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http://jcm.sagepub.com/Materials
Journal of Composite
http://jcm.sagepub.com/content/45/2/133The online version of this article can be found at:
DOI: 10.1177/0021998310371543
2011 45: 133 originally published online 27 October 2010Journal of Composite MaterialsHarmesh Kumar and J. Paulo Davim
Mixed Electric Discharge MachiningRole of Powder in the Machining of Al-10%Sicp Metal Matrix Composites by Powder
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Role of Powder in the Machiningof Al10%Sicp Metal Matrix Composites
by Powder Mixed ElectricDischarge Machining
HARMESH KUMAR1,* AND J. PAULO DAVIM2
1Department of Mechanical Engineering, UIET, Panjab University,
Chandigarh 1600 14, India2Department of Mechanical Engineering, University of Aveiro, Campus Santiago,
AVEIRO, Portugal
ABSTRACT: This article reports the results of an experimental study conducted withthe objective to understand the mechanism of material removal (role of siliconpowder) in powder mixed electric discharge machining (PMEDM) while machiningthe Al10%SiCP metal matrix composites. PMEDM is relatively a new developmentin the direction of enhancement of process capabilities of EDM. A new experimentalset-up has been developed in the laboratory for experimentation. This research pointsout how the suspended powder helps in improving the performance of EDM. Further,
the effect of the suspended powder and other selected parameters on process perfor-mance (machining rate (MR) and surface roughness (SR)) and subsequent optimalsettings of the variables have been obtained using Taguchi method. The obtainedexperimental results indicate significantly improved performance of PMEDM overEDM. The appropriate addition of silicon powder into the dielectric fluid of EDMincreases the MR and decreases the SR. The experimental results further indicate thatthe powder concentration, peak current, and pulse duration are the significant vari-ables, while the supply voltage is an insignificant variable. The results were verified byconducting confirmation experiments with optimal process conditions.
KEY WORDS: powder mixed EDM, metal matrix composites, machining rate,surface roughness, process optimization.
INTRODUCTION
AMONG ALL THE nonconventional machining methods, electric discharge machining
(EDM) is one of the most popular machining methods for the manufacturing of press
tools and dies. This process enables machining of any material which is electrically
*Author to whom correspondence should be addressed. E-mail: shaarut@yahoo.comFigures 15 appear in color online: http://jcm.sagepub.com
Journal of COMPOSITE MATERIALS, Vol. 45, No. 2/2011 133
0021-9983/11/02 013319 $10.00/0 DOI: 10.1177/0021998310371543 The Author(s), 2011. Reprints and permissions:http://www.sagepub.co.uk/journalsPermissions.nav
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conductive, irrespective of its hardness, shape, and strength [1]. Even highly delicate sec-
tions and weak materials can be machined without any fear of distortion because there is
no direct contact between the tool and the workpiece. Metal matrix composites (MMCs)
are such materials, which are manufactured by suspending the reinforcing agents (in the
form of fibers, particulates, whiskers, etc.) into the matrix of the base material [2]. The
machining of such materials required special machining processes, tool design, technology,
and skill due to the addition of reinforcing materials, which are normally harder and stiffer
than matrix. Therefore nonconventional techniques are generally recommended for
machining of MMCs. EDM is one of the most extensively used nonconventional material
removal processes for such kind of materials. However, low efficiency and rough surface
finish restrict its further applications.
To solve this problem, a relatively new advancement in the direction of process capa-
bilities is the addition of powder into the dielectric fluid of EDM [35]. This new hybrid
material removal process is called powder mixed EDM (PMEDM). The results show that
the PMEDM can distinctly improve the surface finish and surface quality to obtain near
mirror-like surfaces at a relatively high machining rate (MR) [5
7]. Moreover, the surfaceproduced by PMEDM has a high resistance to corrosion and abrasion [8,9]. In this pro-
cess, a suitable material in the form of fine powder is mixed into the dielectric fluid of
EDM. The added powder improves the breakdown characteristics of the dielectric fluid,
that is, the insulating strength of the dielectric fluid decreases and consequently, the spark
gap distance between the electrode and workpiece increases [3,4,7]. The enlarged spark gap
distance makes the flushing of debris uniform. As a result, the process becomes more
stable, thereby improving MR and surface finish.
