Experimental and Statistical Optimization Of Wire- EDM For ...

International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:21 No:01 88

213401-5757-IJMME-IJENS © February 2021 IJENS I J E N S

Experimental and Statistical Optimization Of Wire-

EDM For Hipped (HIP) Udimet700

Sara A. El-Bahloul1, Rania Mostafa 1,2* 1Production & Mechanical Design Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt.

2Basic Science Department, Mansoura Higher Institute for Engineering & Technology, Mansoura, Egypt. * Corresponding Author (Email: [email protected] )

Abstract-- The materials development along with the

requirement of high precision machining have contributed

significantly to the research investigation on Wire Electrical

Discharge Machining (Wire-EDM) of Udimet700, a Nickel-

Based Superalloy. This research investigates an experimental

procedure beginning with Udimet700 fabrication by Powder

Metallurgy-Hot Isostatic Pressing (PM-HIP) followed by a

Non-traditional machining process, Wire-EDM. Five

machining parameters namely, Spark on-time, Spark off-time,

Pulse Current, Pulse Voltage, and Wire Speed are studied to

identify their effects on the resultant Material Removal Rate

(MRR), Surface Roughness (SR), and Vickers Micro-Hardness

(VHN). Single and multi-response optimizations are performed

based on a Taguchi-based Grey relational analysis (GRA)

technique. The optimal machining constraints combination to

achieve the best multi-response optimization is (40 µsec) spark

on-time, (5 µsec) spark off-time, (5 A) pulse current, and

setting the wire speed and pulse voltage into 2 and low,

respectively. In order to verify the results of the analysis, the

reliability progress of the responses is forecast and reviewed,

and good alignment is achieved. The experimental and

expected findings confirm the validity of the Taguchi-based

GRA for enhancing the WEDM of Udimet700 nickel-base

superalloy.

Index Term-- Wire-EDM; Hot Isostatic Pressing; Udimet700;

machining constraints; Single response; Multi-response

1. INTRODUCTION

Nickel (Ni) is a valuable metal element that mixes

with extremely distinct metal[1]. The Ni-Crystal-Structure is

a face-centered-cubic (FCC), so it is ductile, malleable, and

tough. Usually, Nickel -Chromium-Cobalt alloys have the

ability to comprehensive protection in corrosion mediums

and can withstand various functioning conditions such as

high stresses and temperatures. Gathering these

considerations make such alloys are useful in contemporary

industry. Udimet700 is a Nickel-Chromium-Cobalt

Superalloy that has greater Aluminum (AL) and Titanium

(Ti) contents [2]. The chemical composition analysis of

Udimet700 is shown in Table I. Such alloying elements

make Udimet700 a precious class of engineering material

that has very useful corrosion resistance, widespread

applications in aircraft, gas turbine disks and hot section

components, rocket engine, and jet engine blades because of

their superior mechanical properties [3]-[5]. Superalloy

Udimet700 is also a promising material due to its high

electrical and thermal conductivity[6, 7].

Table I

Nickel-based alloy (Udimet700) chemical composition

Nickel, Ni Cobalt, Co Chromium, Cr Molybdenum, Mo Aluminum, Al Titanium, Ti Iron,

Fe Carbon, C

Boron,

B

53% 18.5% 15.09% 5% 4.3% 3.4% ≤1% 0.07% 0.03%

To fulfill the demand for the development of new

and innovative engineering materials, and the need for

accurate and versatile components, have made Wire-EDM a

significant production process. So as to erode the workpiece

material and produce the desired shape, the Wire-EDM

process utilizes electrical sparks between a small diameter,

moving wire electrode, and the workpiece. Hence, there is

no physical interaction between the wire electrode and the

workpiece, so the removal of material is not restricted by the

hardness/strength of the workpiece as in traditional

machining, thus its widespread usage in the manufacture of

supper hardened dies [8].

The effects of wire-EDM process controllable

variables have been investigated until now due to the

widespread of material developments. In order to achieve

the desired MRR and SR, Sara A. El-Bahloul optimized

wire-EDM's most critical cutting parameters when cutting

AISI 304 stainless steel. The techniques of the response

surface coupled with the artificial neural network and fuzzy

logic were applied. The results indicated that by increasing

the peak current and the pulse on time and reducing the

pulse off time, the resulting workpiece surface is rougher,

although obtaining a higher MRR [9]. Abhilash P.M. and

D. Chakradhar correlated the mean difference in gap voltage

and wire breakage occurrences during machining of Inconel

718. In predicting mean gap voltage difference, based on

which wire breakage warnings can be issued, the artificial

neuro-fuzzy inference system model was very accurate.

