Experimental investigation of electrode wear and rapidly re-solidified layer thickness in T90Mn2W50Cr45/T90Mn2W50Cr45 elektrodo dilimo ir greitai kietejancio sluoksnio eksperimentinis tyrimas.
Rajendran, S. ; Marimuthu, K.
1. Introduction
This paper presents the relevance of standard Response surface
methodology (RSM) for studying the effect of Electrode Wear (EW) and
Rapidly Re-solidified Layer Thickness (RRLT) in the tool steel of
T90Mn2W50Cr45 used in electrical discharge machining process. The
process parameters Pulse on time, pulse off time, and pulse current were
altered in the experiment. The Response surface methodology (RSM) is
used for developing a mathematical model for the Electrode Wear and
Rapidly Resolidified Layer Thickness. The data's obtained for
Central Composite Rotatable Design (CCRD) has been used in mathematical
model. The end result of Analysis of Variance (ANOVA) has been applied
to verify the lack of fit and capability of the built-up models. The
predicted and experimental values were quite close, which indicates the
developed model can be effectively used to predict the Electrode Wear
and Rapidly Re-solidified Layer Thickness in the machining of tool steel
of T90Mn2W50Cr45.
Electrical discharge machining (EDM) has been established to be the
most feasible electro-thermal process along with the further
non-traditional machining processes. The requirements of the present-day
product manufacturing industries for machining any category of
electrically conductive work, irrespective of its mechanical properties
with the extent of achieving essential shape and size with superior
productivity, better surface finish characteristics, and better
dimensional accuracy features at reasonably reduced costs. The cutting
and grinding processes which are required much harder tool or abrasive
tool to machining the soft work material.
The EDM process utilizes electrical sparks or thermal energy to
erode the redundant work material and create the desired shape. These
sparks create craters and the recast layer on the surface of the EDM
work piece. The EDM has been extensively functional in modern metal
industry for producing complex cavities in moulds and dies, which are
complicated to manufacture by conventional machining [1].The variations
of geometrical tool wear characteristics and machining performance shown
that the machining parameters and dielectric flushing conditions had a
large effect on geometric tool wear [2]. Modelling and analysis of the
rapidly re-solidified layer of spheroid graphite cast iron on the EDM
process using the response surface methodology.
The conclusions reveal that the quantity and area fraction of
graphite particle are the most influential factor on the layer thickness
and ridge density [3]. The potential difference is measured at the end
of the discharge to avoid the influence of the discharge noise. The
experimental results showed that a better sensitivity and resolution can
be obtained when using the voltage peak value which appears at the end
of discharge compared with the method [4]. The metallographic of white
layer, which is upper recast layer of heat affected region, in the die
skinning EDM.
The obtained consequences indicated that the micro cracks were
created making a corner to the machined surface and the dendrites were
oblique in the route of the maximum cooling gradient [5]. Analysis the
surface integrity of steel in the EDM process rising of pulse energy in
machining determine the increase in arbitrary overlapping surface
craters, the density, and penetration depth of the cracks in the rapidly
re-solidified layer [6]. That deals the increase in pulse duration
effect results in an increase in surface roughness, depth of surface
micro cracks and depth of heat affected zones. It facilitates the
relevance of fine cutting condition beside with lower pulse duration
resulting in a better surface geometry [7].
The cooling and solidification at the top surface of the work
piece, they analyzed the pock marks, globules, cracks and micro cracks,
whose thickness and density depends on the process conditions [8].
Determine the deficiency of machining accuracy due to the deposit of
molten metal on the work piece surface in the EDM process [9]. The
combined both copper and brass electrodes in the EDM process the
electrode erosion rate and electrode wear rate with increasing pulse
current were analyzed [10]. The effects of pulse on time, pulse current,
and their interaction on the electrode wear using the using statistical
analysis, analysis of variance and regression analysis [11]. Empirical
and analytical methods for qualitative relationships between the EDM
process parameters namely, current and pulse on time and the resulting
thickness of the white layer [12].
