Table of ContentsCHAPTER 1................................................................................................................................................3

INTRODUCTION...................................................................................................................................3

1.1 Background of Study...............................................................................................................3

1.2 Term/Concept................................................................................................................................4

1.3 Problem Statement.........................................................................................................................8

1.4 Objective.......................................................................................................................................8

1.5 Scope of Project.............................................................................................................................9

1.6 Significant of Project.....................................................................................................................9

1.7 Summary.......................................................................................................................................9

CHAPTER 2..............................................................................................................................................10

LITERATURE REVIEW......................................................................................................................10

2.1 Introduction.................................................................................................................................10

2.2 Review of journals.......................................................................................................................10

2.3 Gaps in Literature Review...........................................................................................................17

CHAPTER 3..............................................................................................................................................18

METHODOLOGY................................................................................................................................18

3.1 Introduction.................................................................................................................................18

3.2 Gathering Information.................................................................................................................19

3.3 Material preparation.....................................................................................................................20

3.4 Selection of the machining parameter (factor) and their level......................................................22

3.5 Design of experiment...................................................................................................................23

3.6 Specimen preparation..................................................................................................................26

3.7 Constant machining parameters use in the cutting process..........................................................26

3.8 Measurement test and analysis Methodology..............................................................................28

3.9 Taguchi method.....................................................................................................................29

3.10 Experimental and measurement equipment...............................................................................31

CHAPTER 4..............................................................................................................................................34

EXPERIMENTAL RESULTS AND ANALYSIS: TAGUCHI METHOD...........................................34

1

4.1 Introduction.................................................................................................................................34

4.2 Data Collection............................................................................................................................35

CHAPTER 5..............................................................................................................................................50

DISCUSSION.......................................................................................................................................50

CHAPTER 6..............................................................................................................................................52

CONCLUSION.....................................................................................................................................52

6.1 Introduction.................................................................................................................................52

6.2 Conclusions.................................................................................................................................52

REFERENCES......................................................................................................................................53

2

CHAPTER 1

INTRODUCTION

1.1 Background of Study

Wire electrical discharge machining (WEDM) is a spark erosion process used to

produce complex two-dimensional and three-dimensional shapes through electrically

conductive work pieces by using wire electrode. The sparks will be generated between

the work piece and a wire electrode flushed with or immersed in a dielectric fluid [1].

In wire electrical discharge machining, (WEDM), the process parameters will

ensure whether the product produce is as required or not which is the product is high

accuracy and fine resultant surface finish[2]. In this study, the process parameters that

will considered are pulse-off time (Toff), peak current (IP), wire feed (WF) and wire

tension (WT).

In this study, efforts are to estimate cutting rate (CR) metal removal rate (MRR)

and surface finish (SF) using experimental data follow by develop prediction models

3

using Taguchi Method approach. The adequacy of the above the proposed models have

been tested through the analysis of variance (ANOVA). Optimal combination of these

parameters was obtained for achieving controlled WEDM of the work pieces.

1.2 Term/Concept

1.2.1 Electric Discharge Machining (EDM)

Electric discharge machining (EDM), also referred to as die sinking spark

machining, wire erosion, or spark eroding. It is a manufacturing process by using

electrical discharges (sparks) to obtain the desired shape.[3] Parent metal is removed

from the work piece by a series of swiftly frequent current discharges between

two electrodes, separated by a dielectric liquid and focus to an electric voltage. One of

the electrodes is the tool-electrode, while the other is the work piece-electrode.

The intensity of the electric field in the volume between the electrodes becomes

greater than the strength of the dielectric, which breaks, allowing current to flow between

the two electrodes when the distance between the two electrodes is reduced. Thus, the

specimen is removed from both the electrodes. When the current flow stops, new liquid

dielectric is usually conveyed into the inter-electrode volume enabling the solid particles

to be carried away and the insulating properties of the dielectric to be restored. Flushing

is the term by referring the adding new liquid dielectric in the inter-electrode. Also,

a difference of potential between the two electrodes is restored to what it was before the

breakdown after a current flow, so that the breakdown of a new liquid dielectric can

occur.

1.2.2 Wire Electric Discharge Machining (WEDM) process

The material removal mechanism of WEDM is involving the erosion effect

produced by the electrical discharges (sparks) which is very similar to the EDM process.

Material is eroded from the work piece by a series of discrete sparks occurring between

the work piece and the wire separated by a stream of dielectric fluid, which is

4

continuously fed to the machining zone [4]. However, today's WEDM process is

commonly conducted on work pieces that are totally submerged in a tank filled with

dielectric fluid. Such sank method of WEDM endorses temperature stabilization and

efficient flushing especially in cases where the work piece has varying thickness. The

WEDM process makes use of electrical energy generating a channel of plasma between

the anode and cathode, and turns it into thermal energy at a temperature in the range of

8000 -12,000 °C or as high as 20,000 °C initializing a substantial amount of heating and

melting of material on the surface of each pole. When the pulsating direct current power

supply occurring between 20,000 and 30,000 Hz is turned off, the plasma channel breaks

down [5]. This causes a sudden reduction in the temperature allowing the circulating

dielectric fluid to implore the plasma channel and flush the molten particles from the pole

surfaces in the form of microscopic debris. While the material removal mechanisms of

WEDM and EDM are similar, their functional characteristics are not identical. WEDM

uses a thin wire continuously feeding through the work piece by a microprocessor, which

enable parts of complex shapes to be machined with exceptional high accuracy [6]. A

varying degree of taper ranging from ISO for a 100 mm thick to 30" for a 400 mm thick

work piece can also be obtained on the cut surface. The microprocessor also constantly

maintains the gap between the wire and the work piece, which varies from 0.025 to

0.05mm [7]. WEDM eliminates the need for elaborate pre-shaped electrodes, which are

commonly required in EDM to perform the roughing and finishing operations [7]. In the

case of WEDM, the wire has to make several machining passes along the profile to be

machined to attain the required dimensional accuracy and surface finish (SF) quality.

