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Pushpendra.S.Bharti. et. al. / International Journal of Engineering Science and Technology

Vol. 2(11), 2010, 6464-6473

EXPERIMENTAL INVESTIGATION OF

INCONEL 718 DURING DIE-SINKING

ELECTRIC DISCHARGE MACHININGPUSHPENDRA S BHARTI*

Research Scholar, University School of Engineering and Technology,

Guru Gobind Singh Indraprastha University, Delhi-110006, India

S. MAHESHWARIManufacturing Process and Automation Engineering Division,

Netaji Subhas Institute of Technology, Delhi, India

C. SHARMADepartment of Mechanical and Automation Engineering,

Indira Gandhi Institute of Technology, Delhi-110006, India

Abstract:

This work investigates the machining characteristics of Inconel 718 during die-sinking electric discharge machining

process with copper as tool electrode. Experiments have been carried out to see the effects of input parameters like

shape factor, pulse-on-time, discharge current, duty cycle, gap voltage, flushing pressure and tool electrode lift time

on performance measures like material removal rate, surface roughness and tool wear rate. Taguchis method has

been used as Design of Experiments technique for experimental investigation. Experiments have been designed asper Taguchis L36 orthogonal array. Analysis of variance (ANOVA) is employed to indicate the level of

significance of machining parameters. Discharge current and pulse-on time are found the most influential common

input parameter on each performance measure. Duty cycle and tool electrode lift time are found the least influentialparameters.

Keywords: Electric-discharge machining(EDM); Material removal rate(MRR); Surface roughness (SR);Tool wear rate (TWR); Taguchis Method; Design of experiments (DOE); Inconel 718.

1. Introduction

Nickel based super alloy are extremely useful in gas turbine, space vehicles, aircraft, nuclear reactors, submarine,petrochemical equipments and other high temperature applications. Inconel 718, a nickel based super alloy, is a

precipitation-hardenable nickel-chromium alloy containing significant amounts of iron, niobium, and molybdenum

along with lesser amounts of aluminum and titanium. It combines corrosion resistance and high strength with

outstanding weldability, including resistance to post weld cracking. The alloy has excellent creep-rupture strength at

temperatures up to 700 C (1300 F). Owing to its excellent mechanical and metallurgical properties this alloy finds

extensive use in gas turbines, rocket motors, spacecraft, nuclear reactors, pumps and tooling. Its outstanding hightemperature strength and toughness create difficulties during machining due to its work hardening tendency. Inonel

718 is one of the most difficult-to-machine super alloys in order to satisfy production and quality requirement. Thisdifficulty in machining is attributed to its ability to maintain hardness at elevated temperature which otherwise isvery useful for hot working environment. Formation of complex shapes by this material along with reasonable speed

and surface finish is not possible in traditional machining. Therefore, EDM is one of the most suitable processes to

shape this alloy. This alloy has attracted many researchers because of its increasing applicability in high temperature

conditions. Still, the available research data pertaining to EDM of Inconel 718 is not sufficient. The authors during

the literature survey did not come across any work that investigates the machining characteristics of Inconel 718during die-sinking EDM. Therefore its machining behavior and its response to change in input parameters of the

process needs to be evaluated. Hence, attempts have been made to investigate the machining characteristics of

Inconel 718 during die-sinking EDMprocess.

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EDM is one of the most extensively used non-conventional material removal processes. EDM is a thermo-

electric process in which material is removed from work piece by erosion effect of series of electric discharges

(sparks) between tool and work piece immersed in a dielectric liquid. The electric energy induced by electric sparks

converts into thermal energy resulting in high temperature which melts and evaporates the work piece and tool

electrode. The eroded particles are flushed away by dielectric liquid. Physical and metallurgical properties do notcreate any limitation for the materials to be machined on EDM as there is no physical contact between tool and work

piece.

This work investigates the influence of input parameters on performance measures during die-sinking EDMof Inconel 718 with copper as tool electrode. There are many input parameters of electric discharge machine that

could be taken for experimental investigation of Inconel 718. Exploratory experiments were conducted to select the

input parameters and their levels. In this work, Shape factor (SF), Pulse-on-time (Ton), Discharge current (Id), Duty

cycle (), Flushing pressure (P) and Tool electrode lift time (TL) have been taken as input parameters. Material

removal rate (MRR), Surface Roughness (SR) and Tool Wear Rate (TWR) have been taken as performance

measures. The level of influence of input parameters has also been identified after experimental investigation.