2. Experimental procedure
The experiments were design based on five level factorial central
composite rotatable designs with full replications. These experiments
were conducted as per design matrix using EDM machine (Make: EMS 5030
Massive Engineering Private Limited, India). The dielectric fluids are
used as kerosene. The work piece material was chosen as a T90Mn2W50Cr45.
The chemical composition of the T90Mn2W50Cr45 material is given in Table
1.
The EDM machine prepared of copper electrode materials with
10x30x30 [mm.sup.3] in dimensions. The response of rapidly Re-solidified
layer thickness was measured by using a zoom microscope. The Electrode
wear was calculated by the following formula
EW = ([W.sub.i] - [W.sub.f]) /1 mg/min
where [W.sub.i] are the before machining weights of electrode
material and [W.sub.f] are the after machining weight of the electrode
material, respectively, and 't' is the machining duration
time. The electrodes materials were weigh by an electronic weighing
machine. The independently controllable process parameters were
identified; they are pulse on time ([t.sub.on]), pulse off time
([t.sub.off]) and pulse current (I) were changed during the test on the
experimental design. Trial runs were conducted by varying one of the
process parameters at a time while keeping the rest of them at constant
value. The upper limit of a factor was coded as +1.682 and its lower
limit as -1.682, the coded values of the intermediate Zlevels being
calculated from the relationship [X.sub.i] = 1.682 [2X - ([X.sub.max] +
[X.sub.min])] / ([X.sub.max] - [X.sub.min])], where [X.sub.i] is the
required coded value of a variable X and X is any value of the variable
from [X.sub.min] to [X.sub.max]; [X.sub.min] is the lower level of the
variable; [X.sub.max] is the upper level of the variable. The selected
values of the process parameters together with their units and notations
are given in Table 2. A three factor, five level central composite
experimental designs with six centre points shown in Table 3 was
selected to conduct the experiments consisting of 20 sets of coded
conditions.
The design matrix comprises a full replication factorial design
[2.sup.3] plus six star points and six centre points. All EDM variables
at the intermediate level (0) constitute the centre points while the
combinations at either it's lowest (-1.682) or highest (+1.682)
value with the other two variables at the intermediate levels
constituting the star points. Thus the 20 experimental runs allowed the
estimation of the linear, quadratic, and two-way interactive effects of
the process variables on the electrode wear and rapidly Re-solidified
layer thickness. Twenty experimental runs were conducted as per the
design matrix at random to avoid any systematic error creeping into the
system.
The Pulse on time ([t.sub.on]), pulse off time ([t.sub.off]) and
pulse current (I) was independent variables studied to predict y
responses (Electrode Wear & Rapidly Re-solidified Layer Thickness)
the independent variables and their levels for the central composite
rotatable designs used in this study are shown in Table 3. In this
table, for experimental runs 15 to 20, even through conditions remain
the same, the responses vary slightly. This is due to the effect of
unknown and unpredictable variables. To account for the impact of these
unknown factors on the response, replicated runs (15-20) were included
in the design matrix. The response function representing electrode wear
and rapidly re-solidified layer thickness can be expressed
Y = f ([X.sub.1], [X.sub.2], [X.sub.3] ...,) (1)
Y is the response e.g. electrode wear and rapidly re-solidified
layer thickness etc, [X.sub.1] is Pulse on time, ([micro]s); [X.sub.2]
is Pulse off time, ([micro]s); [X.sub.3] is Pulse current, (A).The
second-order polynomial (regression) equation used to represent the
response surface for three factors could be expressed as given below
Y = [b.sub.0] + [b.sub.1][X.sub.1] + [b.sub.2][X.sub.2] +
[b.sub.3][X.sub.3] + [b.sub.11][[X.sub.1].sup.2] +
[b.sub.22][[X.sup.2].sub.2] +
+ [b.sub.33][[X.sub.3].sup.2] + [b.sub.12][X.sub.1][X.sub.2] +
[b.sub.13][X.sub.1][X.sub.3] + [b.sub.23][X.sub.2][X.sub.3] (2)
where [b.sub.0] is the free term of the regression equation, the
coefficients [b.sub.1], [b.sub.2] and [b.sub.3] were linear conditions,
the coefficients [b.sub.11], [b.sub.22] and [b.sub.33] are the quadratic
conditions and the coefficients [b.sub.12], [b.sub.13] and [b.sub.23]
are the interaction conditions. Evaluation of coefficients of the model
values of the coefficients of the above polynomial were calculated with
the help of statistical software.
