Optimization of EDM process parameters for machining SS310

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Optimization of EDM process parameters for machining SS310
A. Chandrakanth1, Dr. Md. Aleem pasha2, T.N. Aditya3 K. Gurubrahmam4
1,3,4 Assistant Professor, Dept. of Mech. Engg., CBIT, Hyderabad, Telangana, India
2Associate Professor, Dept. of Mech. Engg., CBIT, Hyderabad, Telangana, India
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Abstract - The Electrical discharge machining is a widely
used Precision manufacturing process. The EDM process
involves a controlled erosion of electrically conductive
materials by initiation of repetitive spark discharge between
electrode tool and work piece, separated by a small gap of
called as spark gap. In the current work, optimization of
various process parameters to increase Materialremovalrate
and to decrease tool wear rateisdoneusingTaguchi’smethod.
Coppers is used as tool materials and SS310 is used as work
piece material. The process parameters selectedaredischarge
current and spark gap. The output characteristics measured
are Material Removal rate and tool wear rate. A full factorial
design of experiment is used to find the influence of process
parameters on Metal Removal Rate and tool wear rate. The
main effects and interaction effects are plotted. From the
experiments it was found that discharge current is the most
influencing factors on MRR and TWR using copper as the
electrode.
Key Words: EDM: Electron Discharge Machining; MRR:
Material Removal Rate; SS: Stainless steel; TWR: Tool
Wear Rate
1. INTRODUCTION
Electrical discharge machining (EDM) has long been the
answer for high accuracy, demanding machining
applications where conventional metal removal is difficultor
impossible. Known by many other names, including spark
machining, arc machining and (inaccurately) burning, the
EDM process is conceptually very simple: an electrical
current pass between an electrode and a work piece which
are separated by a dielectric liquid. The dielectric fluid acts
as an electrical insulator unless enough voltage is applied to
bring it to its ionization point, when it becomes an electrical
conductor. The resulting spark discharge erodes the work
piece to form a desired final shape.
EDM has the ability to machine complex shapes in very hard
metals. The most common use of EDM is in machining dies,
tools and moulds made of hardened steel, tungsten carbide,
high-speed steel and other work piece materials that are
difficult to machine by "traditional" methods. Because of
technical advances in electrode wear, accuracies and speed,
EDM has replaced manyofthetraditional processes.Another
factor contributing to the growing use of EDM is the
expansion of the work envelope, particularly when it comes
to heights and tapers.
1.1 EDM MACHINE
The machining is carried out on ElectronicaC-425 EDM
machine. The machines setupand its specifications are given
below.
Table -1: Specifications of the EDM machine
Work tank 600x400x280mm
Work table size 400x250mm
Table traverse 250x170mm Max
Max work piece weight
100kg
height
160m
Z axis traverse
150mm
Least counter of vernier
0.005mm
Shut height
260mm
Throat
320mm
No. of power settings
99x9
Power supply
3 phase,415v AC. 50Hz
Machine dimensions
1130x1040x1800mm
No of T slots
3
Max working current
22Amps
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 09 Issue: 06 | Jun 2022 www.irjet.net p-ISSN: 2395-0072
Fig -1: ElectronicaC-425 EDM machine