Experimental investigation requires a number of experimental runs that may be an expensive and time

consuming affair. Design of experiments techniques like Taguchis method, Response surface methodology etc. areused to reduce the experimental runs in a scientific manner. DOE, a statistical technique, is used to study the effects

of various input parameters on performance measures simultaneously. In this work, experiments have been designed

as per Taguchis L36 (21 36) orthogonal array. Seven input parameters are taken, out of which one has 2 levels andthe rest six have 3 levels each. Orthogonal array allows to assess the effect of each factor independently of the

effects of other factors. Many authors have applied DOE technique to explain the machining characteristics ofdifferent materials during electric discharge machining. George et al. [1] employed Taguchis method to explain the

machining characteristics of carbon-carbon deposits during electric discharge machining. Liu et al. [2] employed L9

orthogonal array to see the effect of various input parameters on MRR. Ramasawmy and Bunt [3] did quantativeassessment of process parameters of EDM by Taguchis method by taking M300 (tool steel) as the work piece.

Ramasawmy and Bunt [4] presented experimental work that was done in order to quantify the effect of some of

EDM main parameters on surface texture. This work was then verified was Taguchis method. Ramakrishnan and

Krishnamurthy [5] reported the effect of pulse-on-time and delay time on MRR and SR during wire EDM of Inconel718. But they did not discuss the effect of other parameters on performance measures. They reported that higher

pulse-on-time gives more MRR but poor surface finish. Puri and Bhattacharya [6 ] analyzed the effect of 13 process

parameters on MRR, SR and accuracy of WEDM. There are many references in which Taguchis method has been

used as DOE technique to explain the machining characteristics of different material on EDM [7] [8] [9].However, some authors have employed other techniques also [10] to see the influence of process

parameters on performance measures, DOE technique is found very simple and efficient. The authors during theliterature survey did not come across any work that uses DOE technique to investigate the machining characteristics

of Inconel 718 during die-sinking electric discharge machining. Hence, attempts have been made to investigate thedie sinking EDM characteristics of Inconel 718 by DOE techniques in this work.

2. Experiments

Material employed in this study is Inconel 718. The mechanical properties of Inconel 718 are shown in Table 1.

Table 1. Mechanical properties of Inconel 718

Property Unit Value

Density g/cm3 8.19

Melting Point/range C 1260-

1336Ultimate tensile strength MPa 1240

Yield Strength MPa 1036

Hardness HRC 36

Average Coefficient of Thermal

Expansion

m/m K 13

Thermal Conductivity W/m K 11.4

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Inconel 718 has been chosen for the investigation because of its increasing demand in high temperature applications

and lack of literature available on eclectic discharge machining of this material.

Experiments have been carried out on Elecktra Plus S-50 ZNC oil die-sinking electric discharge machine in

which the Z-axis is servo controlled and X and Y axis are manually controlled.

Based on literature survey and preliminary investigations, the parameters chosen as inputs are shape factor,pulse-on-time, discharge current, duty cycle, gap voltage , flushing pressure, tool electrode lift time. The working

range of input parameters and the levels taken are shown in Table 2. Preliminary experiments were conducted in the

given range of different input parameters to select their levels. For accurate characterization of the process,experiments must be designed properly. L36 (2

136) orthogonal array, shown in Table 3, has been used which

contains 36 experimental runs at various combinations of seven input variables.

Table 2. Machining parameters and their levels

Input parameters Unit Symbol Range

(as specified bymachine

manufacturer)

Levels and values

1 2 3

Shape factor (SF) - A - Square Circular -

Pulse-on-time (Ton) s B 0.25-4000 50 100 150

Discharge current (Id) A C 0.5-50 3 8 12

Duty cycle () % D 0-1 0.7 0.75 0.83Gap voltage (Vg) V E 1-150 50 70 90

Flushing pressure (P) kg/cm2

F 0-1 0.3 0.5 0.7

Tool electrode lift time(TL)

sec G 1-12 1 2 3

Since stable machining conditions are achieved after 10 minutes, a study of 15 minutes machining or 0.5 mm depth

of cut (whichever is earlier) is taken in this work.

MRR, TWR and SR have been used to evaluate machining performance. MRR and TWR (mm3/min) are

calculated by measuring the amount of material removed and the machining time by using following equation

(min)timemachining)3(g/mmelectrodeorpieceworkofdensity

(g)electrodeorpieceworkofin weightReduction

/min)

3

(mmTWRorMRR

Initial and final weights of work piece and electrode were measured by electronic weighing balance having a

resolution of 0.001 g. Surface roughness was measured by a contact type stylus based surface tester. The centre line

average (CLA) surface roughness parameter Ra war used to quantify the surface roughness.

