parametric optimization of electro discharge machining ...die sinking edm and wire edm are two...
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IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015 | ISSN (online): 2321-0613
All rights reserved by www.ijsrd.com 3200
Parametric Optimization of Electro Discharge Machining Process for
MRR, Micro Hardness and Surface Roughness
Patel Umesh K1 Prof. Vidhya Nair
2
1,2Department of Mechanical Engineering
1,2LDRP – ITR, Gandhinagar
Abstract— The Electro Discharge Machining is a widely
accepted non-convection machining process. There are so
many process parameters which are statistically affects the
machining. Best combination of these parameters gives
excellent result. For current research pulse on time, pulse off
time, peak current and spark gap set voltage is selected to
optimize material removal rate. Surface roughness and
micro hardness is also optimizing for better result. The
analysis is based on Response surface Methodology.
Keywords: E.D.M., Taguchi Technique, ANOVA, Surface
Finish, MRR
I. INTRODUCTION
Electrical Discharge Machining is a one type of Non-
convectional machining Process. Non-convectional
processes are design to machine hard material and to
produce complex shapes which are not economical to
produce by convectional method. These methods become
more popular with the employment of CNC facilities.
Electrical Discharge Machining is most popular to make
very fine hole. Die sinking EDM and Wire EDM are two
widely used method of Electrical Discharge Machining.
Generally Wire Electrical Discharge Machining is used to
cut complex shape. These methods have found successful
applications in several important industries for machining
of components having complicated shapes made of hard
materials like tungsten carbides, super-alloys, ceramics,
refractory materials as well as common material.
Electrical discharge machining (EDM) is one of the
most extensively used non conventional material removal
processes. Its unique feature of using thermal energy to
machine electrically conductive parts regardless of hardness
has been its distinctive advantage in the manufacture of
mould, die, automotive, aerospace and surgical components.
In addition, EDM does not make direct contact between the
electrode and the workpiece eliminating mechanical
stresses, chatter and vibration problems during machining.
Today, an electrode as small as 0.1 mm can be used to „drill‟
holes into curved surfaces at steep angles without drill
„wander‟.
II. LITERATURE REVIEW
So many research papers and articles are survey on EDM
those are related to know the effect of process parameter on
performance of process. The materials investigated on EDM
are most of HSS, other Tool material, Hot Die material,
Cold Die material, Nickel alloys and Titanium alloys which
are hard compare to other material. These materials are AISI
M2, AISI D2, AISI D3, AISI D5, AISI H11, AISI 4140,
SKD 11, En 16, En 19, En 31, En 32, 1040, 2379, 2738,
Inconel, Ti alloys, Al alloys, 7131 cemented, Tungsten
Carbide (WC) etc. Different author use different
combination of process parameter. They analyze the
experimental data by plotting Interaction graphs, Residual
plots for accuracy and Response curves. Some other
methods used by different author for analysis of Taguchi‟s
DOE data regarding to EDM and EDM are Regression
analysis, Response Surface Methodology, Central
Composite Design (CCD), Feasible-Direction Algorithm,
SA algorithm, Pareto, Artificial Bee Colony (ABC), Grey
Relational Analysis, Genetic Algorithm, Fuzzy clustering,
Artificial Neural Network, Tabu-Search Algorithm,
Principle component method etc. Most of the author used
L27 Orthogonal Array. Generally the effect of Pulse ON
time, Pulse OFF time, Spark gap set Voltage, Peak current,
Flushing Pressure, Work piece height, wire tension and wire
feed on the material removal rate, surface roughness, kerf
and gap current is investigated.
I found in literature survey that nobody did a
process parameter optimization for SS410with Copper
Tungsten electrode. SS410is a low alloy high strength alloy
steel and Copper Tungsten has low wear rate so for present
work this material are selected for analysis and optimization.
III. EXPERIMENTAL PROCEDURE
The Conventional machining processes were developed to
machine the different kind of reinforcements. But they lost
their competitive edge to non-conventional machining
because of poor surface finish, high tool wear rate and high
tooling cost. To Increasing the weight ratio of Copper in has
high tensile strength, electrical conductivity and low
resistance. Powder metallurgy has been an effective method
of producing copper composite material. Tool can be made
up of copper and tungsten material. So increase production
rate, reduced machining cost, tool wear rate is decreased and
improved surface finish of the composite materials. So
Copper-tungsten compsite material is selected for current
project work.
