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Abstract — The newly engineered metal matrix composite (MMC)of aluminium 7075 reinforced with 10 wt% of SiC particles were

prepared by stir casting method. Electrical discharge machining(EDM) was employed to machine MMC with copper electrode. Theexperiment plan adopts face centered central composite design ofresponse surface methodology. Analysis of variance was applied toinvestigate the influence of process parameters and their interactionsviz., pulse current, gap voltage, pulse on time and pulse off time on

material removal rate (MRR), electrode wear ratio (EWR) andsurface roughness (SR). The objective was to identify the significant

process parameters that affect the output characteristics. Further amathematical model has been formulated by applying responsesurface method in order to estimate the machining characteristicssuch as MRR, EWR and SR.

Keywords — EDM, metal matrix composite, RSM, ANOVA

I. I NTRODUCTION

LUMINIUM Metal Matrix Composites (MMCs) are one ofthe recent advanced materials having the properties of

light weight, high specific strength, good wear resistance and a

low thermal expansion coefficient. These composite materialsare extensively used in structural, aerospace and automotiveindustries. The applications of existing Aluminium SiliconCarbide MMCs are limited because of their poormachinability which results in poor surface finish andexcessive tool wear. MMCs are composed of metallic basematerial called matrix, which is reinforced with a hard ceramicreinforcement [1] – [3]. Due to possession of higher hardnessand reinforcement strength, composite materials are difficultto be machined by traditional techniques. Hence Electricaldischarge machining (EDM) process becomes viable methodto these kinds of composite materials. Since the EDM processdoes not involve mechanical energy, the material removal rate

is not influenced by the material properties like hardness,strength, toughness etc. Materials with poor machinability

S. Gopalakannan is a Full time Research Scholar in the Department ofMechanical Engineering, Pondicherry Engineering College, Puducherry-605014, INDIA (Mobile: 9944949026, fax: 0413-2655101303; e-mail:[email protected]).

T. Senthilvelan, Professor and Head, Department of MechanicalEngineering, Pondicherry Engineering College, Puducherry, INDIA (e-mail:[email protected] ).

K. Kalaichelvan, Associate Professor, Department of ProductionTechnology, Madras Institute of Technology, Anna University, Chennai,INDIA (e-mail: [email protected] ).

such as cemented tungsten carbide and composites can also be processed without much difficulty by the EDM process [4]-[5].

Several investigations into the machining aspects of EDMon MMCs with only single particulate reinforcement have

been carried out and reported. George et. al investigated thecarbon- carbon composites considering three parameters attwo levels and reported that pulse current and pulse on time

are significant for EWR and MRR [6]. The effect of percentage volume of SiC and other machining characteristicswere studied while machining Al-SiC, and concluded thatincrease in SiC decreases the MRR, where as increases EWRand SR [7]-[8].The effect of rotation of electrode on EDM ofAl-SiC and Al- Al 2O3 composites yielded positive effect onMRR, EWR and SR [9]-[10]. Harmesh Kumar and PauloDavim have carried out an experimental study on themachining parameters in powder mixed electric dischargemachining of Al-10%SiC MMC. They mixed silicon powderinto the dielectric fluid and reported that the addition of silicon

powder into the dielectric fluid of EDM increases MRR anddecreases SR [11].

The present work is envisaged to develop a mathematicalmodel and analyze the effects of EDM parameters on the

performance characteristics of MMNC using response surfacemethodology (RSM). Accordingly, the quantitativemathematical models have been carried out to study influenceof pulse current (I p), voltage (V g), pulse on time (T on) and

pulse off time (T off ) on the material removal rate (MRR),electrode wear rate (EWR) and surface roughness (SR) byusing RSM [12].

II. EXPERIMENTAL DETAILS

A. Work Material and Ceramic ReinforcementThe material used in the present investigation consists of

Aluminium 7075 (Al-Zn-Mg-Cu alloy) is used as the basematrix alloy. Its chemical composition (%) is Si = 0.2, Fe =0.22, Cu = 2.0 max, Mn = 0.1, Mg = 2.1-2.9, Zn = 5.1-6.1, Ti= 0.1 max, Cr = 0.2, and balance as Al. It is a v ery highstrength material used for highly stressed structural parts. Theapplications of Al 7075 are Aircraft fittings, gears and shafts,fuse parts, meter shafts and gears, missile parts, regulatingvalve parts, worm gears, keys, aircraft, aerospace and defenseapplications; bike frames, all terrain vehicle (ATV).

