ORIGINAL ARTICLE

Optimal parameter settings for rough and finish machiningof die steels in powder-mixed EDM

Anirban Bhattacharya & Ajay Batish & Gurmail Singh &

V. K. Singla

Received: 23 February 2011 /Accepted: 24 October 2011 /Published online: 12 November 2011# Springer-Verlag London Limited 2011

Abstract The present study was undertaken to identify theappropriate parameter settings for rough and finish machinedsurface for EN31, H11, and high carbon high chromium(HCHCr) die steel materials in a powder-mixed electricdischarge machining process. The effect of seven differentprocess variables along with some of their interactions wasevaluated using a dummy-treated experimental design andanalysis of variance. Material removal rate (MRR), tool wearrate, and surface finish were measured after each trial andanalyzed. The parameter settings for rough and finishedmachining operations were obtained. EN31 exhibited maxi-mum MRR as compared to the other two materials at similarprocess settings. Copper (Cu) electrode with aluminumsuspended in the dielectric maximized the MRR. Suspendingpowder in the dielectric resulted in surface modification.Graphite powder showed a lower MRR but improved thesurface finish. HCHCr require higher current and pulse onsettings for initiating a machining cut and works best incombination with tungsten–Cu electrode and graphite powderfor improved finish. The MRR for H11 is lower than EN31but significantly higher than HCHCr under same processconditions.

Keywords Powder-mixed dielectric . Electric dischargemachining .Material removal . Tool wear . Surface finish .

Rough machining . Finish machining

1 Introduction

Electrical Discharge Machining (EDM) is one of the mostversatile machining processes in the manufacture ofprecision intricate components of hardened materials. Theprocess involves cutting of work material using a conduct-ing electrode (tool) by a series of electrical sparks generatedin a dielectric medium. The process produces a mirrorimage of itself by advancing into the workpiece. Thephenomenon of material removal process in EDM makes itsuitable for a secondary application resulting in theimprovement of surface properties. The sparks generatedhave temperature in the vicinity of 8,000°C that creates aplasma channel which causes fusion or partial vaporizationof the workpiece material, electrode, and the dielectric fluidat the point of discharge. Towards the end of the machiningprocess, the plasma channel collapses leading to depositionof some of these constituents on the machined surfaceunder appropriate process conditions. Thus, certain alloyingelements may be introduced through the electrode or mixedwith the dielectric in the form of fine powder for specificsurface modifications. The process called PMEDM resultsin the transfer of some elements to the machined surfaceunder appropriate process parameter settings.

Many process parameters which when varied in thePMEDM process have some effect on output responseparameters such as material removal rate (MRR), tool wearrate (TWR), and surface finish (SR) of the machinedsurface. The parameters that are generally varied to measuretheir impact on the above responses are (a) electrode

A. Bhattacharya :A. Batish (*) :G. Singh :V. K. SinglaMechanical Engineering Department, Thapar University,Patiala 147004 Punjab, Indiae-mail: batishajay@gmail.com

A. Batishe-mail: abatish@thapar.edu

A. Bhattacharyae-mail: abhattacharya@thapar.edu

G. Singhe-mail: gurmail.malhi@gmail.com

V. K. Singlae-mail: vsingla@thapar.edu

Int J Adv Manuf Technol (2012) 61:537–548DOI 10.1007/s00170-011-3716-5

material, (b) current, (c) pulse on and off time, (d) pulsewave form and frequency, (e) polarity, (f) inter-electrodegap, (g) dielectric fluid, (h) discharge voltage, and (i)suspended powder. This study has been carried out toreview the effect of some of these process parameters onMRR, TWR, and SR of three different die steel materialsand generate optimized process parameter settings for thesematerials.