The predictable coefficients obtained above were used to create the
model for the response parameter. The adequacy of the developed model
was tested by means of using the analysis of variance technique which is
presented in Table 4 and 5. It is found that calculated F ratios were
larger than the tabulated values with the 95% of confidence level: hence
the model is considered to be adequate.
The criterion that is commonly used to illustrate the adequacy of a
fitted regression model is the coefficient of determination ([R.sup.2])
and adjusted [R.sup.2]. For the developed models, for the calculated
[R.sup.2] and adjusted [R.sup.2] values are provided in Table 4 and 5.
These values indicate that the regression model is quite adequate.
The value of the regression coefficient indicates to what extents
the factor affects the responses. Insignificant coefficients can be
eliminated to increase the accuracy of the mathematical model. To
achieve this, t- test and F tests are used. The test of significance was
prepared automatically by the statistical software, during backward
steps, a variable is uninvolved from the model and throughout forward
steps, and a variable is added automatically to the model. After
determining the significant coefficients, the final models were
constructed. The final mathematical models with parameters in coded
from, as determine by the procedure are presented below:
-electrode wear
EW = - 4.97 + 0.114 [X.sub.1] + 0.708 [X.sub.2] +
+ 0.321 [X.sub.3] - 0.000398 [[X.sub.1].sup.2] + 0.0312
[[X.sub.3].sup.2]-
- 0.00766 [X.sub.1][X.sub.2] - 0.0054 [X.sub.2][X.sub.3] (3)
-rapidly re-solidified layer thickness
RRLT = 48.7 - 8.71 [X.sub.2] - 3.24 [X.sub.3] +
+ 0.775 [[X.sub.2].sup.2] + 0.155 [[X.sub.3].sup.2+] 0.147
[X.sub.1][X.sub.3] (4)
The regression models developed were tested by drawing scatter
diagram. A typical scatter diagram for the electrode wear and rapidly
re-solidified layer thickness is shown in Fig. 1 and Fig. 2 the
experimental values and predicted values of the responses are scattered
close to the 45[degrees] line, indicating a nearly perfect fit of the
developed empirical model.
3. Results and discussions
Figs. 3 and 4 show the effect of the electrode wear and rapidly
Re-solidified layer thickness for variables pulse on-time, pulse
off-time and pulse current respectively.
[FIGURE 1 OMITTED]
[FIGURE 2 OMITTED]
Electrode wear and rapidly Re-solidified layer thickness are mainly
depending on the above said three variables. From the Figs. 3 and 4, it
is understood that pulse current is the significant factor on EW and
RRLT because of variation of EW and RRLT are significant while variation
EW and RRLT are very small for pulse off time. It is due to the fact of
increase in pulse current leads to an increase in the rate of heat
energy, which causes the electrode wear, and in the rate of melting and
evaporation.
[FIGURE 3 OMITTED]
Therefore, more heat is transferred into the work piece as the
pulse current increases, and the dielectric is continuous not capable to
clear away the molten materials, causing to construct upon the surface
of the parent material. For the duration of pulse off time, the molten
material re-solidified to form re-solidified layer and the thickness of
re-solidified layer depends on the volume of molten material. The pulse
and pulse interval time are varying linearly. The attached molten work
piece material protects the tool electrode surface not in favour of
wear.
However, as seen in Fig. 4 the RRLT is increased with pulse
duration, the combination of high pulse current and low pulse off time
leads to better tool wear.
[FIGURE 4 OMITTED]
Fig. 5 shows the SEM landscape of the machined surfaces. Analysis
of electrical discharge machining through copper electrode indicates to
the molten mass in sheet structure. Fig. 5 shows molten mass comes to
establishment surface as chunk, which gets stuck to the surface for the
basis of its moderately liquid state. The contour indicates the
inaccurate removal, which may be evidence of the way to smooth surface
has not occurred due to the larger size of droplets sticking at the
surface. The T90Mn2W50Cr45 tool steel consists of singular elements. In
order to have higher tool life, it is essential to avoid crack formation
in any event, Fig. 5 explains the SEM landscape of the machined
surfaces.