Electric Discharge Machining Of Al7075/10%Sic Metal Matrix Composite By

Applying Response surface Method

S. Gopalakannan, T. Senthilvelan, and K. Kalaichelvan

A

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Aluminium-zinc-magnesium alloys have a greater response toheat treatment than the binary aluminium-zinc alloys resultingin higher possible strengths. It possesses high heat dissipationcapacity due to its high thermal conductivity and is suitablefor high strength and high temperature applications. Siliconcarbide (SiC) has excellent high-temperature strength, a veryhigh oxidation ability and good chemical resistance. Itsthermal conductivity is four times that of steel and it has low

thermal expansion co efficient, hence it is preferred for hightemperature heat exchangers.

B. Preparation of MMC by stir casting method and its Mechanical PropertiesThe aluminium matrix was reinforced with 10wt% of SiCp

with an average particle size of 25 microns. The compositeswere cast using stir casting technique as it ensures uniformdistribution of the reinforcements [13]. The SEM micrographof MMC shows the uniform dispersion of the SiCp particles isgiven in Fig. 1.

Fig. 1 SEM micrograph showing the SiC particle distribution

From the cast MMC the standard tensile specimens were prepared by machining as per dimensions of ASTM E8. Toobtain mechanical properties, specimens with overall length100 mm, thickness of 6 mm and a gauge length of 25 mmwere tested in UNITEK - 94100 universal testing machinewhich gives an ultimate tensile strength of 132 MN/mm 2 andyield strength of 114MN/mm 2. The hardness of the sampleswas measured using a UHL Vickers micro hardness measuringmachine by applying a load of 0.5kg and this load was applied

for 20 seconds yielded 102 HV. In order to eliminate the possibility of error a minimum of five hardness readings weretaken for each sample.

Fig. 2 ASTM E8 standard tensile specimen

C. Design of ExperimentsResponse surface methodology (RSM) is an interaction of

mathematical and statistical techniques for modeling andoptimizing the response variables which incorporatesquantitative independent variables. The behavior of the systemis explained by the following second order polynomialregression model also called a quadratic model. Thecoefficients of regression model can be estimated from the

experimental results by ‘Design Expert 8.0.6’ software.

(1)

In the present study the experiments were designed on the basis of the central composite design (CCD) technique. Thefactorial portion of CCD is a full factorial design with allcombination of the factors at two levels (high, +1, and low, -1)and composed of eight star points, and six central points(coded level 0), which is the midpoint between the high andlow levels, corresponds to an α value of 1. The “face-centeredCCD” involves 30 experimental observations at fourindependent input variables. The Table 1 shows both thecoded and actual values of the four machining parameters andtheir possible ranges [14]. The experimental layout that wasadopted in this study in the actual form is shown in Table 2.

TABLE 1MACHINING PARAMETERS AND THEIR LEVELS

Labels Parameters LEVELS-1 0 +1

A Voltage(V) volt 40 50 60

B Pulse current(I p) Amps 6 10 14

C Pulse on time(T on) µs 4 6 8

D Pulse off time(T on) µs 5 7 9

D. Experimental ProcedureA series of experiments were performed on a die-sinking

EDM of type Grace D-6030S based on Table 2. The workmaterials of size diameter 20mm and thickness 30 mm, andelectrolytic copper electrode of 10 mm diameter was used.The circular electrode is preferred over the other shapes ofelectrodes, provides higher MRR and lower EWR [15].Commercial grade kerosene was employed as the dielectric

fluid and impulse jet flushing system was used to flush awaythe eroded materials from the sparking zone. The machining isdone for 20 minutes for all experiments. The material removalrate and electrode wear values have been calculated by weightdifference of the workpiece and electrode material before andafter the machining using a digital weighing scale of 0.001gram precision.

III. R ESULTS AND DISCUSSION

The machining performance criteria selected for this studywere based on performance characteristics such as material

SiCarticles

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removal rate (MRR), electrode wear rate (EWR) and surfaceroughness (SR) [16].

MRR = (w jb-w ja) / t (2)

Where w jb and w ja are weights of the work piece before andafter machining, and the machining time. Electrode wear(EW) is expressed as the ratio of difference of weight of the

tool electrode before and after machining to the machiningtime.

EW = (w eb-w ea) / t (3)

Where w eb and w ea are weights of the tool electrode beforeand after machining, and the machining time.

