Experimental Investigation and Multi Objective Optimization for Wire EDM using Taguchi’s Method

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 06 | June -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1318
Experimental investigation and multi objective optimization for wire EDM
using Taguchi’s method
Kapil Kumar1, Pushpendra Kumar2, Shant Kumar Jain3, Sachin Kumar4
1 SR Group of Institution, Jhansi, Dr. APJ Abdul Kalam Technical University Uttar Pradesh, Lucknow
2,3 Assistant Professors, Dept. of Mechanical Engineering, SR Group of Institution, Jhansi, Uttar Pradesh, India
4 Assistant Professors, Dept. of civil Engineering, SR Group of Institution, Jhansi, Uttar Pradesh, India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract- Composite materials and alloys have increased
applications in many industries because of their good
mechanical characteristics such as strength to weight;
stiffness to weight, corrosion resistance,fatigueandthermal
expansion compared with metals. Due to its capability for
automation is a unique feature fulfilling the expectations of
modern manufacturing? EDM is an easy machining process
controlled by a large number of processes such as the pulse
duration; discharge frequency and discharge current
intensity. Any low variations in theparameterscanaffectthe
machining performance beyond the expectations. Selection
of machining conditions for improved machining
performance has great importance during EDM.Inthiswork
the effect of working with piece thickness and many other
process variations such as highest peak current, time, and
other characteristics as cutting rate, surface finish cum
roughness. Taguchi method deals with an orthogonal has
been used for doing experiment and research results. An
experimental cum mathematical model is developed
between process factors and responses as all factors
considering. In this paper a novel work is done for
minimization of machining work for the various machining
processes.
Key Words: Optimization, Taguchi’s method used for
surface roughness and analysis of variance.
1. INTRODUCTION
Electrical discharge machining (EDM) is a well known MRP
used to produce components of intricate shapes, qualityand
profiles as required in today’s scenario.Itisconsideredas an
ease of work of the EDM process that uses the electrodes to
initialize and sparking processes. Apart from this EDM it
utilizes a moving wire electrode which is made of slim
copper, brass or tungsten in the range of diameter 0.05–0.3
mm, which is capable of achieving very small corner radii.
During the EDM processes materials with samples are
eroded and developed the various stresses during
machining. In addition, the EDM process is capable to
machine the high strength including temperature resistive
(HSTR) and diminished the geometrical shapes and changes
occurring in the machining of hard to machine materials.
General applications of EDM includes the fabrication of the
stamping cum extrusion tools and dies, gauges, prototypes,
ships ;aircraft and medical parts with grinding wheel form
tools as its samples to work with and inspite of it there are
various other applications.
1.1 PURPOSE
As per todays demand for modern era, accurate modelling
method such as ANN can be used for interconnecting the
input parameters and machining performance
characteristics. Optimized set of parameters for more
thicknesses of work piece can be obtained using different
boundary conditions.Replicationofvarious experiments and
methods of working can be performed to increase the
accuracy. Experiments canbeperformedwithwider rangeof
input parameters as variables. Various machining
parameters can be tried out for its result accuracy and
verification of results.
2. WORK PIECE MATERIAL
In this the sample used for the experimentation of AISI D3
tool steel .As per requirement AISI D3 is high carbon-high
chromium steel developed for applications high
resistance2wear or to abrasion process and for resistance a
high pressure rather than to suddenshocks.Becauseofthese
qualities and its non-deforming properties, AISI D3 is
unsurpassed for die work on long production runs. In the
experiment the oil-hardening steel which hardens to a great
depth to better result? The production from a die after each
grind is uniform. As the impact strength is relatively low, by
proper adjustment of tool design and heat treatment
process. In this experiment a steel piece as sample has been
used for punche and dies on quite a heavy material being
used.

Figure -1: Work piece
Table -1: Mechanical Properties of Die Steel D-3
Densit
y
Melting
point
Yeild
strength
Elastic
modulu
Possi
on’s
Hard
ness
(g/cm³
) (ºC) (MPa) (GPa) Ratio
7.87 1421 470 190 0.28
18
HRC
Table-:2 Chemical composition of the work piece
material (DIE STEEL D-3) by weight
Material Fe Ni Mn Cr C Si Cu V Mo
%
Composit
ion
84.2
3
0.07
8
0.38
8
12.8
0
2.1
2
0.22
7
0.03
6
0.04
6
0.02
1
3. EXPERIMENTAL DESIGN METHODOLOGY
In this the experiments are conducted over the samples are
being used for testing and measurements of surface
roughness by using Taguchi’s methods are being used, and
results are obtained for establishements of prior studies. In
this experimental work an array force with all experiments
for design almost identical experiments and samples has
done. In this Taguchi’s method various results are analysed
as statistical methods to achieve one or more of the below
mentioned objectives:
1. To established the best or the optimum state for a
product or a process.
2. To estimate the contribution of various parameters
and relation with other parameters
3. To estimate the response under the optimum
condition as per required for better surface finish
and smoothness.
The best conditions are recognized by studying the main
effects of the parameters. The main effects of it indicate the
general trends of influence of each parameter and process.
The knowledge of contribution of individual parameters isa
key in deciding the nature of control to be established on a
production process. Taguchi suggeststwodifferentroutesto
carry out the analysis. First, the standard approach, where
the outcome of a single runis achieved.Thesecondapproach
of Taguchi’s method appeals for multiple runs is to use for
signal-to-noise ratio (S/N) for the same work in the analysis
as done experimentally.
Figure -2: The Taguchi and conventional quality loss
function
4. RESULT AND DISCUSSION
In this study an attempt has been made to find not only the
effect of work piece thickness while several other process
parameters and other overdifferentmachiningperformance
characteristics such as cutting rate, surface roughness, wire
wear ratio but also, an optimized set of parameters for the
work piece thickness is done. All of the obtained 35 set of
parameters for each work piece thickness are non-
dominated to each other; it means that no machining
characteristic can be further improved without worsening
the other machining characteristic. In the present work the
experiments are analysed on Minitab statistical software in
the lab and thus S/N values are obtained for the surface
finish and its analysis for future work and prospective to
work over it.EDM process is analysed and used by using
Taguchi’s method for better surface finish of the samples
which are used in its experiments