IV. DESIGN OF EXPERIMENTS
A. Selection of orthogonal array
Three level of variable process parameter is chosen for
convenience for experiment and analysis. Based on the
literature survey the levels are decided. Table 4 show the
process parameter called factor, their symbol, units and
range as a machine units and actual units.
The following parameters are remaining constant
during process:-
1) Tool Material : Copper-Tungsten Composite
2) Work piece Material : SS410
3) Dielectric Fluid : Deionized Water
4) Flushing Pressure : 12 kgf/cm
Parametric Optimization of Electro Discharge Machining Process for MRR, Micro Hardness and Surface Roughness
(IJSRD/Vol. 3/Issue 03/2015/797)
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Level 1 Level 2 Level 3
Pulse ON time 70 90 100
Pulse OFF time 50 60 90
Peak current 10 15 20
Servo Voltage 35 40 45
Pulse ON time 70 90 100
Table-1&2 Levels of various control factors (A) (B) (C) (D)
1 70 50 10 35
2 70 50 10 35
3 70 50 10 35
4 70 60 15 40
5 70 60 15 40
6 70 60 15 40
7 70 90 20 45
8 70 90 20 45
9 70 90 20 45
10 90 50 15 45
11 90 50 15 45
12 90 50 15 45
13 90 60 20 35
14 90 60 20 35
15 90 60 20 35
16 90 90 15 40
17 90 90 15 40
18 90 90 15 40
19 100 50 20 40
20 100 50 20 40
21 100 50 20 40
22 100 60 15 45
23 100 60 15 45
24 100 60 15 45
25 100 90 15 30
26 100 90 15 30
27 100 90 15 30
Table- 2 T a g u c h i L 2 7 OA
B. Selection of material
An SS410is a high strength, low alloy steel that finds its best
application where there is need for more strength per unit of
weight. Less of this material is needed to fulfill given
strength requirements than is necessary with regular carbon
steels. Grade 50 is used in general plate applications when
the plate will be riveted, bolted, or welded. Grade 50 is a
Columbium-Vanadium steel that offers a minimum yield of
50,000 PSI. In addition, SS410 Grade 50 is noted for its
increased resistance to atmospheric corrosion. Grade 50
contains more alloying elements than plain carbon steel and
thus is somewhat more difficult to form. Grade 50 is more
difficult to cold work, but can be successfully bent or shaped
but requires more force than plain carbon steel.
Machinability is rated at 66%, Average cutting speed 110
ft/min. Easily welded by all commercial methods.
Constitute element % contribution
Carbon (C) 0.23
Manganese (Mn) 1.35
Silicon (Si) 0.15-0.4
Phosphorus (P) 0.04
Sulfur (S) 0.05
Vanadium (V) 0.01-0.05
Niobium (Nb) 0.005-0.05
Table-3: Chemical Composition of AISI A2 Tool Steel
C. Experimental work
The experiments willperformed on F-50 SPARK EROSION
MACHINE. the Following steps will followed in the cutting
operation. First A tool will mounted on machine, The work
piece is mounted on the work table, The program is made
for drill to work piece, All constant parameter are set first
and then the variable parameters are set for first reading as
per Taguchi‟s T27 array.After drilling first piece the
variable parameters are set for second drill.The required
measurements are continuously carried out during and after
drilling operation.