TABLE 2EXPERIMENTAL LAYOUT

Exp.No

Voltage(A)

Current(B)

Pulse onTime (C)

Pulse offTime (D)

1 40 6 4 9

2 60 6 8 93 50 10 4 74 50 10 6 75 50 6 6 76 60 14 4 57 40 14 8 98 40 6 8 99 50 10 6 910 40 6 4 511 60 10 6 712 60 6 8 913 50 10 6 714 50 10 8 715 40 14 4 916 50 10 6 717 50 10 6 7

18 60 6 4 919 60 14 8 520 60 6 4 521 40 14 8 522 60 14 4 923 50 14 6 724 50 10 6 725 60 6 8 526 50 10 6 727 40 14 4 528 40 6 8 529 50 10 6 530 40 10 6 7

The material removal rate and electrode wear values have

been calculated by weight difference of the work material andthe electrode before and after machining using a digitalweighing scale and recorded. The average surface roughnessvalue R a (µm) was chosen to assess the surface finish quality.The surface of material generated using EDM is composed ofmany microscopic craters associated with random sparkdischarge between the electrodes. The size of craters producedmainly on the work piece surface depends mainly upon theenergy of the discharge. As more energetic pulses usually leadto a higher material removal, so a deeper cavity was formed.As the cavity depth increases the roughness value also

increases [4]. The surface roughness measurements for themachined surface are performed with a Kosaka Surfcoder SE1200.

A. Mathematical model for MRR, EWR and SR.The fit summary recommended that the quadratic model

is statistically significant for analysis of MRR and SR andlinear model for EWR. The results of quadratic and linearmodels are given in ANOVA Table 4, TABLE 5 and Table 6respectively.

TABLE 3EXPERIMENTAL RESULTS

Exp.No

Response 1MRR (g/min)

Response 3EWR (g/min)

Response 3SR (µm)

1 0.29 0.001 6.245

2 1.047 0.004 14.3223 0.795 0 .003 7.5454 0.329 0.008 14.7175 1.046 0 .003 9.1496 0.1622 0.013 9.5777 0.484 0.011 16.7588 1.178 0.003 10.3899 0.8175 0 .006 12.19610 0.0854 0.005 6.30111 0.3682 0.009 18.21412 0.738 0.014 21.32413 0.3521 0.008 10.32514 0.3621 0.008 13.60815 0.0866 0.004 6.75316 0.342 0.008 12.48517 0.372 0.008 14.86718 0.292 0.001 9.0419 0.598 0.012 14.51420 0.0918 0.004 7.64721 0.361 0.012 15.84522 0.1165 0.003 10.16823 0.478 0.010 11.72824 0.354 0.008 16.24325 0.157 0.004 11.558

26 0.369 0.008 15.85127 0.165 0.007 10.00828 0.142 0.005 13.28929 0.376 0.007 12.51230 0.3192 0.006 12.629

When the R 2 approaches unity, the better the responsemodel fits the actual data. It exists the less the difference

between the predicted and actual data. Further the value ofadequate precision (AP) in this model, which compares therange of the predicted value at the design point to the average

prediction error, is well above 4. The values obtained are asfollows: R 2 = 0.9765and AP= 42.262 for MRR; R 2 = 0.9365and AP= 36.436 for EWR; R 2 = 0.8865 and AP= 22.093 for

SR. The backward elimination process eliminates theinsignificant terms to adjust the fitted quadratic models. Theseinsignificant model terms can be removed and the test of lackof fit displays not significant as it is desired. The finalresponse equations for MRR, EWR and SR are:

Material Removal Rate (MRR) In Coded Terms: MRR =+0.46-0.029* B+0.044* C+0.068* D-0.11* B * C-0.17* B * D+0.13* C * D-0.29* B 2+0.23 * C 2 (4)

In Actual Factors:

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MRR =+0.45604-0.028717* Current+0.044039*Ton+0.068283* Toff-0.10618* Current * Ton-0.17487 *Current * Toff +0.13429* Ton * Toff-0.28971*Current 2+0.23379* Ton 2 (5)