Copper electrodes of cross sections: square and circle were used to conduct the experiment. The area of both square

and circular shaped electrodes was kept same to avoid any ambiguity in machining.

3. Analysis method

3.1 Taguchis method

Taguchis method is a well accepted methodology for experiment design. In this, signal-to-noise ratio(S/N) is usedto represent a response or quality characteristics and the largest S/N ratio is required. There are three types of quality

characteristics viz. nominal-the-better, larger-the-better and smaller-the-better. In this work, experimentally

observed MRR value is larger-the-better and TWR and SR are lower-the-better. Based on Taguchis method,S/N ratio calculation is done as below-

i) Larger-the-better

n

iiy

nNS

1 2

11log10/ [1]

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ii) Smaller-the-better

n

iiy

nNS

1

21log10/ [2]

Where iy is the experimentally observed value and n is the repeated number of each experiment.

Table 3. Design experiment of L 36(2

1

3

6

) array with different experimental parametric levelsExpNo.

SF

Ton

(s)Id

(A)

(%)Vg(V)

P(kg/ cm2)

TL(sec)

SRTWR

S/N

(MRRS/N(SR)

S/N

(TWR

1 1 1 1 1 1 1 14

4.25 0.0300 13.0984 -12.5678 30.4684

2 1 2 2 2 2 2 22

7.3 0.6995 28.0212 -17.2665 3.1041

3 1 3 3 3 3 3 33

9.46 0.9407 31.2768 -19.5178 0.5311

4 1 1 1 1 1 2 24

6.145 0.1114 13.5607 -15.7704 19.0619

5 1 2 2 2 2 3 33

7.9 0.9235 29.7169 -17.9525 0.6912

6 1 3 3 3 3 1 14

8.55 0.3780 33.8087 -18.6393 8.4509

7 1 1 1 2 3 1 22

5.05 0.0741 8.6729 -14.0658 22.6018

8 1 2 2 3 1 2 32

9 0.3960 29.5153 -19.0849 8.0465

9 1 3 3 1 2 3 13

11.07 0.3010 30.9475 -20.883 10.4297

10 1 1 1 3 2 1 31

5.36 0.0150 5.6339 -14.5833 36.4890

11 1 2 2 1 3 2 11

7.03 0.1029 21.0218 -16.9391 19.7523

12 1 3 3 2 1 3 23

10.73 0.1598 30.7536 -20.612 15.9310

13 1 1 2 3 1 3 22

8.05 0.3109 28.9105 -18.1159 10.1483

14 1 2 3 1 2 1 35

9.8 0.2391 34.8871 -19.8245 12.4298

15 1 3 1 2 3 2 1

2

4.92 0.0075 8.7134 -13.8393 42.5096

16 1 1 2 3 2 1 11

7.16 0.1624 24.7165 -17.0983 15.7857

17 1 2 3 1 3 2 23

9.63 0.5226 29.7869 -19.6725 5.6366

18 1 3 1 2 1 3 37

5.2 0.0479 17.4441 -14.3201 26.3999

19 2 1 2 1 3 3 31

6.33 0.2283 24.6541 -16.0281 12.8310

20 2 2 3 2 1 1 14

10 0.5958 33.5252 -20 4.4973

21 2 3 1 3 2 2 24

4.29 0.0215 13.8749 -12.6491 33.3329

22 2 1 2 2 3 3 11

5.76 0.1750 21.6117 -15.2084 15.1385

23 2 2 3 3 1 1 2

4

7.25 0.3855 32.4808 -17.2068 8.2784

24 2 3 1 1 2 2 34

4.67 0.0156 12.7863 -13.3863 36.1345

25 2 1 3 2 1 2 33

7.09 0.7231 31.9521 -17.0129 2.8160

26 2 2 1 3 2 3 14

6.11 0.0599 12.0518 -15.7208 24.4478

27 2 3 2 1 3 1 21

8.31 0.0202 23.2525 -18.392 33.8737

28 2 1 3 2 2 2 11

6.88 0.2196 24.4669 -16.7518 13.1675

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4.