Many researchers [3,4,1017] have observed the behavior of various powders when
added to the working fluid (dielectric) of EDM. Despite the promising results, the key
issue of the machining mechanism of PMEDM is not clearly understood. Erden and Bilgin[10] reported the experimental and theoretical investigations to determine the effect of
powders (copper, aluminum, iron, and carbon) in the dielectric fluid of EDM. It was
found that the MR increased with the concentration of the powder. Mohri et al. [6] studied
the effects of silicon powder addition on MR and surface finish in EDM. Fine and
corrosion-resistant surfaces having roughness of the order of 2 mm were produced.
However, this performance can only be achieved at controlled machining conditions
(even distribution of powders into dielectric, short discharge time, etc.). It was further
reported that under specific working conditions, aluminum powders exhibit a greater
improvement in surface finish than silicon powder [18]. The use of silicon powder was
also reported in references [8,19].
Near-mirror finish can be achieved by mixing different powders (silicon, graphite,
molybdenum, aluminum, and silicon carbide) into the working fluid of EDM [7]. The
presence of powder increases the gap distance as compared to traditional EDM by at
least a factor of 2. The enlarged and widened discharge channel lowers the breakdown
strength of the dielectric fluid and reduces the electrical density on the machining spot, and
thus generates shallow craters [8]. Ming and He (1995) observed that a bridging effect is
created with the addition of powder, which facilitates the dispersion of discharge into
several increments. As a result, several discharge trajectories are formed within a single
input impulse and several discharge spots are created, and hence the MR and the surface
finish improve [15]. The metal removal rate and surface finish are improved under limited
pulse duration. Modification of the surface of the shell mold, dies, and tools is also pos-sible by PMEDM [9,20]. The wear and corrosion resistance of the work surfaces can be
134 H. KUMAR AND J. P. DAVIM
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improved by depositing a hard layer on its outer surface. Tzeng and Chen [4] optimized the
high-speed EDM by suspending the chromium powder into the dielectric fluid. The latest
and updated literature review on PMEDM is available in Kansal et al. [21]. The improve-
ment in the surface integrity of electrochemical discharge machining using conductive
particles in the electrolyte was proposed by Han et al. [22]. They reported that by sus-
pending the graphite powder into the dielectric fluid of EDM, the discharging pattern
modifies, and as a result, the surface quality improves. Pecas and Henriques [23] discussed
the effect of electrode area on surface roughness (SR) and topography using powder-mixed
electrolyte.
A study reported by Kansal et al. [24] shows that the introduction of suitable powder
into the dielectric fluid of EDM improves the temperature distribution in the workpiece
material and consequently, lowers the magnitude of the temperature stresses induced in the
workpiece material. Further, the induced stresses are uniformly distributed in the work
material. Prihandana et al. (2009) studied the effect of micro-powder suspension and
ultrasonic vibration of dielectric fluid in micro-EDM process. The results showed that
by introducing MoS2 micro-powder in the dielectric fluid and using ultrasonic vibrationssignificantly increases the material removal rate and improves surface quality [25].
The machining of composites by conventional methods is reported by many researchers.
Gordon and Hillery [26] presented a review of the cutting of composite materials. Further,
a literature review on the drilling of fiber-reinforced plastics was arranged by Abrao et al.
[27]. Palanikumar et al. [28] presented the statistical analysis of delamination in drilling
glass fiber reinforced plastics. They analyzed the effect of feed, speed, rotational speed, and
drill geometry on the resulting delamination factor. Gaitonde et al. [29] presented the study
in which the relationship between cutting conditions and machinability characteristics
during the turning of MMC was established. They investigated the effect of cutting
speed and feed rate on machining force, cutting power, and specific cutting force usingresponse surface methodology (RSM).