TABLE 4ANNOVA TABLE FOR MRR

SOURCE SS DF MS FValue

Prob

ModelResidualLack of FitPure ErrorCor Total

1.391.200.91 0.28 2.58

82116 5 29

0.170.0570.0570.057

3.04

1.01 0.5461 Notsignificant

Std. Dev. 0.24Mean 0.42C.V. % 56.51PRESS 2.44

R-Squared 0.9765Adj R-Squared 0.9399Pred R-Squared 0.8534Adeq Precision 42.262

TABLE 5ANNOVA TABLE FOR EWR

SOURCE SS DF MS FValue Prob


1.391.200.91 0.28 2.58

82116 5 29

0.170.0570.0570.057

3.04


Std. Dev. 1.482E-003Mean 60767E-003C.V. % 21.91PRESS 9.34E-005


TABLE 6

ANNOVA TABLE FOR SR

SOURCE SS DF MS FValue Prob


1.391.200.91 0.28 2.58

82116 5 29

0.170.0570.0570.057

3.04


Std. Dev. 2.60Mean 1.29C.V. % 21.32PRESS 306.74


Electrode wear rate:

In Coded Terms: EWR= + 6.767E-003 + 3.111E-003*B + 1.778E-003*C -1.222E-003*D + 1.062E-003* B*C + 1.188E-003*C*D (6)

In Actual Factors:EWR = + 0.018371 - 1.90972E-005*Current - 2.51736E-003*Ton-2.39236E-003*Toff+1.32812E-004*Current*Ton+2.96875E-004*Ton*Toff (7)

Surface Roughness:

In Coded Terms: SR =+13.01-0.28* A+0.82* B+1.52 * C+0.59* D-1.21*A*D+1.42* B * C-1.17* B * D+4.55* A 2-5.91*D 2 (8)

In Actual Factors:SR=+13.01098-0.27933*Voltage+0.81656*Current+1.51839*

Ton+0.59122* Toff-1.20669* Voltage * Toff +1.42281*Current*Ton-1.17219*Current*Toff+4.54560*Voltage 2-

5.90740* Toff 2 (9)

B. Effect of Process Parameters on MRRThe discharge energy was normally smaller when the

pulse current was smaller, hence the smaller discharge energydelivered into the machining zone was associated with a lowerMRR therefore the machined cavity was shallower and thedebris was more easily expelled from the machining zone. Incontrast higher the peak current higher the discharge energy,therefore deeper cavity was formed. However the cavity depthincreases the debris normally became harder to expel from themachining zone [17]. This disturbs the electrical discharge andcauses short-circuit, results in low MRR. Hence optimal valueof pulse current is necessary to achieve maximum MRR. Theexperimental results for MRR, EWR and SR are given inTable 3.

Fig. 3(a)Figure 3 shows the estimated response surface for MRR

in relation to the design parameters of pulse current, pulse ontime and pulse off time. As can be seen from the Fig. 3(a) theMRR increases considerably with increase in pulse current

and pulse on time, similarly for pulse off time as well shownin Fig 3(b). However the MRR increases with respect to pulsecurrent for any value of voltage. This is due to their dominantcontrol over the input energy [18]. Thus the voltage is aninsignificant parameter for MRR whereas Ton and Toff aresignificant parameters.

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Fig.

3(b) Fig. 3 (c)

Fig. 3 (a), (b) and (c) shows the response of Current, Ton and Toffon MRR

C. Effect of Process Parameters on EWRThe wear of tool electrode is a dynamic process which is

simultaneously influenced by different parameters withvarying input values. While electrical discharges erodematerials from both the tool electrode and work piece, thecracked carbon from the dielectric fluid may be depositedon the surface of tool electrode which protects them fromfurther erosion. Generally longer pulse duration, lower

pulse current and pulse off time tends to increase the possibility of carbon deposition on the electrode surface,which helps to minimize the electrode wear [19].

The estimated response surface for EWR in relation tothe design parameters of pulse current, pulse on time and

pulse off time is shown in Figure 5. As can be seen from theFig. 5(a), the EWR increases considerably with increase in

pulse current and pulse on time. The EWR is more at highervalue of Ton and T off, whereas the EWR increases withrespect to pulse current for any value of voltage. Thus thevoltage is an insignificant parameter for EWR whereas Tonand Toff are significant parameters [20].

Fig. 4(a)

Fig. 4(b)

Fig. 4(c)Fig. 4 (a), (b) and (c) shows the response of Voltage, Current, Ton

and Toff on EWR.

D. Effect of Process Parameters on SRIn case of surface roughness, the most influencing

parameters are pulse current, pulse on time. When any one of

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Fig.5(a)

Fig.5(b)

Fig. 5(c)

Fig. 5 (a), (b) and (c) shows the response of Voltage, Current, Ton

and Toff on EWR. this parameter is increased, it enhances the surface roughnessvalue. The high energy pulse produces crater on the machinedsurface which leads to poor surface finish quality.