Fig. 1: Wire cut EDM Machine
SR NO MRR SR MH
1 0.9878 2.23 171.6
2 0.9500 2.21 172.3
3 0.9697 2.15 170.5
4 0.9073 1.00 180.1
5 0.8859 1.81 181.2
6 0.8974 1.80 182.0
7 0.6821 1.79 185.3
8 0.6985 1.78 185.7
9 0.8021 1.75 186.4
10 1.1982 2.10 201.0
11 1.1966 2.08 201.6
12 1.1916 2.09 202.0
13 1.1767 2.11 167.0
14 1.1752 2.06 168.4
15 1.1703 2.07 164.0
16 0.5346 1.70 192.0
17 0.5401 1.65 191.5
18 0.5214 1.68 189.4
19 1.4003 2.02 196.0
20 1.3823 1.90 195.8
21 1.3511 2.04 197.0
22 1.0684 1.95 204.0
23 1.4190 1.96 207.6
24 1.0947 1.94 204.8
Parametric Optimization of Electro Discharge Machining Process for MRR, Micro Hardness and Surface Roughness
(IJSRD/Vol. 3/Issue 03/2015/797)
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25 1.0059 1.90 188.0
26 1.0026 1.89 190.0
27 1.0075 1.88 187.0
V. ANALYSIS BY RESPONSE SURFACE METHODOLOGY (RSM)
1009070
1.2
1.1
1.0
0.9
0.8
906050
201510
1.2
1.1
1.0
0.9
0.8
454035
TON
Me
an
TOFF
I V
Main Effects Plot for MRRData Means
45
0.7 40
0.8
0.9
10
1.0
15 3520
MRR
V
I
TON 85
TOFF 70
Hold Values
Surface Plot of MRR vs V, I
45
1.50 40
1.65
1.80
10
1.95
15 3520
SR
V
I
TON 85
TOFF 70
Hold Values
Surface Plot of SR vs V, I
20
17515
180
185
190
601075
90
MH
I
T OFF
TON 85
V 40
Hold Values
Surface Plot of MH vs I, TOFF
VI. OPTIMIZATION
The method makes use of an objective function, D(X),
called the desirability function and transforms an estimated
response into a scale free value (de) called desirability. The
desirable ranges are from zero to one. The factor settings
with maximum total desirability are considered to be the
optimal parameter conditions. So, higher value of
Desirability is desired for optimal value. The simultaneous
objective function is a geometric mean of all transformed
responses, given as
De = (d1 x d2 x d3 x ..... dn)1/n
CurHigh
Low0.99164D
Optimal
d = 0.99164
Maximum
MRR
y = 1.4918
0.99164
Desirability
Composite
35.0
45.0
10.0
20.0
50.0
90.0
70.0
100.0TOFF I VTON
[100.0] [50.0] [20.0] [35.0]
Parametric Optimization of Electro Discharge Machining Process for MRR, Micro Hardness and Surface Roughness
(IJSRD/Vol. 3/Issue 03/2015/797)
All rights reserved by www.ijsrd.com 3203
CurHigh
Low1.0000D
Optimal
d = 1.0000
Minimum
SR
y = 1.3742
1.0000
Desirability
Composite
35.0
45.0
10.0
20.0
50.0
90.0
70.0
100.0TOFF I VTON
[70.0] [77.4747] [14.9495] [40.5556]
CurHigh
Low0.56410D
Optimal
d = 0.56410
Maximum
MH
y = 212.5127
0.56410
Desirability
Composite
35.0
45.0
10.0
20.0
50.0
90.0
70.0
100.0TOFF I VTON
[100.0] [50.0] [13.1313] [45.0]
VII. CONCLUSION
After completion of thesis work successfully the following
conclusion is carried out about the effect of process
parameter and the optimization of Material removal rate,
Surface roughness and Micro-hardness.
A. The effect of Process Parameter
1) For MRR,
TON : Significant, increasing MH
TOFF : Significant, decreasing MH
V: Not much Significant as TON and TOFF,
increasing MH
I: Not much Significant as TON and TOFF,
decreasing up to 40 than increasing
2) For SR,
TON : Not much Significant as TOFF, increasing
SR
TOFF : Significant, decreasing SR
V : Significant, dcreasing upto 15 than increasing
I : Not much Significant as V and TOFF,
decrasing up to 40 than increasing
3) For MH
TON : More Significant, increasing MH
TOFF : Significant, decrasing MH up to the value
of 60 than increasing
V : Significant, decreasing MH
I : Significant, increasing MH
B. Optimization of Response
1) For MRR,
The optimum value of MRR is 1.49 mm3/min calculated by
software which is confirmed by doing experimental. During
this experiment the optimum value is found 1.48 mm3/min.
For SR,
The optimum value of SR is 1.37 Ra calculated by software
which is confirmed by doing experimental. During this
experiment the optimum value is found 1.4 Ra.
2) For MH
The optimum value of SR is 212 BHN calculated by
software which is confirmed by doing experimental. During
this experiment the optimum value is found 209 BHN.
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