5

1.2.3 Material Removal Rate (MRR)

The machining performance evaluation are using material removal rate (MRR).

When electrodes were used with positive polarity in all cases of semi-sintered electrodes,

the MRR increased. By using EDM-C3 with positive polarity the highest MRR and

minimal wear were obtained. The copper electrode gave the highest electrode wear ratio.

The results of electrode wear ratio relate to melting point which is materials with higher

melting points wear less [8]. However, the wear ratio is inversely proportional to the

MRR result [8]. In the case of lower MRR, the electrode must spend more time to

achieve machining. The positive polarity gives better MRR than negative polarity [8].

This result is the same as for EDM on a conductive material [8]. This can be explained by

the fact that positive polarity gives better machining by causing a higher MRR under

higher discharge energy [8].

6

1.2.4 Surface finish (SF)

Product designers always determined to design machinery that can run faster, last

longer, and operate more accurately than ever. Modern development of high speed

machines has resulted in increased speeds of moving parts and higher loading. Most

manufacturing processes produce parts with surfaces that are either unsatisfactory from

the standpoint of geometrical surface and to correct specific irregularities and so must be

applied carefully to a given production sequence. Each process is a final operation in the

machining sequence for a precision part and is commonly preceded by conventional

grinding [9]. This primer begins by explaining how industry controls and measures the

precise degree of smoothness and roughness of a finished surface.

1.2.5 Cutting rate (CR)

The rate at which the cutting tool and the work piece move in relation to one

another. In the present study, cutting rate is a measure of job cutting which is digitally

displayed on the screen of the machine and is given quantitatively in mm/min.

1.2.6 Titanium Alloy (Ti 6Al 4V)

Pure titanium undergoes an allotropic transformation from the hexagonal close-

packed alpha phase to the body-centered cubic beta phase at a temperature of 882.5°C

(1620.5°F). Alloying elements can act to stabilize either the alpha or beta phase. Through

the use of alloying additions, the beta phase can be sufficiently stabilized to coexist with

alpha at room temperature. This fact forms the basis for creation of titanium alloys that

can be strengthened by heat treating. Titanium alloys are generally classified into three

main categories: Alpha alloys, which contain neutral alloying elements (such as Sn)

and/or alpha stabilizers (such as Al, O) only and are not heat treatable; Alpha + beta

alloys, which generally contain a combination of alpha and beta stabilizers and are heat

7

treatable to various degrees; and Beta alloys, which are metastable and contain sufficient

beta stabilizers (such as Mo, V) to completely retain the beta phase upon quenching, and

can be solution treated and aged to achieve significant increases in strength [10]. Ti 6Al-

4V is known as the "workhorse" of the titanium industry because it is by far the most

common Ti alloy, accounting for more than 50% of total titanium usage. It is an alpha +

beta alloy that is heat treatable to achieve moderate increases in strength [11]. Ti 6Al-4V

is recommended for use at service temperatures up to approximately 350°C (660°F) . Ti

6Al-4V offers a combination of high strength, light weight, formability and corrosion

resistance which have made it a world standard in aerospace applications [10].

1.3 Problem Statement

If the cutting process by WEDM machine is not in optimum parametric, the

product or the component required the heavy grinding and polishing process. If the

optimal parameters are not predicted, the technician also has to waste time to get the

optimal parameters. Due to the problems, it will waste time to produce the product and

component at once wasting the cost to hire the labor for overtime.

1.4 Objective

The wire-cut electrical discharge machining is commonly used in aerospace,

ordinance, automobile and general engineering industries to obtain intricate and complex

shapes [12]. Moreover machine tool tables provided by the manufacturer often do not

meet the requirements in machining for particular material [12]. So, to obtain various

shapes of structural components the wire-cut EDM process and improving the machining

efficiency which is produce the product that have lowest surface roughness it requires the

models to predict optimum parametric combinations accurately[12].

8

1.5 Scope of Project

The scope of the project is more to predict the optimum parametric for the

Titanium alloys [13]. The work piece will be cut and the surface roughness will be

measure.

1.6 Significant of Project

One of significant of this study is facilitate the engineer’s work which is engineer

no need to measure the WEDM parameters for cutting the titanium alloy anymore.

Engineers only just refer to this study. It is at once shortening the time-to-market for the

products or components [14]. Because of that, the company can save the time and cost.

1.7 Summary

This research consists of six chapters. Chapter 1 is the introduction about this

study which has been discussed briefly about project background, problem statement,

objective, scope of project and significant of project. This chapter is the fundamental for

the project and the guidelines for this research. Chapter 2 is the literature review which

discusses methods and findings previously done by other people which are related to the

study. Chapter 3 is the Methodology which explains the approaches and methods used in

performing the research. Chapter 4 is the chapter which reports the outcomes or results of

this research. Chapter 5 is the discussion from the project. The chapter 6 consists of the

recommendation and the chapter 7 is the conclusion of the research.

9

CHAPTER 2

LITERATURE REVIEW

2.1 Introduction

Literature review is one of the scope studies for this research. It works as guide to

run this experiment for this research. It will give part in order to get the information about

wire electrical discharge machine (WEDM) and will give idea to run the experiment.

From the early stage of the project, a variety of literature studies have been done.

Research journals, printed or online conference article were the main source in the project

guides. This part will include almost entire of the operation including the history, test,

machining properties and results.