Analysis of experimental results

4.1 Material Removal Rate

Table 3 shows the orthogonal array based experimental results of MRR and its corresponding S/N ratio, whoseANOVA results are shown in Table 4. Observation of Table 6 indicates that discharge current is the most

dominant factor having percentage contribution as 89.07, followed by gap voltage and pulse-on-time. Fig. 1shows that MRR increases with the increase in discharge current. This is because at higher discharge current,

more spark energy is induced which causes larger overcuts and thus produces larger chips. Fig. 2 shows that

MRR increases as the value of pulse-on-time increases. Higher pulse-on-time i.e. duration time of EDM sparks

indicates that spark energy is induced for a longer time which results in larger craters on work piece indicatinghigh MRR. But at a certain value of pulse-on-time, MRR is almost maximum and further increment in pulse-on-

time does not affect MRR considerably. Fig. 3 shows the graph between MRR and gap voltage which indicates

that initially MRR increases with increase in gap voltage but after certain point MRR decreases with furtherincrease in gap voltage. Further increment in gap voltage increases the discharge gap distance which in effect

reduces the effect of induced energy at work piece and hence MRR decreases. Shape factor, duty cycle, flushing

pressure and tool electrode lift time do not have considerable effect on MRR.

Fig.1 Relationship between MRR and discharge current

29 2 2 1 3 3 3 23

5.82 0.0300 10.5735 -15.2985 30.4684

30 2 3 2 1 1 1 33

7.28 0.0874 30.0572 -17.2426 21.1659

31 2 1 3 3 3 2 33

6.9 0.2781 30.8659 -16.777 11.1154

32 2 2 1 1 1 3 14

4.49 0.0653 13.9080 -13.0449 23.6984

33 2 3 2 2 2 1 2 2 7.03 0.0694 27.0865 -16.9391 23.1781

34 2 1 3 1 2 3 23

7.19 0.4013 31.7398 -17.1346 7.9310

35 2 2 1 2 3 1 32

6.03 0.0150 8.3155 -15.6063 36.4890

36 2 3 2 3 1 2 12

7.32 0.3037 28.1843 -17.2902 10.3518

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Fig. 2 Relationship between MRR and pulse-on-time

Fig. 3 Relationship between MRR and gap voltage

4.2 Surface Roughness

Orthogonal array based experimental results of SR and their corresponding S/N ratios are represented in Table

3. ANOVA results for SR, reported in Table 5, show that discharge current is the most dominant factor havingpercentage contribution as 68.42, followed by pulse-on-time and shape factor. Fig. 4 and 5 shows that SR

increases when discharge current and pulse-on-time increase. The electric-discharge machined surface consists

of a multitude of overlapping craters that are formed by spark discharges. The size of these craters depends onthe discharge energy and duration. More is the discharge energy (i.e. discharge current) and duration (pulse-on-

time), the larger are the craters resulting in more surface roughness. It is also observed from Fig. 6 that circular

tool electrode gives better surface finish than the square one. Duty cycle, gap voltage, flushing pressure and tool

electrode lift time do not have considerable effect on SR.

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Fig. 4 Relationship between SR and discharge current

Fig. 5 Relationship between SR and pulse-on-time

Table 4. ANOVA results for MRR

Source

Degrees of

freedom

Sum of

squares

Mean

square F-ratio

Percentage

contribution

Shape factor (A) 1 2.3 2.3 0.3970 0.0805

Pulse-on-time(B) 2 238.8017 119.40 20.6121 8.3538

Dischargecurrent(C) 2 2151.7568 1075.87 185.7285 75.2731

Duty cycle(D) 2 6.3 3.15 0.54378 0.2204

Gap voltage(E) 2 308.0027 154 26.5851 10.7746

Flushing

pressure(F) 2 5.3 2.65 0.4574 0.1854

Time interval(G) 2 18.7 9.35 1.61409 0.6542Error 22 127.44 5.7927 1 4.4581

Total 2858.6 100

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Fig. 6 Relationship between SR and shape factor

Table 5. ANOVA results for SR

Source

Degrees of

freedom

Sum of

squares

Mean

square F-ratio

Percentage

contribution

Shape factor (A) 1 10.09 10.09 7.7344 5.6492

Pulse-on-time(B) 2 12.4 6.2 4.7526 6.9425Discharge

current(C) 2 123.52 61.76 47.3421 69.1563

Duty cycle(D) 2 0.12 0.06 0.0459 0.0672

Gap voltage(E) 2 0.13 0.065 0.0498 0.0728

Flushing

pressure(F) 2 2.51 1.255 0.9620 1.4053

Time interval(G) 2 1.14 0.57 0.4369 0.6383

Error 22 28.7 1.304545 16.0685

Total 178.61 100

4.3 Tool Wear Rate

Orthogonal array based experimental results of TWR and their corresponding S/N ratios are represented in

Table 3. ANOVA results for TWR are reported in Table 6. ANOVA results show that discharge current is themost dominant factor having percentage contribution as 63.24, followed by pulse-on-time, flushing pressure and

gap voltage. Fig. 7 shows that TWR increases as discharge current increases. High discharge current induces

high spark energy which facilitates more material removal from work piece and tool electrode. TWR increasesinitially with increment in pulse-on-time but decreases with further increase in pulse-on-time as shown in Fig. 8.

