current,

Pulse-off time, Open Circuit voltage) developed by taguchi method and find a set of optimal input parameters with

maximum nearby MRR during ED Machining of η-WC-10%CO (nano tungsten carbide-cobalt binder) material.

Key Words:- EDM Process Parameter, η-WC-10%CO, MRR, EWR, Taguchi, ANOVA

1. Introduction

History of electro discharge machining is used from World War I, B. R. Lazarenkoand N. I. Lazarenko

invented the relaxation circuit (RC). There is using a simple servo controller they retained the gap width

between the tool needle and the workpiece, reduced arcing, and made EDM more profitable. Subsequently

1940, die sinking by EDM has been advanced using pulse generator, planetary and orbital motion techniques,

computer numerical control (CNC), and the adaptive control systems. During the 1960s the extensive research

led the progress of EDM when numerous problems related to mathematical modeling were tackled. In 1970s

the evolution of wire EDM was outstanding from the field of powerful generators.

New generation wire electrodes tool done machining with intelligence machining and beater finishing. These

tools having 20 times faster and saving a minimum at least 30% of machining cost.

1.1 Necessity of EDM

In existing times for unusual application with exclusive metallurgical properties, materials – such as steels

tool, stainless steels, alloys based on titanium, alloys based on nickel, tungsten carbide and its composites,

hardened steels and other super alloys, are introduce to fill the demands for severe applications. WC and its

composites materials are tough, hard, low heat sensitive and/or more resistant to corrosion and fatigue, they

are not easy to machine. The application area of these materials are wide such that in the aerospace industry in

defense, in gas & oil industries, and also in the public interests industry. Because of extensively use of

application, the machining of such types of materials is very vital concern in the manufacturing. In view of the

fact that these types of materials have great mechanical properties which can be very valuable in many major

applications. Nano Tungsten carbide (η-WC-10%Co) is an awfully hard material used extensively in

manufacturing for the motive that it’s better wear & tear and corrosion resistance properties. Now a days, WC

and its composite (WC–CO) are of too much effect in the production of special tools, die and cutting tools and

components over a wide variety of temperature because of their high strength, toughness, hardness and wear

resistance. For that reason last few years machining of WC has become one of the most important concerns of

the company. With this investigation we have been accepted out to machine this material with non-traditional

machining process.




Consecutively , electro- discharge machining (EDM) remove the technical difficulties between traditional

machining processes and non-traditional methods.

Following are the advantages of EDM:

Small holes with lean walls and fine structures may be formed.

Irregular shapes are possible.

No effect of hardness of work piece.

The process is free from burr.

2. Literature of review

Electrical Discharge Machining (EDM) - Die Sink is one of the most extensively used non-conventional

material removal processes. Its unique feature of using thermal energy to machine electrically conductive

parts regardless of hardness has been its distinctive advantage in the manufacture of mould, die, automotive,

aerospace and surgical components. In addition, EDM does not make direct contact between the electrode and

the workpiece eliminating mechanical stresses, chatter and vibration problems during machining. [2] Based on

Yussni (2008), the variables parameters are have great effects to the machining performances results

especially to the material removal rate (MRR), electrode wear rate and surface quality. There are two major

groups of parameters that have been discovered and categorized [2]:

A) Non-electrical Parameters

a. Injection flushing pressure

b. Rotational of speed electrode

B) Electrical Parameters

a. Peak current

b. Polarity

c. Pulse duration

d. Power supply voltage

In the other hand, Van Tri (2002) categorized the parameters into five groups: [5]

A) Dielectric fluid; type of dielectric, temperature, pressure, flushing system

B) Machine characteristics; servo system and stability stiffness, thermal stability and accuracy

C) Tool; material, shape, accuracy

D) Workpiece

E) Adjustable parameters; discharge current, gap voltage, pulse duration, polarity, charge frequency,

capacitance and tool materials

Some of the most important parameters implicated in the EDM manufacturing process are the following ones

[2]:

A) On-time (pulse time or ti): The duration of time (μs) the current is allowed to flow percycle. Material

removal is directly proportional to the amount of energy applied during this on-time. This energy is really

controlled by the peak current and the length of the on-time.

B) Off-time (pause time or t0): It is the duration of time (μs) between the sparks (that is to say, on-time). This

time allows the molten material to solidify and to be wash out of the arc gap. This parameter is to affect the

speed and the stability of the cut. Thus, if the off-time is too short, it will cause sparks to be unstable.