Additionally, The model's capacity was further verified by

verification tests [10]. C. Naresh, et al., reported the

relationship between Wire-EDM machining parameters and

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output parameters using an artificial neuro-fuzzy inference

system predicted model. The findings were differentiated

from the experimental values and the predicted values of the

performance attributes were shown to be in reasonable

alignment with the real values [11]. The possible process

parameters affecting the MRR, SR, and kerf width were

analyzed and optimized by Amit Kumar, et al., while

machining high-speed steel grade M2. Using the Grey

relation grade, the optimal state of the machining parameter

was obtained. Additionally, analysis of variance is used to

assess the importance of the input parameters [12].

Ravindranadh examined a Taguchi-based multi-response

optimization methodology coupled with GRA for Wire-

EDM operations on an aluminum alloy of ballistic grade. In

order to verify the results obtained by GRA, the validation

tests were also carried out and showed that considerable

progress was accomplished with a lower error percentage

[13]. M.T. Antar, et al., provided experimental results about

the fatigue performance of Udimet720 nickel-based

superalloy during machining, using minimum damage

generator technology. The combination of 'Clean Cut'

generator technology with minimal damage and adequate

trim-pass techniques greatly improved the machined

components' fatigue performance [8]. The effect of process

parameters on the MRR and surface integrity of four kinds

of advanced material was investigated by Scott F. Miller, et.

al. Although the conclusions provided were machine-

dependent, this analysis presented guidance and procedures

for the implementation of the wire EDM method for the

machining of new engineering materials in order to achieve

various production targets, including high MRR, miniature

features or a combination between both of them [14].

Due to the unique properties of Udimet700 and its

great applications, it is necessary to study its machinability

behavior by Wire-EDM. This work investigates an

experimental procedure considering five machining

constraints (MC); namely, Pulse on-time (Ton), Pulse off-

time (Toff), Peak current (PC), Wire speed (WS), and Peak

voltage (PV), to identify their effects on the resultant

Material MRR, SR, and VHN. To optimize the three

responses together based on the considered Five MC, a

Taguchi-based GRA technique is applied. Furthermore, with

the assistance of response graphs, a single response

optimization is developed.

2. MATERIAL AND METHODS

Figure 1 illustrates a flowchart that displays the

procedures of the applied methodology and techniques that

are performed during performing the experimental work.

2.1. Material and Samples Preparation

Hot Isostatic Pressing (HIP) fabrication process,

shown in Fig. 2, is used in various industrial applications

such as Casting, Additive-Manufacturing (AM), Medical

Implants, Offshore industry, and Metal -Injection- Molding

(MIM) [15–21]. Nowadays, Powder Metallurgy (PM)-HIP

technology is applied in a wide range of pressure sintering

of high-performance Ni-based alloys such as Udimet-

Family. PM-HIP has a great ability to form and densify

containerized powder shape to about the maximum

theoretical density and to improve the ductility and

corrosion resistance of such super alloy Udimet700 [22–24].

In this work, a cylindrical rod (12 mm diameter

and 70 mm long) of superalloy Udimet700 is produced by a

compact small PM-HIP system in a single-spacing saving

cabinet at simultaneously high temperature 1250 oC and

high isostatic pressure 120 MPa using an Argon gas as a

transfer medium for 4 hr. PM-HIP system is moderated with

Uniform Rapid Cooling (URC) to cool the Udimet700 rod

at a managed rate of 70 oC/min. URC controls the thermal

distortion and the grain-growth and offers the consolidation

of heat treatment and HIP in one step. After the HIP process

is complete, the sample is turned out. The produced

cylindrical rod of Udimet700 is machined and cut to obtain

20 samples each with 10 mm diameter and 3 mm thickness

as shown in Fig. 3.