[FIGURE 5 OMITTED]
An EDM surface comprises of microscopic craters related with the
discrete discharges and is essentially of unexciting form. This
excellence morphology of the surface, which has undergone in EDM
machining, is appropriate to the infinite quantity of heat generated by
means of discharges, which cause the vaporization of the accumulation
molten metal. The crater size and for this basis surface roughness is
related to pulse energy.
The existence of T90Mn2W50Cr45 tool steel material makes it more
individual from the surfaces machined with EDM. These material particles
do not melt or evaporate throughout the discharge. Their existence
alters the gap condition in addition to the flexibility of the molten
T90Mn2W50Cr45.
Fig. 5 shows that material particles possibly will be the particles
scarlet deposited on the machined surfaces at the ending of the
discharge or these particles could be protruded on the surfaces in view
of the fact that they were not displaced at some stage in the machining
process. Figs. 6 and 7 represents the response surface for the electrode
wear and rapidly re-solidified layer thickness response obtained for the
regression model. Note that the EW and RRLT tend to significantly
increase with a combination of pulse current and pulse on time.
Electrodes wear increases with a combination of high pulse current
levels and low pulse on time. Otherwise, when a conservative electrode
is suggested a combination of high value of pulse current level must be
accompanied by low pulse-on time. In audition for low pulse current
levels, the electrode wear does not vary as much with pulse on time as
it does for high pulse current levels.
[FIGURE 6 OMITTED]
[FIGURE 7 OMITTED]
[FIGURE 8 OMITTED]
Fig. 8 and 9 shows that the deviation curve has the contour to
denote the pulse current and pulse on time interaction. In addition the
twisted plane shown in figure is representative of a typical model with
interaction. The contour plots after such useful information that is
desirable. Electrode wear and rapidly re-solidified layer thickness
response might easily be obtained by searching a direction of
improvement.
[FIGURE 9 OMITTED]
4. Conclusion
The experiments conducted using Design of experiments were applied
to develop regression models using response surface methodology to
predict the electrode wear and rapidly re-solidified layer thickness on
T90Mn2W50Cr45 materials.
In these experiments, the pulse current has established the nearly
all considerable factor performance on both electrode wear and rapidly
Re-solidified layer thickness, by the identical time of pulse off time
on both responses. The pulse interval time increases the pulse current
of T90Mn2W50Cr45 materials.
The machining parameter on the electrode wear and rapidly
re-solidified layer thickness has been evaluated using response surface
methodology. The most excellent possible machining conditions to make
illumination of the electrode wear have been considered.
The elevated discharge current, copper electrode is the evidence
for uppermost material removal rate. The scanning electrode machining of
electrical discharge machining surface indicates that molten mass has
been detached from the surface indicated as ligaments and mass and also
as chunks, which are obtained at stuck to surface, appropriate to molten
situation.