MeanofSNratios
4321
-28
-29
-30
-31
4321 4321
4321
-28
-29
-30
-31
4321
V Ip Ton
Toff p
Main Effects Plot for SN ratios for MRR
Signal-to-noise: Larger is better
MeanofMeans
4321
0.0400
0.0375
0.0350
0.0325
0.0300
4321 4321
4321
0.0400
0.0375
0.0350
0.0325
0.0300
4321
V Ip Ton
Toff p
Main Effects Plot for Means MRR
 After optimization highestcuttingrate9.6242mm2/min
(surface roughness-3.31 µm and wire wear ratio-
0.061576), lowest surface roughness 0.99 µm (cutting
rate-4.8765 mm2/min and wire wear ratio-0.023119)
and lowest wire wear ratio0.02146(cutting rate-6.0325
mm2/min and surface roughness-1.10 µm) for 5 mm
thickness has been obtained, which is far more better
than highest cutting rate 5.673 mm 2/min, lowest
surface roughness 1.56 µm and lowest wire wear ratio
0.034 obtained during experimentation.
 All of above three results show the effectivenessofusing
controlled NSGA II for multi-objective optimization.
 On performing confirmation experiments on some of
obtained set of parameters it was observed that for
cutting rate error %age varies from 2.612 to 7.213, for
surface roughness varies from 3.238 to 8.256 and for
wire wear ratio varies from 3.01 to 7.022.
5. CONCLUSIONS
More accurate modelling method such as ANN can be used
for interconnecting the input parameters and machining
performance characteristics. Optimizedsetofparameters for
more thicknesses of work piece can be obtained using
different boundary conditions. Replication of experiments
can be performed to increase the accuracy. Experimentscan
be performed with wider range of input parameters.
Different machining parameters can be tried out.
ACKNOWLEDGEMENT
We express sincere thanks to Er. Pushpendra Kumar
(Assistant Professor) in Mechanical Engineering
department SR Group of Institution, Jhansi for consistent
encouragement and support for shaping our project
thesis/dissertation in the presentable form. Words are
inadequate in offering our thanks to Dr.(Prof.) ArchnaLala
Group Director of SRGI, Jhansi, Er. Sachin Kumar
(Assistant Professor), and Er. Shant Kumar Jain (H.O.D)
in Mechanical engineering SR Group of Institution,Jhansi for
his kind cooperation for our Thesis/ Dissertation
REFERENCES
[1] K.H. Ho, S.T. Newman, S. Rahimifard, R.D. Allen, 2004,
State of the art in wire electrical discharge machining
(EDM), International Journal of Machine Tools &
Manufacture, Vol. 44, pp. 1247–1259.
[2] A. Ghosh, A. K. Mallik, 2010, Manufacturing Science,
Second Edition
[3] D. Ghodsiyeh, A. Golshan, J.A. Shirvanehdeh, 2013,
Review on Current Research Trends in Wire Electrical
Discharge Machining (EDM), Indian Journal of Science
and Technology, Vol. 6, pp. 4128-4140.
[4] H.A. Hofy, 2005, Advanced MachiningProcesses,McGraw-
Hill, Production Engineering Department, Alexandria
University, Egypt.
[5] Taguchi, GRA and entropy method, Frontiers of
Mechanical Engineering, Vol. 7, Issue 3, pp. 288–299.
BIOGRAPHIES
Kapil Kumar
M.Tech
Mechanical Engineering
Er. Pushpendra Kumar
Assistant Professor
SRGI, Jhansi
Er. Shant Kumar Jain
HOD, Mechanical EnggDepartment
SRGI, Jhansi
Er. Sachin Kumar
HOD, Civil Engg. Department
SRGI, Jhansi

Experimental Investigation and Multi Objective Optimization for Wire EDM using Taguchi’s Method

More Related Content

What's hot (20)

Similar to Experimental Investigation and Multi Objective Optimization for Wire EDM using Taguchi’s Method (20)

More from IRJET Journal (20)

Recently uploaded (20)

Experimental Investigation and Multi Objective Optimization for Wire EDM using Taguchi’s Method