2.2 Review of journals

The wire-cut electrical discharge machining (WEDM) is commonly used in

aerospace, ordinance, automobile and general engineering industries. For this study, the

10

several journals that I analyze have the same objective with this study which is determine

appropriate machining parameters to improve surface quality. The conclusion of the

entire journal proved that, peak current (IP) and pulse duration are the most significant

parameters. The investigating of the viability and dependability of the magnetic rough

media for finishing machined surface had proved that the magnetic force assisted EDM

had a better machining stability, since the wreckage driven by the assisted magnetic force

would be expelled more quickly and completely to reduce abnormal discharge. [14]

Investigation the effect of machining parameters on kerf statistically in WEDM had

proved that the highly effective parameters on both the kerf and the MRR were found as

open circuit voltage and pulse duration, while wire speed and dielectric flushing pressure

were less effective factors. [1] To present an efficient method by means of which to

determine appropriate machining parameters so as to be able to achieve the objective of

the shortest machining time whilst at the same time satisfying the requirements of

accuracy and surface roughness. It is found the table feed and pulse-on time have a

significant influence on the metal removal rate, the gap voltage and the total discharge

frequency, whilst the gap width and the surface roughness are mainly influenced by the

pulse-on time. [15] Modeling the machining parameters of wire electrical discharge

machining of Inconel 601 using Response Surface Methodology (RSM) study has proved

its adequacy to machine Inconel 601 material under acceptable volumetric material

removal rate which reached 8 mm3/min and surface finish (Ra) less than 1µm.[2] On the

research of to predict the optimum parametric combination accurately due to improve the

machining efficiency, it is found that, the parameters IP and TON have the most significant

effect on surface roughness due to the fact that the energy content of a single spark

discharge can be expressed as a product of TON and IP known as discharge energy.[12]

11

Table 2.1: Journals Comparison

No Author and Title Description Finding

1 Y.S. Liao, J.T.

Huang, Y.H.

Chen – A study to

achieve a fine

surface finish in

Wire-EDM

The objectives of this research are:

1. To obtain a fine surface.

2. To improve surface quality and

achieve an optimal surface

roughness in finishing process

This research is considering those

controlling factors:

1. Pulse-generating circuit (PS)

2. Conductivity of the dielectric

(K)

3. Resistance in the circuit (R)

4. Capacitance in the circuit (C)

5. Applied voltage (V)

6. Feed rate of the table (F)

7. Pulse-off time (Toff)

8. Error, e

A dc pulse-

generating circuit

of positive polarity

(wire electrode is

set as anode) can

achieve a better

surface roughness

in finishing

operation.

2 Yan-Cherng Lin,

Yuan-Feng Chen,

Der-An Wang,

Ho-Shiun Lee –

Optimization of

machining

parameters in

magnetic force

assisted EDM

based on Taguchi

Method.

The investigating of the feasibility and

reliability of the magnetic abrasive

media for finishing machined surface.

The control parameters:

1. Machining polarity (P)

2. Peak current (IP)

3. Auxiliary current with high

voltage (IH)

4. Pulse duration (τP)

5. No-load voltage (V)

6. Servo reference voltage (SV)

By using Taguchi method: 6 factors, 3

levels = L18

The magnetic force

assisted EDM had a

better machining

stability, since the

wreckage driven by

the assisted

magnetic force

would be expelled

more quickly and

completely to

reduce abnormal

discharge.

12

Work piece – SKD 61 steel

Electrode – electrolytic copper

3 Nihat Tosun, Can

Cogun, Gul

Tosun – A study

on kerf and

material removal

rate in wire

electrical

discharge

machining based

on Taguchi

method.

Investigate the effect of machining

parameters on kerf statistically in

WEDM.

The controlling parameters:

1. Open circuit voltage (V)

2. Pulse duration (µs)

3. Wire speed (m/min)

4. Flushing pressure (kg/cm2)

By using Taguchi method: 4 factors, 3

levels = L18

Work piece – AISI 4140 steel (DIN

42CrMo4)

Electrode – CuZn37 Master brass wire

Finding – the

highly effective

parameters on both

the kerf and the

MRR were found as

open circuit voltage

and pulse duration,

whereas wire speed

and dielectric

flushing pressure

were less effective

factors.

4 Y.S. Liao, J.T.

Huang, H.C. Su –

A study on the

machining-

parameters

optimization of

wire electrical

discharge

machining.

To present an efficient method by

means of which to determine

appropriate machining parameters so as

to be able to achieve the objective of

the shortest machining time whilst at

the same time satisfying the

requirements of accuracy and surface

roughness.

The controlling parameters:

1. Table feed

2. Pulse-on time

3. Pulse-off time

4. Wire speed

5. Wire tension

6. Flushing

By using Taguchi method : 6 factors, 3

Finding – it is

found the table feed

and pulse-on time

have a significant

influence on the

metal removal rate,

the gap voltage and

the total discharge

frequency, whilst

the gap width and

the surface

roughness are

mainly influenced

by the pulse-on

time.

13

levels = L18

Work piece – SKD11 alloy steels

Electrode – brass wire

5 M.S. Hewidy,

T.A. El-Taweel,

M.F.Safty –

Modelling the

machining

parameters of

wire electrical

discharge

machining of

Inconel 601 using

RSM

The objective of the mathematical

models is to achieve higher machining

productivity with a desired accuracy

and surface finish.

Process parameters :

1. Peak current (IP)

2. Duty factor

3. Wire tension

4. Water pressure

By using RSM = 31 no of experiments

Work piece – Inconel 601

Electrode – Brass CuZn377

Finding – WEDM

has proved its

adequacy to

machine Inconel

601 material under

acceptable

volumetric material

removal rate which

reached 8 mm3/min

and surface finish

(Ra) less than 1µm.

6 Pujari Srinivasa

Rao, Beela

Satyanarayana,

Koona Ramji –

Effect of WEDM

conditions on

surface roughness

: A parametric

optimization

using Taguchi

method.

The objective of this research is to

predict the optimum parametric

combination accurately due to improve

the machining efficiency.

The controlling parameters:

1. Pulse-on time

2. Pulse-off time

3. Peak current

4. Flushing pressure of dielectric

fluid

5. Wire feed rate setting

6. Wire tension setting

7. Spark gap voltage setting

8. Servo feed setting

Taguchi method – 7 factors, 3 level =

L18

From the ANOVA

and S/N ratio

calculations, it is

found that, the

parameters IP and

TON have the most

significant effect on

surface roughness

due to the fact that

the energy content

of a single spark

discharge can be

expressed as a

product of TON and

IP known as

discharge energy

14

Work piece – Aluminium-24345

7 Muthu Kumar,

Suresh Babu,

Venkatasamy and

Raajenthiren –

Optimization of

the WEDM

parameters on

machining

Incoloy800 Super

alloy with

Multiple Quality

Characteristics

Investigation of the multi-response

optimization of WEDM process for

machining Incoloy 800 using

combination of Grey Relational

analysis and Taguchi method to achieve

higher Material Removal Rate (MRR),

lower surface roughness (Ra) and Kerf

width (k).