C) Arc gap (or gap): It is the distance between the electrode and the part during the process of EDM. It may be

called as spark gap.

D) Duty cycle : It is a percentage of the on-time relative to the total cycle time. This parameter is calculated

by dividing the on-time by the total cycle time (on-time plus off-time). The result is multiplied by 100 for the

percentage of efficiency or the so called duty cycle.

E) Intensity (I): It points out the different levels of power that can be supplied by the generator of the EDM

machine. (I) represents the mean value of the discharge current intensity.




EDM performance, regardless of the type of the electrode material and dielectric fluid, is measured usually by

the following criteria:

a) Metal removal rate (MRR):

Maximum of MRR is an important indicator of the efficiency and cost effectiveness of the EDM process,

however increasing MRR is not always desirable for all applications since this may scarify the surface

integrity of the workpiece. A rough surface finish is the outcome of fast removal rates. [6]

b) Resistance to wear or electrode wear (EW)

The electrode wear also depends on the dielectric flow in the machining zone. If the flow is too turbulent, it

results in an increase in electrode wear. Pulsed injection of the dielectric has enable reduction of wear due to

dielectric flow. [2]

c) Surface Roughness (Ra) of workpiece

The surface produced by EDM process consists of a large number of craters that are formed from the

discharge energy. The quality of surface mainly depends upon the energy per spark.

3. Experimental Details

3.1 Electrical Discharge Machining Condition

Work Condition Description

Electrode Graphite, diameter3 mm, Length 40 mm

Workpiece Tungsten Carbide ceramic,

Discharge Current 3.0 To 55 A

Off time 10 To 1200μs

Open circuit voltage 100 to 200 V

Dielectric Fluid Kerosene

3.2 Taguchi Method

Quality control methodology that combines control charts and process control with product and process

design to achieve a robust total design. It aims to reduce product variability with a system for developing

specifications and designing them into a product or process. Named after its inventor, the Japanese engineer-

statistician Dr. Genichi Taguchi who also developed the quality loss function.

Calculation

The S/N ratio is computed from the mean square deviation (MSD) by the equations:

S/N = - 10 log10 (MSD)

If larger is the best quality characteristic;

MSD = [(1/Y12 + 1/ Y2

2 + ---------------+ 1/ Yn

2)] /N

If smaller is the best quality characteristic;

MSD = [(Y12 + Y2

2 + ----------------+ Yn

2)] / N

Table 1. EDM parameter and their levels for MRR AND EWR

EDM process

parameter

Parameter

Designation

Level

Level 1 Level 2 Level 3

Discharge Current A 3.0 25 55

Off time (µs) 10 400 1200

Open circuit

voltage

V 100 150 200




There are 4 basic types of three level arrays from standard Orthogonal Arrays (OA) from the Genichi Taguchi

parameter design (Genichi Taguchi and Yu –in Wu, Offline Quality control, 1979). An L9 Orthogonal Array is

selected for this research work. The layout of this L9 OA is as mentioned in Table 2.

Table 2. Design layout and experimental result

s.no Discharge

current(A)

Off time

(µs)

Open circuit

voltage(V)

MRR

(mm3/min) TWR(%)

1 3 10 100 0.128 505.217

2 3 400 150 0.04 415.667

3 3 1200 200 0.079 325.550

4 25 10 150 0.46 405.556

5 25 400 200 0.235 337.143

6 25 1200 100 0.191 287.143

7 55 10 200 2.65 326.460

8 55 400 100 1.65 137.360

9 55 1200 150 1.46 87.234

4 Result and Discussion

4.1 Material Removal Rate: MRR Analysis

The performance of each experimental arrangement is evaluated by computing their S/N ratio. In the present

work a software MINITAB -16 is used for the calculation of S/N ratio and ANOVA. The software

MINITAB -16 is first confirmed for its accuracy by matching the results of similar types of problems in the

literature.

Table 3- S/N Ratio for MRR

s.no Discharge

current(A)

Off time

(µs)

Open circuit

voltage(V)

MRR

(mm3/min)

S/N

(MRR)

1 3 10 100 0.128 -18.2477

2 3 400 150 0.04 -27.2238

3 3 1200 200 0.079 -21.6886

4 25 10 150 0.46 -6.16964

5 25 400 200 0.235 -12.3978

6 25 1200 100 0.191 -13.5371

7 55 10 200 2.65 8.554357

8 55 400 100 1.65 4.514697

9 55 1200 150 1.46 3.106269




Table 4- Average S/N Ratio MRR (software MINITAB -16)

55253

0

-10

-20

120040010

200150100

0

-10

-20

Discharge current(A)

Me

an

of

SN

ra

tio

s

Off time

Open circuit voltage(V)

Main Effects Plot for SN ratiosData Means

Signal-to-noise: Larger is better

Fig.1 – Mean effects for SN ratio for MRR

Table 4 shows, The Value of delta of average S/N ratio is maximum for the discharge current is 27.77. On

this behalf, discharge current play a major role in finding the optimum parameter for MRR.