2.2. Machining Setup

The Wire-EDM experiments are conducted on a

Kingred CNC wire cut EDM machine that is found in the

non-traditional machining laboratory – Faculty of

Engineering – Mansoura University – Egypt. Figure 4

shows the Wire-EDM setup. A cylindrical specimen of 10

mm diameter and 3 mm thickness is used as a workpiece for

each experiment. A molybdenum wire with a diameter of

0.16 mm is used as an electrode. The used working fluid is

tap water with anticorrosive.

2.3. Design of Experiment

In order to perform the experimental design, the Taguchi

technique is applied. It is used to decrease the number of

experiments that are required to be carried out compared to

the full factorial experiments. However, this approach is

developed to optimize only a single response [25].



Fig. 1. The procedures during performing the experimental work

Fig. 2. The layout of the Hot Isostatic Pressing (HIP) process [15] Fig. 3. The PM-HIP Udimet700 Samples



Fig. 4. Kingred CNC wire cut EDM machine

The MC and their levels are chosen and described

in Table II depending on the machining capabilities and the

pilot experiments based on the literature review. Four

different wire speeds are ranging from “0” to “3”, “0” is the

fastest speed, while “3” is the slowest one. The machine

controller interface only allows two voltage setups to be

swapped from: “low” and “high”. The design of

experiments is created using MINITAB software based on

the Taguchi technique. A total of sixteen experiments have

been carried out as illustrated in Table III.

2.4. Measurements and Mechanical Testing

Because of the nature of Wire-EDM, the MMR, SR

of the machined surface, and its VHN are deemed as the

main problems of the cutting process [26]. So, the MRR,

SR, and VHN will be measured and considered as the

output responses in the present designed problem.

2.4.1. MRR Calculation

Equation (1) is used to calculate the MRR.

MRR = kw × t × vc (1)

where kw is the kerf width, t is the workpiece thickness, and

vc is the cutting velocity. The kw can be estimated by adding

the wire diameter to twice the gap distance between the

workpiece and the wire. The vc can be calculated by

dividing the machining length by the machining time. The

resultant MRR for each experiment is given in Table III.

2.4.2. SR Measurement

The SR measurements (Ra) are achieved by the

Portable Mitutoyo SJ-210 Series 178, 178-565-01A [27].

The measuring conditions during the SR-tests are illustrated

in Table IV. The SR test is performed along with two

directions, one along the Radial Direction (RD) - the length

of cut, and the other along the Axial Direction (AD) -

thickness of the sample, to reach the surface quality

information in all cutting directions. Each SR-measurement

is repeated 5 times in the RD and 3 times in the AD and the

average of (Ra) is calculated to attain the more precise

value. The obtained results are given in Table III.

Table II MC and their levels

Machining Constraint Symbol Unit Level 1 Level 2 Level 3 Level 4

Pulse on-time Ton µsec 10 20 30 40

Pulse off-time Toff µsec 5 10 15 20

Peak current PC A 2 3 4 5

Wire speed WS ─ 3 2 1 0

Peak voltage PV ─ Low High

2.4.3. VHN Test

The VHN test is obtained for Udimet700 samples

using SMTFMF-DHT device model VHN-1000. The test is

performed under applied load 4.9 N in 10 sec. The average

VHN is calculated for three readings along the sample

surface to obtain the most accurate results. The obtained

results for each experiment are given in Table III. The VHN

of the base material is measured, and it is about 194.8 VHN.

2.5. GRA

A Taguchi-based GRA technique is applied to

optimize more than one response. The GRA has been

widely used to solve the setting of optimum MC associated

with a problem with several responses [28]. First of all, the

normalizing of pre-processing data must be performed to

generate the grey relational data. Two characteristics,

namely, larger-the-better or smaller-the-better, can be

implemented on each response according to its optimization

objective function. Equations (2) and (3) are used to

normalize the larger-the-better and the smaller-the-better

characteristics, respectively.

𝑁𝑖 = 𝑦𝑖 − min 𝑦

max 𝑦 − min 𝑦 (2) ;

𝑁𝑖 = 𝑚𝑎𝑥 𝑦 − 𝑦𝑖

𝑚𝑎𝑥 𝑦 − 𝑚𝑖𝑛 𝑦 (3)

where Ni denotes the normalized characteristic for the ith

experiment, and yi represents the ith experiment response

value. Once the response is normalized and deviated, the

next step is to calculate the grey relational coefficient using

Equation (4).