The estimated response surface for SR in relation to thedesign parameters of pulse off time and voltage is shown inFig. 5 (a), pulse current and pulse on time in Fig. 5(b). As can

be seen from this figure, the SR tends to increase as the pulse

current increases, where as with voltage it increases up to 50volt and then decreases. The SR also increases with increase in pulse on time. This is due to their dominant control over theinput energy.

IV. MULTI RESPONSE OPTIMIZATION OF THE PROCESS

Selection of the optimal machining parameter combinationfor achieving improved process performance, e.g., materialremoval rate, electrode wear rate and surface roughness, is achallenging task in EDM operation due to the presence of alarge number of process variables and complicated stochastic

process mechanism. Derringer and Suich [14] describes amultiple response method called desirability. It is an attractivemethod for industry for optimization of multiple qualitycharacteristics problems. The method makes use of anobjective function D(X), called the desirability function(Utility transfer function) and transform an estimated responseinto a scale-free value (di) called desirability. The desirablerange are from 0 to 1 (least to most desirable, respectively). Avalue of 1 represents the ideal case; 0 indicates that one ormore responses are outside their acceptable limits. Compositedesirability is the weighted geometric mean of the individualdesirability for the responses. The factor settings withmaximum total desirability are considered to be the optimal

parameter conditions. The simultaneous objective function is ageometric mean of all transformed responses [21]. Thiscombination has been evaluated with the help of DesignExpert Software. Three responses i.e., MRR, EWR, and SR,have been optimized simultaneously using developed models,i.e., Eqs. 4-9, based on composite desirability optimizationtechnique. In multi-response optimization, a measure of howthe solution has satisfied the combined goals for all responsesmust be assured. The optimality solution is to evaluate theinput process parameters in experiment range for maximizingMRR and minimizing both EWR and SR. The numeric valuesof constraints, optimum values of input parameters, and the

predicted values of responses under these conditions are presented tables 7 and 8.

Once the optimal level of the process parameters is selected,the final step is to predict and verify the improvement of the

performance characteristics using the optimal level of themachining parameters. Experiment was performed tomachine and verify the EDM at the above optimal input

parameter setting for MRR, EWR and SR compared withoptimal response value. Table 8 shows the age of error percentfor experimental validation of the developed models for theresponses with optimal parametric setting during EDM. Fromthe analysis of Table 8, it can be observed that the error

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calculated is small. Obviously, this confirms excellentreproducibility of the experiment conclusions.

TABLE 7CONSTRAINT OF INPUT PARAMETERS AND OPTIMUM VALUES

Parameter Goal Optimum valueVoltage (V) In range 47.34Pulse Current (Amps) In range 6.00Pulse on time (Ton) In range 8.00Pulse off time(Toff) In range 8.97

TABLE 8PREDICTED AND OBSERVED OPTIMUM VALUES OF RESPONSES

Response Goal Predicted Observed Error (%)MRR(g/min) Maximize 1.26554 1.196 5.9EWR(g/min) Minimize 0.00149949 0.001575 -3.5

SR(µm) Minimize 9.91344 10.648 -6.9

V. CONCLUSION

In this study, the MRR, EWR and SR in EDM process of Al7075/10% SiC using copper electrode were modeled analyzedand optimized through RSM. Summarizing the main features,the following conclusions could be drawn:

1. The predicted values match the experimental valuesreasonably well with R 2 of MRR, EWR and SR.

2. Pulse current was found to be the most important factoraffecting all the tree output parameters MRR, EWR and SR.

3. The main significant factors that affect the MRR are pulse current, pulse on time and pulse off time whereasvoltage remains insignificant. The pulse current and pulse ontime have statistical significance on both EWR and SR.

4. The higher pulse off time offers lower the EWR value.On contrary, the EWR increases with increase in pulse currentand pulse on time for any value of voltage.

5. The value SR increases with increase in pulse current and pulse on time, whereas in voltage is concerned SR increasesup to 50 volt and then decreases with a further increase involtage.

6. The optimum parameter of combination setting isVoltage 47.34 Volt, Pulse current 6.00 Amps, Pulse on time8.00µs and pulse off time 8.97µs for maximizing MRR,minimizing EWR and SR.

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