The controlling parameters :

1. Gap voltage

2. Pulse-on time

3. Pulse-off time

4. Wire feed

Work piece – Incoloy800

Electrode – brass wire

By using Grey Taguchi method – 4

factors, 3 levels = L9

The optimal

process parameters

based on Grey

Relational Analysis

for the Wire-Cut

EDM of

Incoloy800 include

a 50 V gap voltage,

10 µs pulse-on

time, 6 µs pulse-off

time and 8

mm/minute Wire

Feed rate.

8 H. Singh, R. Garg

– Effects of

process

parameters on

material removal

rate in WEDM

Investigations to reveal the process

parameters impact on material removal

rate of hot die steel (H-11)

Controlling parameters :

1. Pulse-on time

2. Pulse-off time

3. Spark gap set voltage

4. Peak current

5. Wire feed

6. Wire tension

Work piece – hot die steel H-11

Electrode – brass wire

By using one factor at a time approach.

The finding is the

material removal

rate (MRR) directly

increase in pulse-on

time (TON) and peak

curent (IP) while

decreases with

increase in pulse-

off time (TOFF) and

servo voltage (SV).

15

9 Anish Kumar,

Vinod Kumar,

Jatinder Kumar –

Prediction of

surface roughness

in wire electric

discharge

machining

(WEDM) process

based on

Response Surface

Methodology.

The objective of this study is the

investigation of pulse-on time, pulse-off

time, peak current, spark gap voltage,

wire feed and wire tension effect on

surface roughness.

Controlling parameters :

1. pulse-on time

2. pulse-off time

3. peak current

4. spark gap voltage

5. wire feed

6. wire tension

work piece – pure titanium (grade-2)

electrode – brass wire

RSM method = 54 experiments order

The surface

roughness was

ranged from

2.48μm to 2.62μm

during WEDM of

pure titanium. The

minimum surface

roughness was

obtained for the

process parameter

combination given

by Ton=112μs,

Toff=56μs,

Ip=120A, SV=60V,

WF = 7m/min and

WT = 980 grams.

The percentage

contribution of

input parameters

given by Ton: 55%,

Toff: 28%, Ip: 8%,

SV: 6% and error:

3%.

10 R.

Ramakrishnan,

L.

Karunamoorthy

– Modeling and

multi-response

To predict the performance

characteristic namely material removal

rate and surface roughness, artificial

neural network models were developed

using back-propagation algorithms.

Controlling parameters :

By an increase of

pulse on time and

ignition current, the

effect of MRR was

improved. But at

higher rates of

16

optimization of

Inconel 718 on

machining on

machining of

CNC WEDM

process.

1) Pulse-on time

2) Pulse-off time

3) Wire feed speed

4) Ignition current

Work piece – Inconel 718

Electrode – brass wire

By using Taguchi method – 4 factors, 3

levels =L9

pulse on time and

ignition current the

surface quality of

the work specimen

was affected.

2.3 Gaps in Literature Review

After a comprehensive study of the existing literature, a number of gaps have been

observed in machining of WEDM.

The previous researchers have investigated effect of other process parameters on

the performance measures of the specimen.

The effects of machining parameters on hot working titanium alloy Ti 6A 4Al

has not been explored using WEDM with brass wire as electrode.

17

CHAPTER 3

METHODOLOGY

3.1 Introduction

Current chapter generally discusses methodology of the project, with a focus on

electric discharge machine (EDM) experiment and machining. Pertinent data collection is

done in order for further research analysis in next chapter. This chapter contains the

methodology to conduct this study. Methodology involves Design of Experiment (DOE),

the problem identification and solving, and detail experimental design. This project

consists of two semesters. The proposal, literature review and methodology planning

were conducted in semester 1 of this project. It is also including the study of electric

discharge machine (EDM). The semester two concludes the preparation of work pieces

and experimental tools, running experiment, and get data collection do the analysis.

18

Start

End

Topic discussion

Literature review

Survey for material and equipment

Propose the experimental design

Determine test condition

Run the experiment

Analyze the result

Main effect plot, best parameters

Confirmation test

3.2 Gathering Information

Flow chart 3.1: The investigation flow

19

3.3 Material preparation

The most important thing is material selection to this experiment because

different materials have different working parameters depending on their properties. In

processes related to the EDM the right selection of the machining material is also the

most important aspect to take into consideration. From the observation at the workshop in

Mechanical Engineering Faculty in UiTM Shah Alam and discussion with partner and

supervisor, the work piece that has been selected is Titanium Alloy (Ti 6Al 4V) while the

wire electrode is brass wire.

3.3.1 Work piece material

The work piece material was titanium alloy (Ti 6Al 4V) and its dimensions were

6mm x 5mm x 50mm. Titanium alloy (Ti 6Al 4V) have the low weight ratio high

strength, and outstanding corrosion resistance inherent. In order that, it is has led to a

wide and diversified range of successful applications which demand high levels of

reliable performance in automotive, power generation, aerospace, oil and gas extraction,

and other major industries. In the majority of these and other engineering applications

titanium has replaced heavier, less practical or less cost effective materials. Reliable,

economic and tougher systems and components should be taken into account in designing

with titanium, which in many situations have considerably exceeded performance and

service life prospect. Titanium is available in several different grades.

20

Figure 3.1: Titanium Alloy Ti 6Al 4V

3.3.2 Wire Electrode

The electrode material was brass wire which is the most common material of tool

electrode used in WEDM industries. The electrode front face was 0.25 mm diameter.

Figure 3.2: Brass Wire

21

3.4 Selection of the machining parameter (factor) and their level

According to Taguchi method, L27 mixed orthogonal arrays table was chosen for

the experiments. The four factors chosen are pulse-off time, wire feed, wire tension and

peak current. Each parameter was designed to have three levels.