𝐺𝑅𝐶𝑖 = ∆𝑚𝑖𝑛 + ζ∆𝑚𝑎𝑥

∆𝑖 + ζ∆𝑚𝑎𝑥

(4)

where GRCi signifies the grey relational coefficient for the

ith experiment. It is computed as a function of ∆min and ∆max,

the minimum and maximum deviations for each response,

i.e., equals 0 and 1 respectively. To assign equal weights to

each response, the distinguishing coefficient ζ is normally

set to 0.5. A composite grey relational grade is then

estimated using Equation (5) by averaging each response

variable's GRC.

𝐺𝑅𝐺𝑖 =1

𝑛∑ 𝐺𝑅𝐶𝑖

𝑛

𝑖=1

(5)

where n represents the number of the considered responses

while calculating the GRG for the ith experiment. The final

step is to forecast and check the output response using

Equation (6).

𝐺𝑅𝐺𝑃𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 = 𝐺𝑅𝐺𝑚 + ∑ 𝐺𝑅𝐺𝑚𝑎𝑥 − 𝐺𝑅𝐺𝑚

𝑞

𝑖=1

(6)

Table III Experimental design based on Taguchi technique.

Experiment Number Ton Toff PC WS PV MRR (mm3/min) SR (µm Ra) VHN GRG

1 1 1 1 1 1 2.025 2.715 114.5 0.407

2 1 2 2 2 1 2.093 2.581 115.0 0.466

3 1 3 3 3 2 2.129 2.402 123.1 0.543

4 1 4 4 4 2 2.100 2.575 114.5 0.472

5 2 1 2 3 2 2.139 3.297 121.7 0.475

6 2 2 1 4 2 2.137 2.458 116.1 0.536

7 2 3 4 1 1 2.135 2.495 149.3 0.621

8 2 4 3 2 1 2.077 2.297 118.4 0.497

9 3 1 3 4 1 2.180 2.994 148.7 0.675

10 3 2 4 3 1 2.129 3.065 149.3 0.557

11 3 3 1 2 2 2.093 2.455 113.8 0.480

12 3 4 2 1 2 2.100 2.695 116.3 0.462

13 4 1 4 2 2 2.186 3.586 164.8 0.789

14 4 2 3 1 2 2.146 3.869 159.3 0.609

15 4 3 2 4 1 2.122 2.228 113.5 0.547

16 4 4 1 3 1 2.125 1.886 112.3 0.634

Table IV

The Measuring conditions of SR Experimental Test

Standard Profile Cut-off value λc (µm) Sampling length λs (µm) Speed (mm/s) RangeX (mm)

ISO1997 R 0.25 2.5 0.5 5

where GRGmax denotes the maximum average of GRG at the optimal level of the machining constraint with number q, and

GRGm represents the mean GRG.

3. RESULTS AND DISCUSSION

3.1. MC Effect on MRR

Figure 5 illustrates the response graphs of the MC

effect on the MRR. It is found that by increasing Ton, PC,

WS, or PV, the MRR increases. This occurs due to the

increase of the spark discharge energy, leading to the

increasing of the crater volume. In contrast, as Toff

increases, the MRR decreases, due to the cooling effect

increasing of the dielectric without discharging effect.

Based on the response graphs, it is obvious that the most

significant machining constraint is Ton. Also, it is clear that

the optimal MC combination that will achieve the highest

MRR is Ton4 - Toff1 - PC4 – WS4 – PV2. A confirmation

test is performed considering the resultant optimal

conditions. The estimated MRR based on Equation (1) is 2.2

mm3/min, which is higher than compared to each

experimental MRR.

3.2. MC Effect on SR

Figure 6 displays the response graphs for the

effects on the SR of the MC. Due to the increase of Ton,

PC, or PV, the increase in SR exists. This occurs due to the

increase of the spark discharge energy. In contrast, it can be

observed that the increase of Toff and WS induce the

decrease of SR, due to increasing the improvement of debris

removal by dielectric flushing after discharging.

Based on the response graphs, the most significant

machining constraint is Toff. Besides, it is evident that the

optimal combination of the MC that will achieve the lowest

SR is Ton1 – Toff4 – PC1 – WS4 – PV1. Under the

resulting optimal conditions, a validation test is performed.