10.5755/j01.mech.18.6.3164
Received November 07, 2011 Accepted December 11, 2012
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Mr. S. Rajendran *, Dr. K. Marimuthu **
* Department of Mechanical Engineering, Kumara guru College of
Technology, Tamilnadu, India, E-mail: methermal2005@gmail.com
** Department of Mechanical Engineering, Coimbatore Institute of
Technology, Coimbatore, Tamilnadu, India, E-mail: marimuthu@cit.edu.in
Table 1
Chemical composition of test specimen (wt %)
Constituent C Mn Si S
Composition (%) 0.90 1.50 0.30 0.025
Constituent P Cr V W
Composition (%) 0.025 0.50 0.25 0.50
Table 2
Process variables and their limits
Parameters Symbol Unit Notation
Pulse on time [X.sub.1] [micro]s [t.sub.on]
Pulse off time [X.sub.2] [micro]s [t.sub.off]
Pulse current [X.sub.3] A I
Factor Levels
Parameters
-1.682 -1 0 1 1.682
Pulse on time 27 42 63 84 99
Pulse off time 2 3 4.5 6 7
Pulse current 3 5 9 12 15
Table 3
Design matrix with its experimental results and predicted model value
Matrix design EW (mg/min)
[t.sub.on] [t.sub.off]
S.No. ([micro]s) ([micro]s) I (A) Observed Predicted
1 1 -1 1 8.24 8.02
2 1 1 -1 2.4 2.35
3 1 1 1 7.25 7.04
4 -1 -1 -1 1.96 1.87
5 -1 1 1 7.42 7.18
6 -1 -1 1 7.45 7.2
7 1 -1 -1 3.28 3.22
8 -1 -1 2.05 1.97
9 0 0 1.682 10.35 10.7
10 0 1.682 0 4.24 4.49
11 -1.682 0 0 3.85 4.1
12 0 0 -1.682 1.65 1.74
13 0 -1.682 0 4.98 5.25
14 1.682 0 0 4.82 5.06
15 0 0 0 5.08 5.18
16 0 0 0 5.14 5.24
17 0 0 0 5.17 5.26
18 0 0 0 5.20 5.29
19 0 0 0 5.22 5.16
20 0 0 0 5.11 5.19
RRLT ([micro]s)
S.No. Observed Predicted
1 38.9 39.5
2 16.62 16.35
3 38.5 39.5
4 14 14.75
5 30.00 30.45
6 30.5 31.45
7 16.2 16.4
8 15.75 16.5
9 48.62 48.5
10 23.25 24.7
11 19.65 19.8
12 13.62 13.65
13 24.75 25.5
14 26.72 27.25
15 21.45 21.52
16 21.56 21.59
17 21.48 21.44
18 21.58 21.53
19 21.61 21.56
20 21.52 21.54
Table 4
ANOVA table for testing electrode wear
Source DF SS MS F P
Model 9 96.275 10.697 174.25 0.000
[X.sub.1]([micro]s) 1 1.126 1.126 18.34 0.001 *
[X.sub.2]([micro]s) 1 0.683 0.683 11.12 0.002 *
[X.sub.3](A) 1 90.69 90.69 1477.03 0.004 *
[X.sub.1.sup.2] 1 0.679 0.679 11.05 0.02 *
[X.sub.2.sup.2] 1 0.219 0.219 3.56 0.244
[X.sub.3.sup.2] 1 2.268 2.268 36.94 0.000 *
[X.sub.1][X.sub.2] 1 0.466 0.466 7.589 0.02 *
[X.sub.1][X.sub.3] 1 0.137 0.137 2.231 0.166
[X.sub.2][X.sub.3] 1 0.006 0.006 0.097 0.003 *
Residual error 10 0.614 0.0614 - -
Pure error 5 0 0 - -
Total 19 96.889 - - -
[R.sup.2] = 0.994; [R.sup.2] (Adj) = 0.988; * Significant
DF - degree of freedom; SS - sum of squares; MS - mean sum of squares
F - calculated 'F' ratio; P- probability.
Table 5
ANOVA table for testing rapidly re-solidified layer thickness
Source DF SS MS F P
Model 9 1616.57 179.62 40.94 0.000
[X.sub.1] ([micro]s) 1 131.16 131.16 29.87 0.284
[X.sub.2] ([micro]s) 1 0.35 0.35 0.078 0.015 *
[X.sub.3] (A) 1 1310.17 1310.17 298.44 0.021 *
[X.sub.1.sup.2] 1 2.54 2.54 0.578 0.934
[X.sub.2.sup.2] 1 33.11 33.11 7.54 0.011 *
[X.sub.3.sup.2] 1 56.12 56.12 12.78 0.005 *
[X.sub.1][X.sub.2] 1 0.25 0.25 0.056 0.815
[X.sub.1][X.sub.3] 1 78.11 78.11 17.79 0.002 *
[X.sub.2][X.sub.3] 1 4.78 4.78 1.088 0.321
Residual error 10 43.87 43.87 4.387 -
Pure error 5 0 0 0 -
Total 19 1660.45 - - -
[R.sup.2] = 0.974; [R.sup.2] (Adj) = 0.950; * significant
DF - degree of freedom; SS - sum of squares; MS - mean sum of squares
F - calculated 'F' ratio; P- probability.