Table 3.1: Parameters and Their Levels

PARAMETER

LEVEL

L1 L2 L3

Pulse-off time 1 3 5

Peak current 8 9 10

Wire tension 8 9 10

Wire feed 8 9 10

3.4.1 Pulse off Time

The pulse off time is referred as Toff and it represents the duration of time in

between the two simultaneous sparks. The voltage is not present during this part of the

cycle. The Toff setting time range available on the machine tool is 1-5 which is applied in

steps of 2 units. With a lower value of Toff, there is more number of discharges in a given

time which is resulting in increase in the sparking efficiency. As a result, the cutting rate

also increases. The wire breakage may occur by using very low values of Toff period,

which in turn reduces the cutting efficiency. As and when the discharge conditions

become unstable, the Toff period can be increase for stabilize the conditions. This will

allow lower pulse duty factor and will reduce the average gap current.

3.4.2 Peak Current

The peak current is represented by IP and it is the maximum value of the current

passing through the electrodes for the given pulse. 8–10 ampere is the IP setting current

range available on the present WEDM which is applied in steps of 1 ampere. Increase in

22

the IP value will increase the pulse discharge energy which in turn can improve the

cutting rate further. For higher value of IP, gap conditions may become unstable with

improper combination of Ton, Toff, SV & SF settings.

3.4.3 Wire Feed

Wire feed is the rate at which the wire-electrode travels along the wire guide path

and is fed continuously for sparking. 8–10 m/min is the wire feed range available on the

present WEDM in steps of 1m/min. It is always desirable to set the wire feed to

maximum. This will result in less wire breakage, better machining stability and slightly

more cutting speed.

3.4.4 Wire Tension

Wire tension determines how much the wire is to be stretched between upper and

lower wire guides. This is a gram-equivalent load with which the continuously fed wire is

kept under tension so that it remains straight between the wire guides. More the thickness

of job more is the tension required. Inaccuracies in the job will occur as well as wire

breakage if the parameter in improper setting of tension. The wire tension range available

on the machine is 8-10 units in steps of 1.

3.5 Design of experiment

In general usage, design of experiments (DOE) or experimental design is the design of any information-gathering exercises where variation is present, whether under the full control of the researcher or not. However, in statistics, these terms are usually used for controlled experiments. Formal planned experimentation is often used in evaluating physical objects, structures, components, materials and chemical formulations. Other types of study, and their design, are discussed in the articles on natural experiments, quasi-experiments, opinion polls and statistical surveys.

23

In the design of experiments, the researcher is often interested in the effect of some process or intervention on some objects, which may be people, parts of people, groups of people, animals, plants, etc. Design of experiments is thus a discipline that has very broad application across all the natural and social sciences and engineering.

24

Table 3.2: Design of Experiment

Experiment No Pulse-Off Time Peak Current Wire Tension Feed Rate

1 1 8 8 8

2 1 8 8 8

3 1 8 8 8

4 1 9 9 9

5 1 9 9 9

6 1 9 9 9

7 1 10 10 10

8 1 10 10 10

9 1 10 10 10

10 3 8 9 10

11 3 8 9 10

12 3 8 9 10

13 3 9 10 8

14 3 9 10 8

15 3 9 10 8

16 3 10 8 9

17 3 10 8 9

18 3 10 8 9

19 5 8 10 9

20 5 8 10 9

21 5 8 10 9

22 5 9 8 10

23 5 9 8 10

24 5 9 8 10

25 5 10 9 8

26 5 10 9 8

27 5 10 9 8

25

3.6 Specimen preparation

3.6.1 Procedure

The experiments were accomplished on a Mitsubishi FX series WEDM machine.

Following steps were followed in the cutting operation:

1. The wire was made vertical with the help of verticality block.

2. The work piece was mounted and clamped on the work table.

3. A reference point on the work piece was set for setting work co-ordinate system

(WCS). The programming was done with the reference to the WCS. The reference point

was defined by the ground edges of the work piece.

4. The program was made for cutting operation of the work piece and a profile of 10 mm

x 10 mm square was cut.

3.7 Constant machining parameters use in the cutting process

Table 3.3: The constant machining parameters uses in the cutting process in this

study

No Parameter Symbol Value Units

1 Pulse-on time Ton 1 µ sec

2 Flushing pressure of dielectric fluid WP 5 kg/cm2

3 Spark gap voltage setting SV 8 Volts

4 Servo feed setting SF 500 mm/min

3.7.1 Spark Gap Set Voltage

The spark gap set voltage is a reference voltage for the actual gap between the

work piece and the wire used for cutting. The SV voltage range accessible on the

machinery used in this study is 00 - 99 volt and is applied in steps of 1volt.

26

3.7.2 Pulse Peak Voltage

Pulse peak voltage setting is for selection of open gap voltage. Increase in the VP

value will increase the pulse discharge energy which in turn can improve the cutting rate.

The pulse peak voltage setting range available on the machine is either 1 or 2 .Normally

it is selected at value 2.

3.7.3 Flushing Pressure

Flushing Pressure is for selection of flushing input pressure of the dielectric. The

flushing pressure range on this machine is either 1 (High) or 0 (low). High input pressure

of water dielectric is necessary for cutting with higher values of pulse power and also

while cutting the work piece of more thickness. Low input pressure is used for thin work

piece and in trim cuts.

3.7.4 Servo Feed

Servo feed setting decides the servo speed; the servo speed, at the set value of SF,

can vary in proportion with the gap voltage (normal feed mode) or can be held constant

while machining (with constant feed mode).

The ranges of process parameters for the experiments were decided on the basis of

literature survey and the pilot experiments conducted using one factor at a time approach

(OFAT). Results of the pilot experiments are given in subsequent sections.

3.7.5 Pulse On-Time

Pulse on time is defined as the time during which the machining is performed.

The machining process becomes faster after increasing the pulse on time. If the pulse on

27

time increasing, the material removal rate also increasing. Because of that, it will produce

the poor surface finish on the specimen.