Few researchers have reported the machining of MMCs by EDM in literature. The
Al2O3 particulate-reinforced aluminum-based composites are reported to be machined
by EDM [30]. Later, they studied the machining characteristics of Al2O3/6061Al compos-
ites using rotary EDM with a disk-like electrode [31]. The modeling of die sinking EDM of
ceramic material such as silionized silicon carbide (SiSiC) was done by [32]. The EDM of
carbon fiber-reinforced carbon composite material was investigated by Guu et al. [33]. The
reported experimental results indicate the extent of delamination, thickness of the recast
layer, and SR. They showed that EDM produces excellent surface characteristics and high-
quality holes in composites under low discharge energy conditions. However, no research
study has been reported for the machining of MMCs by PMEDM.
This research is part of the larger research project which aims the development of new
and viable PMEDM technology for the machining of MMCs. The aluminum-based MMC
is manufactured by suspending the reinforced SiC in aluminum matrix. A detailed analysis
of the role of suspended powder into the dielectric fluid of EDM on machining of
Al2O3SiC is the first part of this research, while the second part presents the influence
of various processing parameters, including the effects of silicon powder particles mixed
into the dielectric fluid on the performance of EDM. The performance of EDM is mea-
sured in terms of MR and SR. The experiments are planned and results are analyzed using
one of the most powerful and reliable design of experiments techniques called Taguchi
philosophy. The proposed set of process parameters is also presented in order to optimizethe MR and SR.
Machining of Al10%Sicp Metal Matrix Composites 135
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PROPOSED MACHINING MECHANISM OF PMEDM
A schematic diagram of the proposed mechanism of material removal in PMEDM is
illustrated in Figure 1(a) and (b).
The machining mechanism showing the role of powder mixed into the dielectric fluid is
proposed after conducting a series of extensive experimental studies. In this process, a
suitable material in the powder form is mixed into the dielectric fluid of EDM. When a
voltage of 80320 V is applied to both the electrodes, an electric field in the range
105107 V/m is created. The spark gap is filled up with additive particles and the gap
distance between the tool and the workpiece increases from 25 to 50 mm to many times
(Figure 1(a)). The powder particles get energized and behave in a zigzag fashion. The
grains come close to each other under the sparking area and gather in clusters.
Under the influence of electric forces, the powder particles arrange themselves in the
form of chains at different places under the sparking area (Figure 1(b)). The chain forma-
tion helps in bridging the gap between both the electrodes. Due to bridging effect, the gap
voltage and insulating strength of the dielectric fluid decreases. An easy short circuit takes
place, which causes early explosion in the gap. As a result, the series discharge starts
under the electrode area. Due to increase in frequency of discharging, faster sparking
(Workpiece)
()
(+)
(Tool)
Dischargecolumn
Crater
Bridging
Powder mixeddielectric
Discharge gap
(a)
Work piece ()
Tool (+)Powderparticles
(b)
Figure 1. Schematic representation of mechanism of machining in PMEDM.
Notes: (a) It is expected that the insulating strength of the dielectric fluid decreases as powder is suspended
into it. The spark gap distance is increased by manifold than normal EDM. It is proposed that the increase in
gap might have caused wider discharge passages.
(b) In wider and enlarged plasma channel, the suspended powder particles share and redistribute the impactforce. As a result, shallow, uniform, and flat craters are formed on the workpiece surface.
136 H. KUMAR AND J. P. DAVIM
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within a discharge takes place which causes faster erosion from the workpiece surface.
At the same time, the added powder modifies the plasma channel. The plasma channel
becomes enlarged and widened. The electric density decreases; hence, sparking is uni-
formly distributed among the powder particles. As a result, even and more uniform dis-
tribution of the discharge takes place, which causes uniform erosion (shallow craters) on
the workpiece. This results in improvement in surface finish.
The improvement in surface topography can be visualized from the SEM photographs
taken from the EDM and PMEDM surfaces as shown in Figure 2 [24].
EXPERIMENTAL DETAILS
PMEDM Set-up
A die sinking EDM machine, model Mini G-30 manufactured by ToolCraft, India,
was used for experimentation. It is energized by A15 type, 25 A working current pulse
generator and associated controller to produce rectangular-shaped current pulses for dis-
charging purpose.