Over few decades, many research works have beenundergone for the control, optimization, and prediction ofthe EDM process. For rough machining, maximizing of MRRwas possible. But even the process has the possibility ofachieving fine surface finish (for finish machining), theprocess has constraints of abnormal discharge, scatteredmachining resulting in non-homogeneous surface finish, orhigh machining time [1, 2]. As reported, in conventionalEDM, high surface finish is achieved with copper electrodewith area below a specified value [3]. Therefore, alteration inthe process to improve MRR, reduce TWR, and enhance SRand surface properties, PMEDM has gained lot of interest.Additives can improve MRR, decrease TWR, and improvethe surface quality of the work mid-finish machining andfinish machining [4]. A detailed review on the currentresearch trends in EDM [5], as well different attempts aboutthe method of surface modifications using different powdersmixed in dielectric [6] had been made. The effect of siliconpowder addition in dielectric have been investigated for AISID2 die steels [7], and performance improvement usingpowder-mixed dielectric fluid has been found possible [8].It has been reported that the presence of powder particles indielectric fluid and the concentration of powder createsconditions suitable for achieving a better surface quality inthe machined area [9]. The effect of the addition of graphite[10] and aluminum [11] powders in dielectric was studied forenhancing MRR, reducing TWR or for improvement ofsurface finish. MRR, TWR, and wear ratio had been studiedusing powder-mixed EDM of cobalt-bonded tungsten car-bide [12]. The effect of electrode (copper) area on surfaceroughness and surface topography of AISI H13 die steelduring silicon powder mixed in dielectric has been investi-gated [13]. Effect of different process parameters on thesurface roughness of the machined workpiece has beenstudied [14]. Experimental investigations on the machiningefficiency and surface roughness in rough machining havebeen carried out and it has been found that PMEDMimproves machining efficiency and surface roughness [15].Lubricant layer deposition by EDM process during finishingprocess and monitoring of the process had been reported[16]. The influence of electrical conditions on performanceduring powder suspension in working oil had been assessedand the process was found capable of titanium carbidedeposition [17]. Comparison of performances betweenkerosene and abrasive mixed deionized water had been

made, as well relationship between surface roughness, MRRwith EDM-operating parameters for different kinds ofpowder, and concentration in kerosene/water has beendeveloped [18]. Artificial neural network, Taguchi technique,had been implemented for the surface modification in EDMprocess using tungsten–copper powder metallurgy-sinteredelectrodes [19, 20]. Many optimization techniques likeresponse surface methodology [21], Taguchi technique[22], and analytic hierarchy process [23] had been imple-mented for a better control of the process.

The effect of the different types of powders suspended indielectric and its effect on output responses when studied incombination with different workpiece and electrode mate-rial is still not fully exploited. The feasibility of the processis well established and no studies have been reported onsurface modification using graphite and aluminum powderin kerosene oil and refined mineral oil (clean transformeroil) dielectric fluid with copper and tungsten–copperelectrode. In the present study, the effect of different inputparameters, namely, current, electrode material, dielectricmedium, pulse on time, pulse off time, and powder mixedin dielectric and some of their interactions on the MRR,TWR, and SR of three different die steel materials havebeen studied. The effect of these parameters on outputresponses has been analyzed using Analysis of Variance(ANOVA) to establish additive equations for each responseand for each material. The optimal parametric setting usingadditive equations have been developed for both rough andfinished machining.

2 Methodology and experimental setup

2.1 Experimental design with dummy treatment

The experimental study was undertaken with an objectiveto identify the process parameters that significantly affectthe MRR, TWR, and SR. A pilot study along withextensive review of literature was carried out to identifythe factors that may affect these four responses in PMEDM.Based on the results of this study, the workpiece material,the dielectric fluid, electrode material, pulse on and offtime, and the current and type of suspended powder wereidentified as some of the contributing factors. All the otherfactors such as open circuit voltage (135±5%V), polarity(anode, workpiece; cathode, tool), and powder concentra-tion of 10 g/l and machining time of 10 min were keptconstant throughout the study. The levels for the processparameters like current, pulse off, and pulse on time wereselected based on extensive literature review, pilot study,and the setup range available on the machine. Based on thisanalysis, five of the seven factors studied were varied atthree levels each and the remaining two factors were varied

538 Int J Adv Manuf Technol (2012) 61:537–548

at two levels each. The factors with their designation, units,and their respective levels are listed in Table 1.

The interactions between two factors are studied tomeasure their combined effect as varying one of the factorsmay have an adverse or a synergetic effect on anotherfactor. In the present case, the interaction effect betweeneach of the seven factors would result in a full factorialexperimental design which is orthogonal. All combinationsof all the seven factors will need to be tested. Using thisinformation, both factor and interaction effects can beestimated. Unfortunately, such an experimental design willmake the number of experimental runs prohibitive, espe-cially since the experiments were to be conducted onequipment with lengthy setup time. Thus, such a design ispossible only if there are few factors to be investigated.Taguchi has developed a family of fractional factorialexperiment matrices which can be utilized to overcome thefinancial and time limitations associated with full factorialexperiments. Certain treatment conditions are chosen tomaintain the orthogonality among the various factors andinteractions [24]. The interactions that need to be studied inan experiment will need to be chosen carefully so thatfewer selections of interactions could be used to estimatethe effect of factors. Before the main experiment started,some of these possible interactions between factors werestudied during a pilot experiment. The interactions betweencurrent, powder, and pulse on time were observed to beinsignificant and were thus not included in the mainexperiment. Three interactions between the main factorswere identified for a detailed statistical analysis. Thesewere workpiece vs. electrode (A×C), workpiece vs. powder(A×G), and electrode vs. powder (C×G).