3.8 Measurement test and analysis Methodology

3.8.1 Cutting Rate (CR)

For WEDM, cutting rate is a desirable characteristic and it should be as high as

possible to give least machine cycle time leading to increased productivity. In the present

study cutting rate is a measure of job cutting which is digitally displayed on the screen of

the machine and is given quantitatively in mm/min.

3.8.2 Material Removal Rate (MRR)

Weight before machining, minus to weight after machining, divide to the time

taken for machining.

MRR = W (after machining)−W (before machining)

t

The quality of characteristic for MRR is the higher the better.

3.8.3 Surface Roughness (Ra)

Since irregularities in the surface may form nucleation sites for cracks or

corrosion, roughness is often a good predictor of the performance of a mechanical

component. Roughness is a measure of the texture of a surface. It is measured by the

vertical deviations of a real surface from its ideal form. If these deviations are large, the

surface is rough otherwise if these deviation if small, the surface is smooth. Roughness is

typically considered to be the higher frequency, shorter wavelength component of a

measured surface.

28

3.9 Taguchi method

Taguchi’s comprehensive system of quality engineering is one of the greatest

engineering achievements of the 20th century. This method focuses on the effective

application of engineering strategies. It includes both, shop-floor quality engineering and

upstream. Upstream methods competently use small-scale experiments to decrease

remain cost-effective and variability and robust designs for market place and large-scale

production. Shop-floor techniques provide real time methods for monitoring, maintaining

quality in production and cost-based. The farther upstream a quality method is applied,

the greater leverages it produces on the improvement, and the more it decreases the cost

and time.

3.9.1 Full Factorial

The full factorial design is the technique of defining and investigating all

conditions in an experiment while the fractional factorial design investigates only a

fraction of all the combinations. The Taguchi method has been proposed by simplifying

and standardizing the fractional factorial design. Taguchi method employs a special

design of orthogonal array to investigate the effects of the entire machining parameters

through small number of experiments. The methodology involves identification of

controllable and uncontrollable parameters and the establishment of a series of

experiments to find out the optimum combination of parameter which has greatest

influence on the performance and the least variation from the target of the design.

3.9.2 Signal-to-noise ratio

 The S/N ratio, as stated earlier, is a concurrent statistic. A concurrent statistic is

able to look at two characteristics of a distribution and roll these characteristics into a

29

single number or figure of merit. The S/N ratio combines the variance around this mean

and mean level of the quality characteristic into a single metric.

A high value of S/N implies that signal is much higher than the random effects of

noise factors. Process operation consistent with highest S/N always yields optimum

quality with minimum variation.

3.9.3 Orthogonal array

In selecting an appropriate OA, the pre-requisites are:

Selection of process parameters and/or interactions to be evaluated

Selection of number of levels for the selected parameters

The determination of parameters to investigate depends upon the product or

process performance characteristics or responses of interest. Several methods are

suggested by Taguchi for determining which parameters to include in an experiment.

a) Brainstorming

b) Flow charting

c) Cause-Effect diagrams

The total Degrees of Freedom (DOF) of an experiment is a direct function of total

number of trials. If the number of levels of a parameter increases, the DOF of the

parameter also increases because the DOF of a parameter is the number of levels minus

one. Thus, increasing the number of levels for a parameter increases the total degrees of

freedom in the experiment which in turn increases the total number of trials. Thus, two

levels for each parameter are recommended to minimize the size of the experiment [11].

If curved or higher order polynomial relationship between the parameters under study and

the response is expected, at least three levels for each parameter should be considered.

30

3.9.4 Analysis of Variance (ANOVA)

For the analysis of variance, the total sum of squares may be divided into four parts[:

The contribution due to the first order terms

The contribution due to the second order terms

A ‘Lack of fit’ component which measures the deviations of the response

from the fitted surface

Experimental error which is obtained from the centre points

3.10 Experimental and measurement equipment

3.10.1 Mitsubishi FX series WEDM flushing type

31

Display screen

Work tank

Work head

Power on/off

Keyboard

3.10.2 Portable surface roughness tester

32

Display screen

Parameter control Power on/off

Probe

3.10.4 Work piece weighing machine

33

Power on/off

Display screen

CHAPTER 4

EXPERIMENTAL RESULTS AND ANALYSIS: TAGUCHI METHOD

4.1 Introduction

The present chapter gives the application of the Taguchi Method. The design of

experiments was selected and the experiments were conducted to investigate the effect of

process parameters on the output parameters e.g. surface roughness, material removal

rate. The experimental results are discussed subsequently in this chapter. The selected

process variables were varied up to three levels and L27 orthogonal array was adopted to

design the experiments. The Taguchi Method was selected to design the experimental

design and to analyze the data through signal-to-noise(S/N) ratio.

34

4.2 Data Collection

4.2.1 Surface Roughness

Table above show the data collection of surface roughness data. The surface

roughness data collection recorded by using portable surface roughness tester. For each

experiment, three reading for surface roughness recorded which is at the starting point,

middle point and end point of the specimen. The graph of surface roughness versus no. of

experiment was plotted. The maximum surface roughness was at the experiment number

15 which is in the condition of lowest feed rate while the minimum surface roughness

was at the experiment number 19 which is in condition highest pulse-off-time and lowest

peak current.