The existing dielectric circulation system of ToolCraft EDM machine needs about 60 L
of dielectric fluid (kerosene) in circulation. The mixing of powder with the whole of dielec-
tric fluid was avoided. This is because of the fact that for experimentation, different levels
of concentration of powders were to be mixed into the dielectric. Moreover, there was
difficulty in changing the dielectric fluid and removing all the powder particles from the
circulating system. Further, it was also not possible to circulate the powder-mixed dielec-
tric through the existing circulation system, because the filter might choke due to the
presence of powder particles and debris. Therefore, a need was felt to develop a newpowder-mixed dielectric circulation system for the experimentation. To fulfill this require-
ment, a new experimental set-up for PMEDM was designed and developed in the labo-
ratory. The schematic of kinematic configuration of the PMEDM set-up is shown
in Figure 3.
The new PMEDM system was designed for 7 L of dielectric fluid for each experiment.
The line diagram of the powder-mixed dielectric circulation system for PMEDM is shown
in Figure 4.
Figure 2. SEM photograph of workpiece surface machined by EDM and PMEDM.
Machining of Al10%Sicp Metal Matrix Composites 137
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It consists of a transparent bath-like container, called machining tank (MT). It was
placed in the work tank of EDM and the machining was performed in this container.
To hold the workpiece, a workpiece fixture assembly (W) was placed in it. The MT
was filled up with the dielectric fluid (kerosene oil). To avoid particle settling, a stirring
system (S) was incorporated. A small dielectric circulation pump (P) was installed there
for proper circulation of the powder-mixed dielectric fluid into the discharge gap. The
pump and the stirrer assembly was placed in the same tank in which machining was
performed. The distance between the powder-mixed dielectric suction point and the
nozzle outlet is made as short as possible (10 inches) in order to ensure the completesuspension of powder in the discharge gap. Magnetic forces were used to separate the
1 Magnets; 2 Circulation pump; 3 Work tank 4 Nozzle;
5 Machining tank; 6 Workpiece; 7 Electrode; 8 Stirrer;
9 Oscilloscope; 10 Recorder; 11 ZNC generator; 12 Power supply
10
9
11
12
5
7
8
6
4
23
1
Figure 3. Schematic of PMEDM experimental set-up.
F
ST
V1
V2
V3
CP
Worktank
MT
PW
N
E
Figure 4. A block diagram of dielectric circuit of PMEDM set-up.
138 H. KUMAR AND J. P. DAVIM
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debris from the dielectric fluid. For this purpose, two permanent magnets (M) were placed
at the bottom of MT (Figure 3).
The line diagram of the powder-mixed dielectric circulation system for PMEDM is
shown in Figure 4. The pure kerosene oil was also allowed to flow continuously through
the existing (conventional) dielectric flow circuit to maintain the circuitry (Figure 4). The
conventional dielectric circuit involves the flow of dielectric from storage tank (ST) to
work tank via centrifugal pump (CP) and valve (V3). From work tank, the dielectric fluid
was sent back to ST via valves (V1 and V2) and filter (F). The pump (P) in the MT
delivered the powder-mixed dielectric fluid into the discharge gap through the ejector
nozzle (N). The flow of pure kerosene through the conventional dielectric system andpowder-mixed kerosene through the newly developed circulation system was continuous
till the end of the machining process. A close view of the machining area is shown in
Figure 5.
Powder and Electrode Materials
Silicon powder was suspended into the commercially available kerosene oil. The size of
the powder particles was in the range of order 2030 mm.
Each trial run was performed for a duration of 30 min. The experiments have been
performed with positive polarity as recommended in Zhao et al. [3].
In this study, Al
10%SiCP as cast MMC was selected as the work material. The
Al10%SiCP MMC is manufactured by stir casting process. The chemical composition
of the workpiece material is given in Table 1.
The material had reinforcement of 10% SiC particles (by volume) with an average
particle size of 25mm. The mechanical and physical properties of Al10%SiCP are pre-
sented in Table 2. Copper electrode with a diameter of 5 mm has been used to machine the
Al10%SiCP MMC.
Process Variables of PMEDM
The process parameters of PMEDM are shown in the Ishikawa cause
effect diagram(Figure 6).
Toolelectrode
Stirrer
Powder-suspendedkerosene
Purekerosene
Workpiece
Magnets
Circulating pump (P)
C
R
DCpowersupply
Figure 5. Close view of the machining area for PMEDM.