Table 5-The results of ANOVA statistical test performed for MRR

Source DF Seq SS Adj SS Adj MS F-Test P-Value

Discharge current(A) 2 1167.18 1167.18 583.590 89.07** 0.011

Off time(B) 2 71.50 71.50 35.752 5.46* 0.155

Open circuit voltage(V) 2 3.86 3.86 1.930 0.29* 0.772

Error 2 13.10 13.10 6.552

Total 8 1255.65

Level Discharge

current(A)

Off time(µs) Open circuit

voltage(V)

1 -22.38 -5.288 -9.090

2 -10.70 11.703 -10.096

3 5.392 10.706 -8.511

Delta 27.77 6.415 1.585

Rank 1** 2 * 3*




The results are analyzed by using ANOVA in MINITAB16 software. The analysis of variance at 95%

confidence level is given by F test in table 5. The principle of F test is that larger the value of F of parameter

more is the significance of parameter on the MRR. ANOVA table shows that “Discharge current (A)” has the

highest value (F= 89.07). It means tool is the most significant factor for MRR and “Off time (B)” with F=

5.46is second most important factor. From table it is clear that “Open circuit voltage (V)” has least effect on

MRR.

Fig. 2 - MRR with various combination of process parameter

4.2 Electrode Wear Rate: EWR Analysis

Table 6 - Average S/N Ratio EWR (software MINITAB -16)

55253

-44

-46

-48

-50

-52

120040010

200150100

-44

-46

-48

-50

-52

Discharge current(A)

Mean

of S

N ra

tios

Off time(µs)

Open circuit voltage(V)

Main Effects Plot for SN ratiosData Means

Signal-to-noise: Smaller is better

Fig 3- Mean effects for SN ratio for EWR

Level Discharge

current(A)

Off time(µs) Open circuit

voltage(V)

1 -55.22 -52.15 -48.62

2 -50.55 -48.51 -47.74

3 -43.93 -46.04 -50.34

Delta 8.29 6.11 2.60

Rank 1 2 3




The Value of delta of average S/N ratio is maximum for the discharge current is 8.29 for EWR. On this

behalf, discharge current play a major role in finding the optimum parameter for EWR.

Table 7-The results of a ANOVA statistical test performed for EWR

Source DF Seq SS Adj SS Adj MS F- Test P-Value

Discharge current(A) 2 115.29 115.29 57.643 8.63 0.104

Off time(B) 2 56.72 56.72 28.358 4.24 0.191

Open circuit voltage(V) 2 10.52 10.520 5.262 0.79 0.559

Error 2 13.36 13.36 6.682

Total 8 195.89

The principle of F test is that larger the value of F of parameter more is the significance of parameter on the

EWR. ANOVA table shows that “Discharge current(A)” has the highest value (F= 8.63). It means Discharge

Current is the most significant factor for EWR.

Fig. 3- EWR with various combination of process parameter

As par the fig. 2, we find maximum MRR (2.65) from the 7th combination of process parameters at which we

find the value 2.65 and as par fig.3, we find the maximum value of EWR from the 1t h

combination. The Fig.4

shows comparison of MRR with EWR. If we consider the max value of EWR, we find MRR value 0.128,

which is very less as compare with maximum value of MRR. Now, If we choose maximum EWR, we find the

value of EWR is 326.46,which can be consider in compare with maximum EWR. So, now 7th combination is

best combination of process parameters for machining η-WC-10Co on EDM machine as par experiment

conducted.

0

100

200

300

400

500

600

505.217

415.667

325.55

405.556

337.143

287.143326.46

137.36

87.234

EWR

EWR




Fig. 4- Comparison of MRR with EWR

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0

0.5

1

1.5

2

2.5

3

505.217 415.667 325.55 405.556 337.143 287.143 326.46 137.36 87.234

0.128 0.04 0.079

0.460.235 0.191

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EWR

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R 〖𝑚𝑚

〗^3/𝑚

𝑖𝑛




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