This is because of deposition of carbon particles on tool electrode at a high temperature. While calculating the

weight loss of tool, actual loss is compensated, up to some extent, by carbon deposits. As a result tool wear rate

decreases with further increase in pulse-on-time. Fig. 9 depicts that TWR increases when flushing pressure

increases. High flushing pressure removes the eroded particles from the gap between tool and the work piece

more effectively and efficiently which in effect increases the tool wear rate. High gap voltage induces higherspark energy which leads to more TWR. Shape factor, duty cycle, flushing pressure and tool electrode lift time

do not have considerable effect on TWR.

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Fig. 7 Relationship between TWR and discharge current

Fig. 8 Relationshipbetween TWR and pulse-on-time

Fig. 9 Relationship between TWR and flushing pressure

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Table 6. ANOVA results for TWR

Source

Degrees of

freedom

Sum of

squares

Mean

square F-ratio

Percentage

contribution

Shape factor (A) 1 101 101 2.7237 2.1412

Pulse-on-time(B) 2 327 163.5 4.4091 6.9324

Discharge

current(C) 2 3020.2 1510.1 40.7234 64.0280

Duty cycle(D) 2 58 29 0.7820 1.2296

Gap voltage(E) 2 145 72.5 1.9551 3.0740

Flushingpressure(F) 2 242 121 3.2630 5.1304

Time interval(G) 2 8 4 0.1078 0.1696

Error 22 815.8 37.0818 17.2949

Total 35 4717 100

7. Conclusions

The present work explains the machining characteristics of die-sinking EDM on Inconel 718. Taguchis methodhas been employed as a design of experiments technique successfully for establishing the relationship between

various input parameters and performance measures. MRR increases with the increase in discharge current and

pulse-on-time. MRR increases initially, attains a maximum value and further decreases with increase in gap

voltage. SR increases with the increase in discharge current and pulse-on-time. TWR increases with the increasein discharge current and flushing pressure. TWR increases initially with the increase in pulse-on-time but after

certain value it decreases. ANOVA has been applied to find the level of influence of input parameters on

performance measures. Discharge current is found the most influential input parameter on each performance

measure. Higher discharge current increases MRR, deteriorates surface finish and leads for more tool electrodeloss. Discharge current and pulse-on-time are identified as common influencing parameters for MRR, SR and

TWR.

References

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[2] Liu, J.W.; Yue, T.M.; Guo, Z.N. (2009): Wire elcrtochemical discharge machining of Al2O3 particle reinforced Aluminium Alloy6061, Materials and Manufacturing Processes, 14, pp. 446-453.

[3] Ramasawmy, H; Blunt, L. (2002): 3D surface characterization of electro polished EDMed surface and quantitative assessment of

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[4] Ramasawmy, H; Blunt, L.(2004): Effect of EDM process parameters on 3D surface topography, Journal of Material ProcessingTechnology, 148, pp. 115-164.

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[6] Puri, A.B.; Bhattacharya, B. (2003): An analysis and optimization of the geometrical inaccuracy due to wire lag phenomenon in

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[8] Tzeng, Yih-fong; Chen, Fu-chen. (2003): A simple approach for robust design of high-speed electrical-discharge machining

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[9] Lin, Yan-Cherng; Cheng, Chao-Hsu; Su, Bo-Lin; Hwang, Lih-Ren (2006): Machining Characteristics and Optimization of MachiningParameters of SKH 57 High- Speed Steel Using Electrical-Discharge Machining Based on Taguchi Method, Materials and ManufacturingProcesses, 21, pp. 922-929.

[10] Pellicer, N.; Ciurana, J; Ozel, T. (2009): Influence of process parameters and electrode geometry on feature micreo-accuracy inelectro-discharge machining of tool steel, Materials and Manufacturing Processes, 24, pp. 1282-1289.

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