2. METHODOLOGY
In the present work, optimization of theinputparametersfor
various output parameters are done using Design of
Experiments. Two input parameters at three levels are
considered for the experiment. The input process
parameters and their levels are shown in the table below.
Table -2: Selected Input parameters with levels
Control parameters Level1 Level 2 Level 3
Discharge current
(Amp)
4 8 12
Spark gap (mm) 0.05 0.1 0.15
The experiments are conducted using full factorialdesign
by selecting L9 orthogonal array. The experiments are
designed using Taguchi’s method. The experiments were
conducted on diesink electricdischargemachineasshownin
Fig.1 which consist a work table, a servocontrolsystemanda
dielectric supplysystem.Themachinehascurrentsettingsup
to 22A. The experiments are conducted on AISI 310 material
with dimensions are 100 mm x 25 mm x 5 mm. Work piece
material properties are: Hardness (HRC)= 43-45, density
(g/cm3)= 8.16, Ultimate tensile strength (Kg/mm2) =85,
Elongation % =3. The tool material used is copper with
density 8.96 gm/cm3and thermal conductivity of 386w/mk
and the machining is done with straight polarity. Spo oil is
used as the dielectric fluid and the experiments were
performed for a particular set of input parameters. The
number of experiments andinputlevelsaredecidedbasedon
the design of experiments andtheinputparametersandtheir
levels. The MRR and TWR arecalculatedusingdigitalbalance
of accuracy 1mg and the machining time is using digital
watch of accuracy 1 microsecond. The weight of the
workpiece and tool before machining is recorded using the
digital balance. The total machining time is also recorded
using a digital watch. The input parameters and their levels
are shown in Table-3.
Table -3: Process parameters selected for experimentation
Experiment
No.
Discharge current
(Amp)
Spark gap (mm)
1 4 0.05
2 4 0.10
3 4 0.15
4 8 0.05
5 8 0.10
6 8 0.15
7 12 0.05
8 12 0.10
9 12 0.15
The machining samples after the experimentation are
marked for various process parameters. The samples after
the machining process are shown in the fig.2
Fig -2: Samples after the experimentation
3. RESULTS AND DISCUSIONS
The output values are calculated bymeasuringthe weightof
the workpiece and tool after the machining process. The
difference in the weight of the samples is used to calculate
MRR and TWR. The calculated output parametersareshown
in the table-4 below.
Table -4: output responses recorded after experimentation
Experi
ment
No.
Discharg
e current
(Amp)
Spark
gap
(mm)
MRR
mm3/min
TWR
mm3/min
1 4 0.05 9.677 4.650
2 4 0.10 10.193 5.580
3 4 0.15 12.534 5.391
4 8 0.05 4.313 2.391
5 8 0.10 5.298 3.597
6 8 0.15 7.373 3.256
7 12 0.05 3.124 1.584
8 12 0.10 1.801 1.291
9 12 0.15 1.481 0.859

Fig -3: Main effect for means (MRR)
Fig -4: Interaction plot for means (MRR)
Fig -5: main effect plot for S/N ratio (MRR)
Fig -6: Interaction effect plot for S/N ratio (MRR)
Table-5: Response Table of Means for MRR
Level Amp mm
1 10.801 5.705
2 5.661 5.764
3 2.135 7.129
Delta 8.666 1.425
Rank 1 2
Table-6: Response Table for Signal to Noise Ratios Larger
is better for MRR
Level Amp mm
1 20.614 14.102
2 14.844 13.253
3 6.139 14.242
Delta 14.476 0.989
Rank 1 2
Table-7: ANOVA results for MRR
Source DF SS MS F P
Amp 2 113.9518 56.9759 30.983 0.001
mm 6 11.0335 1.8389
Total 8 124.9854
Table-8: Variance Components
Source Var Comp.
% of
Total StDev
Amp 18.379 90.90 4.287
mm 1.839 9.10 1.356
Total 20.218 4.496
Table-9: Expected Mean Squares
1 Amp 1.00(2) + 3.00(1)
2 mm 1.00(2)

The following figures show the main effect and interaction
effect plots for Tool wear rate
Fig -7: Main effect for means (TWR)
Fig -8: Interaction plot for means (TWR)
Fig -9: Main effect plot for S/N ratio (TWR)
Fig -10: Interaction effect plot for S/N ratio (TWR)
Table-10: Response Table of Means for TWR
Level Amp mm
1 5.207 2.875
2 3.081 3.489
3 1.245 3.169
Delta 3.962 0.614
Rank 1 2
Table-11: Response Table for Signal to Noise Ratios
Smaller is better for TWR
Level Amp mm
1 -14.305 -8.305
2 -9.648 -9.423
3 -1.631 -7.856
Delta 12.674 1.568
Rank 1 2
Table-12: ANOVA results for MRR
Source DF SS MS F P
Amp 2 23.5919 11.7959 46.494 0.000
mm 6 1.5222 0.2537
Total 8 25.1141
Table-13: Variance Components
Source Var Comp.
% of
Total StDev
Amp 3.847 93.81 1.961
mm 0.254 6.19 0.504
Total 4.101 2.025
Table-14: Expected Mean Squares
1 Amp 1.00(2) + 3.00(1)
2 mm 1.00(2)

4. CONCLUSION
From the experimental results, the main effect plots and
interaction plots are generatedforMaterial removal rate and
Tool wear rate. The S/N ratio is also calculated by
considering maximum is better for Material removal rate
and minimum is better for Tool wear rate. From Table-6 it
can be concluded that discharge current is the most
influential factor for Material removal rate and hence more
discharge current is recommended. From Table-11,itcanbe
concluded that discharge current is most influential
parameter for Tool wear rate. The experimental
investigations can be carried out with more numberofinput
process parameters.
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