35

Table 4.1: Surface Roughness by Portable Surface Roughness Tester

Experiment No

Start

(µm)

Middle

(µm)

End

(µm) Average Max Min

Max

Error

Min

Error

1 4.57 2.43 2.72 3.24 4.57 2.43 1.33 0.81

2 4.35 2.51 2.90 3.43 4.35 2.51 0.92 0.92

3 4.70 4.75 3.10 4.75 4.75 4.75 0.00 0.00

4 4.67 3.26 2.80 3.97 4.67 3.26 0.71 0.71

5 3.54 3.38 3.10 3.46 3.54 3.38 0.08 0.08

6 3.19 3.29 3.40 3.24 3.29 3.19 0.05 0.05

7 3.47 3.24 3.52 3.41 3.52 3.24 0.11 0.17

8 3.13 3.42 3.61 3.39 3.61 3.13 0.22 0.26

9 3.01 3.22 3.31 3.18 3.31 3.01 0.13 0.17

10 3.16 2.96 3.09 3.07 3.16 2.96 0.09 0.11

11 2.86 4.84 3.06 3.59 4.84 2.86 1.25 0.73

12 5.28 4.84 2.92 4.35 5.28 2.92 0.93 1.43

13 4.88 4.81 3.19 4.29 4.88 3.19 0.59 1.10

14 5.00 3.48 3.08 3.28 3.48 3.08 0.20 0.20

15 6.45 6.13 2.99 5.19 6.45 2.99 1.26 2.20

16 5.62 3.02 2.88 3.84 5.62 2.88 1.78 0.96

17 5.85 3.22 3.28 4.12 5.85 3.22 1.73 0.90

18 3.24 3.28 2.88 3.13 3.28 2.88 0.15 0.25

19 2.34 2.80 2.73 2.54 2.73 2.34 0.20 0.20

20 2.78 2.85 2.46 2.70 2.85 2.46 0.15 0.24

21 2.66 2.93 2.91 2.83 2.93 2.66 0.10 0.17

22 3.03 2.47 3.09 2.86 3.09 2.47 0.23 0.39

23 2.83 2.42 2.99 2.75 2.99 2.42 0.24 0.33

24 2.92 2.97 2.50 2.95 2.97 2.92 0.02 0.03

25 3.37 2.99 3.13 3.16 3.37 2.99 0.21 0.17

26 2.63 3.15 2.85 2.88 3.15 2.63 0.27 0.25

27 3.12 2.95 2.71 2.93 3.12 2.71 0.19 0.22

36

The surface roughnesses were taken at three points to get the accurate data surface

roughness of the specimen. The considered points are at the start point, middle point and

at the end point of the specimen as shown in figure 4.1. After completed the surface

roughness data taking process, the averages were calculated and the maximum and

minimum error are obtained to plot the graph 4.1.

Figure 4.1: Point of The Specimen’s Surface Roughness Taken

37

end

middle

start

Table 4.2: Feed Rate Cutting

Experiment No Feed Rate Cutting (mm/min)

Start End Average

1 7.105 13.482 10.294

2 7.409 13.274 10.342

3 7.433 11.559 9.496

4 8.851 7.230 8.041

5 8.829 7.261 8.045

6 8.913 13.724 11.319

7 8.910 13.772 11.341

8 10.369 13.740 12.055

9 9.115 8.835 8.975

10 8.028 13.772 10.900

11 7.797 13.796 10.797

12 6.728 13.700 10.214

13 9.501 7.704 8.603

14 7.888 9.888 8.888

15 9.041 13.784 11.413

16 9.343 7.767 8.555

17 10.642 13.712 12.177

18 10.099 9.456 9.778

19 8.347 13.736 11.042

20 7.005 6.507 6.756

21 8.554 10.414 9.484

22 9.855 7.206 8.531

23 9.338 7.108 8.223

24 9.612 13.712 11.662

25 10.740 9.146 9.943

26 9.962 9.383 9.673

27 10.433 9.268 9.851

38

4.2.3 Specimen Weight and the Time Taken

While cutting the specimen, each of the specimen and the time taken to cut the

specimen was collected. The time taken was depending on the peak current which is the

time taken to cut the specimen decrease while the peak current increase and the time

taken to cut the specimen increase while the peak current increase.

39

Table 4.3: Specimen Weight and the Time Taken

Experiment No

Specimen

Weight (g)

Time

Taken (s)

1 6.353 512

2 6.385 509

3 6.353 511

4 6.376 422

5 6.377 421

6 6.366 421

7 6.356 367

8 6.345 375

9 6.327 432

10 6.327 471

11 6.310 469

12 6.227 468

13 6.240 379

14 6.248 375

15 6.233 378

16 6.244 390

17 6.220 404

18 6.222 388

19 6.212 470

20 6.207 468

21 6.190 471

22 6.174 424

23 6.166 423

24 6.162 423

25 6.140 393

26 6.124 328

27 6.125 326

40

4.2.4 Surface Roughness, Material Removal Rate and Cutting Rate

The WEDM experiments were conducted, with the process parameter levels set as

given in Table 4.4, to study the effect of process parameters over the output parameters.

Experiments were conducted according to the test conditions specified by L27 orthogonal

array design. Experimental results are also given in Table 4.4 for cutting rate, surface

roughness, and material removal rate. Altogether 27 experiments were conducted using

Taguchi Method.

From the data collection, the significant factor that affecting the material removal

rate is peak current which is the material removal rate increasing by increasing the peak

current. Peak current also was the significant factor that affecting the time taken to cut the

specimen. For the surface roughness, the significant factor that affecting the surface

roughness was the wire tension which is the surface roughness increasing by decreasing

the wire tension.

41

Table 4.4: The Surface Roughness, Material Removal Rate and Cutting Rate

Experimen

t No

Pulse-Off

Time

Peak

Current

Wire

Tension

Feed

Rate

SR

(µm)

MRR

(g/s)

CR

(mm/

min)