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The following process variables may affect the performance of the PMEDM process.
1. Powder concentration,
2. Peak current,
3. Pulse duration, and
4. Supply voltage.
The range of the selected process variables was decided by conducting the experiments
with one-variable-at-a-time approach. The process variables, their designated symbols,
and range are given in Table 3. The response parameters in this study were MR and
SR. In each test, the MR was calculated by the weight-loss method. The SR was measured
in terms of arithmetic mean roughness of the evaluated roughness profile (Ra in mm) using
a Surfcoder SE1200 surface testing analyzer.
Taguchi Method
The Taguchi experimental design is used to get information such as main effects and
interaction effect of design parameters from minimum number of experiments. The objec-
tive of Taguchi method for parameter design is to find out the best combination of designparameters with minimum variation. The Taguchi method uses signal-to-noise (S/N) ratio
Nonelectrical
parameters
Flushing
Gain
Lift
PMEDM process
Performance (MR,SR, TWR)
Electrical
parameters
Pulse on time
Supply voltage
Peak current
Pulse off time
Electrode
parameters
Material
Size
Powderparameters
Powder concentration
Powder type
Shape & size
Figure 6. The Ishikawa causeeffect diagram for PMEDM.
Table 2. Physical and mechanical properties of Al
10%SiCP MMC.
Ultimate tensile
strength (MPa)
Elastic modulus
(GPa)
Thermal conductivity
(cal/cm s K)
Coefficient of thermal
expansion (106/K)
Density
(kg/m3)
Hardness
(HRB)
411 94.5 0.45 18.7 2210 77
Table 1. Chemical analysis of Al10%SiCP MMC.
Si Mg Cu Zn Ti Balance
7% 0.3% 0.4% 0.1% 0.1% Aluminum
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to quantify the variation in data. There are three categories of S/N ratios depending on the
types of characteristics like, lower is best (LB), higher is best (HB), and nominal is best
(NB). In this work, LB and HB, S/N ratio has been used [34].
Taguchi recommended various standardized orthogonal arrays (OAs) such as L4, L8, L9,
L16, L18, L25, etc. Depending upon the number and type of parameters to be studied, a
suitable OA is chosen. In this work, there were a total of four parameters, each at three
levels. The choice of L9 (34) OA is suitable for this work. L9 (3
4) OA was selected to assign
various columns. The experiments were conducted according to the trial conditions
specified in L9 (34) OA (Table 4).
The observed and S/N values of MR and SR are set to higher the best and lower the
best, respectively [35].
RESULTS AND DISCUSSION
The data collected from the experiments (performed as per Taguchi L9 OA) is given inTable 5 and was transformed into S/N ratio of the response parameters by using
Table 4. The L9 (34) orthogonal array (parameters assigned) with response.
Experiment number Run order
Process parameters Response
1 2 3 4
R1 R2 R3A B C D
1 2 1 1 1 1 Y11 Y12 Y132 8 2 2 2 2
3 5 3 3 3 3
4 9 1 2 2 3
5 6 2 3 3 1
6 3 3 1 1 2
7 1 1 3 3 2
8 7 2 1 1 3 9 4 3 2 2 1 Y91 Y92 Y93
The 1s, 2s, and 3s represent levels 1, 2, and 3 of the parameters, respectively which appear at the top of the column. A,concentration; B, peak current; C, pulse duration; D, duty cycle. R1, R2, and R3 represent repetitions and Yij the measuredvalues of the response characteristic.
Table 3. Process variables and their range.
Symbol Process variable Units
Levels
L1 L2 L3
A Silicon powder concentration g/L 0 2 4B Peak current ampere 3 6 9
C Pulse on time ms 50 100 150
D Supply voltage V 50 70 90
aL represents levels.Constant parameters: Type of powder, Si (size 2030mm); discharge voltage, 35 V; gain, 0.86 mm/s; electrode lift time,1.36 s; machining time, 30 min; flushing, nozzle; polarity, ve; workpiece material, Al10%SiCP MMC, and electrode (tool)material, pure red copper.Response characteristics: 1. MR and 2. SR.
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Software Minitab. The mean data and their corresponding S/N ratio values for each trial
for both MR and SR are further analyzed and studied to draw conclusions.