The measured SR (Ra) is equal to 1.662 µm, which is lower than compared to each experimental SR.

Fig. 5. MRR response graphs Fig. 6. SR response graphs

3.3. MC Effect on VHN

Figure 7 shows the response graphs for the VHN.

The increase of VHN occurs by the increase of Ton, PC, or

PV, due to the increase of the thermal energy during

discharging. In contradiction, the increase of Toff or WS

causes the decrease of the produced VHN. This is due to the

decline in the influence of thermal energy on the formed

surface, which allows the grains to expand slowly. The

increase of VHN indicates that the generated recast layer

thickness is small. This layer significantly lowers the fatigue

strength of the alloy.

Based on the response graphs, the PC is the most

significant machining constraint. Furthermore, it is obvious

that the optimum combination of MC that will achieve the

lowest VHN is Ton4 – Toff1 – PC4 – WS1 – PV2.

Considering the resulting optimal conditions, a validation

test is carried out. The measured VHN is 187.5, which is

higher than compared to each experimental VHN.

3.4. Multi-Response Optimization

By using the Taguchi-based GRA, the multiple

objective optimization issues have been translated into a

single equivalent objective function optimization problem.

The GRG value for each experiment is estimated by using

Equation (5) and displayed in Table III. Once the GRGs are

ascertained, a response table is designed as shown in Table

V. From this table, it is obvious that the optimal MC

combination to achieve the best multi-response optimization

is Ton = 40 µsec, Toff = 5 µsec, PC = 5 A, and setting the

WS and PV into 2 and low, respectively.

Once the optimal setting has been established,

forecasting and checking the performance progress of the

responses is the final stage. The predicted GRG is

determined using Equation (6). To validate the outcomes of

the research, confirmation tests are performed, and the

average GRG of the trails is determined. The MRR, SR, and

VHN are measured to be equal to 2.179 mm3/min, 2.897

µmRa, and 159.8, respectively. Furthermore, it can be

concluded from Table VI that the findings of the

confirmation experiment are in strong alignment with the

predicted value. Additionally, the experimental results

affirm the validity of the Taguchi-based GRA for enhancing

the Wire-EDM of Udimet 700 nickel-base superalloy.

4. CONCLUSION

This research explores an experimental approach

starting with the manufacture and preparation of workpieces

by hot isostatic pressing accompanied by Wire-EDM. A

Taguchi-based GRA technique is applied to optimize the

machining conditions while cutting Udimet 700 nickel-base

superalloy by Wire-EDM. The developed mathematical

models are able to describe the impact of the machining

constraint on three different responses effectively with the

help of response graphs. The coupled technique finds the

ideal state that corresponds to a higher MRR and VHN, with

achieving lower SR. The optimal MC combination to

achieve the best multi-response optimization is

Ton=40µsec, Toff=5µsec, PC=5A, and setting the WS and

PV into 2 and low respectively. To validate the outcomes of

the research, forecasting, and checking of the performance

progress of the responses are performed and achieved strong

alignment. The experimental and predicted results affirm the

validity of the Taguchi-based GRA for enhancing the Wire

EDM of Udimet700 nickel-base superalloy.



Fig. 7. VHN response graphs

Table V GRG response table

MC Level 1 Level 2 Level 3 Level 4

Ton 0.4721 0.5322 0.5435 0.6451

Toff 0.5866 0.5420 0.5477 0.5166

PC 0.5144 0.4875 0.5813 0.6098

WS 0.5247 0.5583 0.5522 0.5576

PV 0.5506 0.5459

Table VI Confirmation test and predicted value results

Optimal Machining

Conditions

Experimental

GRG

Predicted

GRG

Ton = 4

Toff = 1

PC = 4

WS = 2

PV = 1

0.753 0.757

ACKNOWLEDGMENTS

The authors would like to appreciate the Faculty of

Engineering-Mansoura University-Egypt, for providing the

requisite facilities for the experimental work to be carried

out. Besides, the authors would like to thank Assoc.

Prof./Noha Abdel Mawla El-Wassefy, Faculty of Dentistry-

Mansoura University-Egypt for her outstanding assistance

and patience during SR measurements.

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Experimental and Statistical Optimization Of Wire- EDM For ...

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