1 1 8 8 8 3.240 0.012 10.294

2 1 8 8 8 3.430 0.013 10.342

3 1 8 8 8 4.750 0.012 9.496

4 1 9 9 9 3.965 0.015 8.041

5 1 9 9 9 3.460 0.015 8.045

6 1 9 9 9 3.240 0.015 11.319

7 1 10 10 10 3.410 0.017 11.341

8 1 10 10 10 3.387 0.017 12.055

9 1 10 10 10 3.180 0.015 8.975

10 3 8 9 10 3.070 0.013 10.900

11 3 8 9 10 3.587 0.013 10.797

12 3 8 9 10 4.347 0.013 10.214

13 3 9 10 8 4.293 0.016 8.603

14 3 9 10 8 3.280 0.017 8.888

15 3 9 10 8 5.190 0.016 11.413

16 3 10 8 9 3.840 0.016 8.555

17 3 10 8 9 4.117 0.015 12.177

18 3 10 8 9 3.133 0.016 9.778

19 5 8 10 9 2.535 0.013 11.042

20 5 8 10 9 2.697 0.013 6.756

21 5 8 10 9 2.833 0.013 9.484

22 5 9 8 10 2.863 0.015 8.531

23 5 9 8 10 2.747 0.015 8.223

24 5 9 8 10 2.945 0.015 11.662

25 5 10 9 8 3.163 0.016 9.943

26 5 10 9 8 2.877 0.019 9.673

27 5 10 9 8 2.927 0.019 9.851

42

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 270.00

1.00

2.00

3.00

4.00

5.00

6.00

Surface Roughness

No of Experiments

Surf

ace

roug

hnes

s

Graph 4.1: Graph Surface Roughness versus Number of Experiment

Graph 4.1 shows that the surface roughness of the entire specimen was uneven. In

overall, the specimen that has the highest surface roughness is specimen 15 which is had

been cut at the highest wire tension which is 10 and lowest wire speed which is 8 at

5.19µm. Otherwise, the specimen that has the lowest surface roughness is specimen 19

which is had been cut at the lowest peak current and highest wire tension. In this case the

significant parameters are peak current and wire speed.

43

1 2 3 4 5 6 7 8 9 1011 1213 1415 161718 1920 2122 232425 26270.0000

0.0020

0.0040

0.0060

0.0080

0.0100

0.0120

0.0140

0.0160

0.0180

0.0200

MRR

MRR

No of Experiment

MRR

Graph 4.3 MRR versus No of Experiment

Graph 4.3 shows that the material removal rate of the entire specimen was

uneven. In overall, the specimen that has the highest surface roughness is specimen 27

which is had been cut at the highest pulse-off-time which is 5 and highest peak current

which is 10 at 0.188 g/s. Otherwise, the specimen that has the lowest material removal

rate is specimen 1 which is had been cut at the lowest pulse-off-time, peak current, wire

tension and wire feed at 0.0124. In this case the significant parameters are pulse-off-time,

peak current and wire speed.

44

4.2.5 Signal to Noise Ratio

Table 4.5.: Signal-to-Noise Ratio for Surface Roughness

Leve

l Pulse-Off Time Peak Current Wire Tension Feed Rate

1 -11.0779 -10.5728341 -10.75328343 -11.3274

2 -11.83559816 -10.9581219 -10.64734816 -10.3524

3 -9.073962523 -10.4565381 -10.58686258 -10.3076

The signal-to-noise-ratio for surface roughness was lowest at the first level of

pulse-off-time, wire tension and feed rate. This shows that pulse-off-time, wire tension

and feed rate is the significant parameters to the surface roughness.

Figure 4.1: Effects of Process Parameters on Surface Roughness (S/N Data)

45

Table 4.6: Signal-to-Noise Ratio for Material Removal Rate

Leve

l Pulse-Off Time Peak Current Wire Tension Feed Rate

1 -36.77534892 -37.7108079 -24.70417734 -36.2865

2 -36.37133627 -36.2559502 -36.33523968 -36.387

3 -36.48528973 -35.6652168 -36.3486579 -36.6744

The signal-to-noise-ratio for material removal rate was highest at the third level of

pulse-off-time and peak current. This shows that pulse-off-time and peak current is the

significant parameters to the material removal rate.

Figure 4.3: Effects of Process Parameters on Material Removal Rate (S/N Data)

46

Table 4.7: Signal-to-Noise Ratio for Cutting Rate

Level Pulse-Off Time Peak Current Wire Tension Cutting Rate

1 18.89938701 22.71033485 18.42785025 26.49133

2 19.9677491 14.5027131 26.64473055 13.65512

3 21.15596541 22.81005358 14.95052073 19.87665

In this study, the cutting rate was not considered due to the problem while the data

collection process.

Figure 4.5: Effects of Process Parameters on Cutting Rate (S/N Data)

47

4.2.6 Main Effects Plot for Means (Raw Data)

Figure 4.2: Effects of Process Parameters on Surface Roughness (Raw Data)

Figure 4.4: Effects of Process Parameters on Material Removal Rate (Raw Data)

48

Figure 4.6: Effects of Process Parameters on Cutting Rate (Raw Data)

49

CHAPTER 5

DISCUSSION

1. In this investigation, the best parametric combination was obtained. The

conclusion done by considering the set of parameters that produce the lowest

signal-to-noise ratio for surface finish and the higher signal-to-noise ratio

material removal rate.

2. From this investigation, the set of parameters that has the minimum surface

finish is experiment number 15 which is have the reading of surface roughness

5.190 µm.

3. The signal-to-noise-ratio for surface roughness was lowest at the first level of

pulse-off-time, wire tension and feed rate.

4. This shows that pulse-off-time, wire tension and feed rate is the significant

parameters to the surface roughness.

5. The higher material removal rate seen at the set of parameters no 26 and 27 with

the material removal rate 0.019 g/s.

6. The signal-to-noise-ratio for material removal rate was highest at the third level

of pulse-off-time and peak current.

50

7. This shows that pulse-off-time and peak current is the significant parameters to

the material removal rate.

8. The cutting rate was not considered due to the problem while the data collection

process which certain data taken while the wire electrode had touched the

material and the others data taken while the wire electrode do not touch the

material. So that, the result is invalid.

51

CHAPTER 6

CONCLUSION

6.1 Introduction

In the previous chapters, the effects of process variables on response

characteristics (cutting rate, surface roughness, material removal rate) of the wire

electric discharge machining (WEDM) process have been discussed. An optimal set of

process variables that yields the optimum quality features to machined parts produced by

WEDM process has also been obtained. The important conclusions from the present

research work are summarized in this chapter.

6.2 Conclusions

For the conclusion, the best parameter to obtain the various shapes of structural

components the wire-cut EDM process and improving the machining efficiency which is

produce the product that have lowest surface roughness is the parameters with the

minimum feed rate, maximum pulse-off-time and maximum peak current.

52

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54