Machining Rate
The variation of mean values of MR at different levels of input process parameters is
given in Tables 6 and 7, respectively. The response curves (Figure 7) for the individual
effect of the four process parameters on the average value and S/N ratio for MR have been
plotted using these data.
From the trend of variation of MR at different levels of the process parameters, it can be
noted that when Si powder is suspended into the dielectric fluid of EDM, the MR
improves. Level 1 indicates the case of simple EDM, while levels 2 and 3 represent
PMEDM. The reason for enhancement of MR is mainly that the conductive powder
particles when added into the dielectric fluid of EDM lower the breakdown strength of
the dielectric fluid. The powder particles try to bridge the discharge gap between both the
electrodes. This facilitates the dispersion of discharge into several increments (sparkingfrequency increases) and hence, enhances the MR. Another observation from this
Table 5. Experimental results of various response characteristics.
Experiment
number
Run
order
Observed values
MR (mm3/min) SR (km)
R1 R2 R3 Mean S/N ratio R1 R2 R3 Mean S/N ratio
1 2 0.20 0.21 0.19 0.20 13.97 0.68 0.94 0.81 0.81 1.83
2 8 0.57 0.41 0.49 0.49 6.19 1.38 1.30 1.52 1.40 2.92
3 5 1.00 0.98 0.87 0.95 0.44 1.76 1.70 1.79 1.75 4.86
4 9 0.57 0.65 0.46 0.56 5.03 0.70 0.72 0.70 0.71 2.97
5 6 0.82 0.81 0.95 0.86 1.31 1.44 1.50 1.32 1.42 3.04
6 3 1.79 1.80 2.02 1.87 5.43 1.80 1.70 1.78 1.76 4.91
7 1 0.82 0.75 0.89 0.82 1.72 0.48 0.48 0.63 0.53 5.51
8 7 1.21 1.22 1.20 1.21 1.65 0.99 1.05 1.17 1.07 0.58
9 4 2.93 2.99 2.90 2.94 9.36 1.05 1.14 1.08 1.09 0.74TMR overall mean of MR1.10 TSR overall mean of SR1.17
Table 6. Average and main effects raw data (MR).
Process parameter
Average values, MR (mm3/min) Main effects, MR (mm3/min)
L1 L2 L3 L2L1 L3L2
Concentration (A) 0.54 1.09 1.65 0.55 0.54
Peak current (B) 0.52 0.85 1.92 0.33 0.07
Pulse on time (C) 1.09 1.33 0.87 0.24 0.46
Supply voltage (D) 1.33 0.90 0.42 0.43 0.48
L1, L2, and L3 represent average values of raw data of corresponding parameters at levels 1, 2, and 3, respectively. L2L1 isthe average main effect when the corresponding parameter changes from level 1 to level 2. L3L2 is the average main effectwhen the corresponding parameter changes from level 2 to level 3.
142 H. KUMAR AND J. P. DAVIM
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experiment is that the increase in peak current improves the MR. This may be due to its
dominant control over the input energy. It is representative of the energy per pulse
expended in the spark gap region. It thus controls the rate of erosion of the material.
This result is in line with the findings of [3].
The pulse duration is another factor that shows the variation in mean and S/N ratio.
The MR increases with an increase in pulse duration and reaches an optimum value at
100 ms; however, further increase in pulse duration decreases the MR. This is due to the
fact that the short pulse duration may cause less vaporization on the surface of the work-
piece, whereas the long pulse duration may cause an expansion of the plasma channel,
thereby decreasing the energy density in the machining process; therefore, sufficient pulse
duration generates high MR. It is further noted from the response curves that the supplyvoltage does not produce a pronounced effect on MR.
0
1
2
50
Supply voltage (V)
2.5
1.5
0.5
0.5
S/N
ratio
(dB)
0
1
2
50
Pulse duration (s)
3
2
1
0
S/N
ratio
(dB)
0
1
2
3
3
Peak current (A)
8
6
4
2
0
2
4
6
S/Nra
tio(dB)
0
1
2
0
Concentration (g/L)
MR
(m
m3/min)
MR(m
m3/min)
MR
(mm3
/min)
MR
(mm3
/min)
8
6
4
2
0
2
4
S/Nra
tio(dB)
2 4 6 9
100 150 70 90
Figure 7. Effect of process parameters on MR and S/N ratio. (#) Mean MRR; (m) S/N ratio.
Table 7. Average and main effects S/N data (MR).
Process parameter
S/N average values (dB) Main effects (dB)
L1 L2 L3 L2L1 L3L2
Concentration (A) 6.8 0.30 3.09 6.5 3.39Peak current (B) 6.91 1.95 4.78 4.96 6.73
Pulse on time (C) 2.29 0.62 1.15 1.67 1.77
Supply voltage (D) 1.97 0.82 1.27 1.15 2.09
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Selection of Optimal Levels
MR is the higher the better type of quality characteristic. Therefore, greater values of
MR are considered to be optimal. From Figure 7, it can be observed that the parameters:
concentration of Si powder (A); peak current (B); and pulse duration (C) appreciably
affect both the mean and variation in MR values (S/N ratio). The trend of variation of
the response curves suggested that the 3rd level of parameters A (A3) and B (B3) and the
2nd level of parameter C (C2) may provide maximum MR from workpiece surface when
machined by PMEDM. It can be further noted that in the case of parameters A, B, and C,
the highest value of average response corresponds to the highest value of S/N ratio.
However, this is not the case with the parameter D. The best average response for D
would be obtained at the 1st level but S/N ratio for D is best at the 2nd level. In order
to make a final decision, the relative contribution of mean value and S/N ratio has been
considered from analysis of variance (ANOVA). The pooled version of ANOVA for aver-
age values of raw data as well as S/N data is given in Tables 8 and 9, respectively.
Tables 8 and 9 show that the relative contribution of factor D toward mean value of MR
(12.98%) is higher than that for S/N ratio (2.06%). Therefore, considering the level cor-
responding to higher relative contribution, the optimum combination of input parameters
for best MR is A3, B3, C2, and D1.
Table 9. S/N pooled ANOVA (raw data: MR).
Process parameter Sum of squares
Degrees of
freedom Mean square F-value
Contribution
(%)
Concentration (A) 123.06 2 61.53 84.29* 43.08
Peak current (B) 155.73 2 77.87 106.67* 54.62
Pulse on time (C) 2.14 2 1.07 1.47* 0.24
Supply voltage (D) 1.46 (2) Pooled
Residual 1.46 2 0.73 2.06
Model 280.94 6 46.82 28.68*
Correlation total 282.40 8 100
The model F-value of 28.68 implies that the model is significant. There is only a 0.05% chance that a Model F-value thislarge could occur due to noise.*Significant at 95% confidence level.
Table 8. Pooled ANOVA (raw data: MR).
Process parameter Sum of squares Degrees of freedom Mean square F-value Contribution (%)
Concentration (A) 2.01 2 1.00 10.0* 29.84Peak current (B) 3.54 2 1.77 17.7* 54.57
Pulse on time (C) 0.36 2 0.18 1.8* 2.61
Supply voltage (D) 0.20 (2) Pooled
Residual 0.20 2 0.10 12.98
Model 5.91 6 0.99 14.01*
Correlation total 6.12 8 100
The model F-value of 14.01 implies that the model is significant. There is only a 0.05% chance that a Model F-value thislarge could occur due to noise.*Significant at 95% confidence level.
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parameter C (C2), and 1st level of parameter D may provide minimum SR. It may be
further noted that in the case of parameters AD, the lowest values of the mean response
correspond to the highest values of S/N ratio. This is the requisite condition for SR as it
has been decided to be as lower the best quality characteristic.
The pooled ANOVA for raw data of SR and S/N data is given in Tables 12 and 13,
respectively.
These tables indicate that the parameters A
C significantly affect both the mean valueand the S/N ratio. The percentage contribution of parameters indicates that A and B are
0
1
2
Peak current (A)
SR
(m)
5
3
1
1
3
5
S/Nratio(dB)
1
1.5
2
Pulse duration (s)
SR
(m
)
3
2
1
S/Nratio(
dB)
0
1
2
Supply voltage (V)
SR
(s
)
1.5
1
0.5
0
0.5
S/Nratio
(dB)
0
1
2
Concentration (g/L)
SR
(s)
4
2
0
2
4
S/Nra
tio(dB)
5050
30 2 4 6 9
100 150 70 90
Figure 8. Effect of process parameters on SR and S/N ratio. (#) Mean SR; (m) S/N ratio.
Table 12. Pooled ANOVA (raw data: surface roughness).
Process parameter Sum of squares
Degrees of
freedom Mean square F-value
Contribution
(%)
Concentration (A) 0.43 2 0.22 22.00* 23.29
Peak current (B) 1.24 2 0.62 62.00* 68.75
Pulse on time (C) 0.05 2 0.02 2.00* 1.14
Supply voltage (D) 0.03 (2) Pooled
Residual 0.03 2 0.01 6.82
Model 1.72 6 0.287 14.81*
Correlation total 1.75 8 100
The model F-value of 14.81 implies that the model is significant. There is only a 0.05% chance that a Model F-value thislarge could occur due to noise.*Significant at 95% confidence level.
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highly significant parameters in controlling the mean values of SR and S/N ratio.
However, parameter Chas very small contribution toward the mean and S/N ratio for SR.
ESTIMATION OF OPTIMUM RESPONSE CHARACTERISTICS
Machining Rate
The significant process parameters affecting the MR and their optimum levels (as
already selected) are as follows:
Significant partameters: A, B, and COptimal levels: A3, B3, C2, and D1.
The average value (from Table 6) of MR at:
3rd level of powder concentration ( A3) 1.65;
3rd level of peak current ( B3) 1.92;
2nd level of pulse duration ( C2) 1.33.
The overall mean of MR ( TMR) 1.10 (from Table 5).
The predicted optimum value of material removal (MR) has been calculated as follows:
MR A3 B3 C2 2 TMR 2:70
The 95% confidence intervals for the mean of the population (CIPOP and CICE) and
three confirmation experiments have been calculated by substituting the values in
Equations (1) and (2):
CICE
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiF1,fe Ve
1
neff
1
R
s, 1
CIPOP ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiF1,fe Ve
neffs
, 2
Table 13. S/N pooled ANOVA (raw data: surface roughness).
Process parameter Sum of squares
Degrees of
freedom Mean square F-value
Contribution
(%)
Concentration (A) 19.81 2 9.90 70.71* 23.12
Peak current (B) 63.58 2 31.79 227.07* 74.88Pulse on time (C) 0.85 2 0.43 3.07* 0.67
Supply voltage (D) 0.28 (2) Pooled
Residual 0.28 2 0.14 1.33
Model 84.24 6 14.04 16.33*
Correlation total 84.52 8 100
The model F-value of 16.33 implies that the model is significant. There is only a 0.05% chance that a Model F-value thislarge could occur due to noise.*Significant at 95% confidence level.
Machining of Al10%Sicp Metal Matrix Composites 147
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N 9 3 27 (treatment 9, repetitions 3); fe (error DOF) (8 6) 2; ve (error
variance) 0.10 (recalculated from Table 8)
neffN
1 DOF of all factors used
in the estimate of mean 3:86
F0.05 (1,2) 18.51 (tabulated F-value). Therefore, CIPOP 0.69 and CICE 1.04.
The 95% confidence intervals (CIPOP and CICE) of the predicted optimum MR are:
CIPOP: 2.01
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The 95% confidence intervals (CIPOP and CICE) of the predicted optimum SR:
CIPOP: 0.07
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machining of Al10%SiCP MMCs. The results indicate that concentration of the added
silicon powder and peak current are the most influential parameters on MR and SR. The
addition of appropriate amount of silicon powder (4 g/L) into the dielectric fluid of EDM
triplicates the MR and lowers the SR by 33%. The optimum settings of parameters for
highest MR are: powder concentration 4 g/L, peak current 9 A, pulse duration 100ms and
supply voltage 50 V and for lowest SR are powder concentration 4 g/L, peak current 3 A,
pulse duration 100ms and supply voltage 50 V. The selected optimal values of the process
parameters are validated with the confirmation experiments conducted at the same settings
for each of the response characteristics.
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