Taguchi’s experimental design methodology was usedfor designing the experimental trials because of its inherentcapability of estimating the significance of control factorson the measured responses by conducting fewer experi-ments. The basic orthogonal arrays (OA) were designed toaccommodate either two or three level factors which could

be modified to accommodate higher levels or mixed levelslike the one used in this study. In order to accommodatetwo and three level factor in a single experimental design,Taguchi had proposed a dummy treatment. Dummytreatment accommodates two-level factor in a basic three-level OA by using only two of possible levels for the factorand simply repeating one level from the previous of twolevels for the indicated third level. Any one of the twolevels for the factor can be repeated, so whichever iseasiest, cheapest, or makes more sense should be repeated[24].

The minimum degrees of freedom (dof) required in theexperiment are the sum of all the dof of factors andinteractions. The dof for each factor is given by (n−1),where n is the number of levels for each factor. In thepresent experimental setup, there are five three-level factorsand two are two-level factors. Thus, each of the three-levelfactors has two dof and each two-level factor has one dof.The interaction dof are calculated by multiplying the dof ofthe interacting factors. The total dof for the experiment wasthus calculated to be 20. The most suitable array for acombination of three-level and two-level factors studied inthis case was identified as L27 with 26 dof assigned to itsvarious columns. Since the experimental design neededonly 20 dof, the additional six dof were used to measure therandom experimental error. The assignments of factors weremade using Taguchi linear graphs [24]. Factors A, C, and Gwere assigned to columns 1, 2, and 5, respectively.Columns 3 and 4, columns 6 and 7, and columns 8 and11 were merged to measure the interaction between thefactors A×C, A×G, and C×G, respectively. The remainingassignments were made in the other appropriate unassignedcolumns (factor B to column 9, D to 10, E to 12, and F to13). Two-level factors, dielectric fluid, and electrodematerial were used with the dummy treatment for the thirdlevel. The final form of the OA with actual values for eachfactor, as used for experimentation, is shown in Table 2.

2.2 Experimental setup

The experiments were conducted on the electrical dischargemachine, model T-3822 of Victory Electromech, availablein the Machine Tool Laboratory of the university. Aseparate tank (dimensions, 330×180×187 mm) fabricatedusing 3-mm thick mild steel material with a capacity of 9 lwas used with motorized stirrer for mixing of the suspendedpowder particles throughout the experimentation and toavoid settling of powder particles. The machine andexperimental setup along with a schematic arrangement isshown in Fig. 1.

Three kinds of die steel workpiece materials EN31, H11,and HCHCr were used in the experimental study. Theelectrode materials used were tungsten–copper (W–Cu) and

Table 1 Factors of interest and their levels

Factors, symbol (unit) Levels

Level 1 Level 2 Level 3

Worpiece material, A EN 31 H11 HCHCr

Dielectric, B Kerosene Refined mineral oil(transformer oil)

Kerosenea

Electrode, C Copper Tungsten–copper Coppera

Pulse off (μs), D 38 57 85

Pulse on (μs), E 10 50 100

Current (Amp), F 2 5 8

Powder, G No Graphite Aluminum

aDummy-treated level

Int J Adv Manuf Technol (2012) 61:537–548 539

copper (Cu). The chemical compositions of workpiece andelectrode material were measured on an optical emissionspectrometer DV-6 and are given in Tables 3 and 4,respectively. Each workpiece was cut to a size of 100×50×10 mm for experimental trials and machined using

electrodes with 20 mm diameter. Each of the workpiece wasground (top and bottom surface) before the experimentationso as to maintain proper alignment with the tool face andflatness. The workpiece and tool used for the present study areshown in Fig. 2.

(a) Control panel (b) Tank mounting (c) Schematic arrangement

Fig. 1 Machine, setup, and schematic arrangement for the PMEDM process. a Control panel, b tank mounting, c schematic arrangement

Table 2 L27 experimentaldesign

aDummy treated

Trial no. Workpiece Dielectric Electrode Pulse off Pulse on Current Powder

1 EN31 Kerosene Cu 38 10 2 No

2 EN31 Refined mineral oil Cu 57 50 5 Gr

3 EN31 Kerosenea Cu 85 100 8 Al

4 EN31 Refined mineral oil W 57 100 8 No

5 EN31 Kerosenea W 85 10 2 Gr

6 EN31 Kerosene W 38 50 5 Al

7 EN31 Kerosenea Cua 85 50 5 No

8 EN31 Kerosene Cua 38 100 8 Gr

9 EN31 Refined mineral oil Cua 57 10 2 Al

10 H11 Refined mineral oil Cu 85 50 8 No

11 H11 Kerosenea Cu 38 100 2 Gr

12 H11 Kerosene Cu 57 10 5 Al

13 H11 Kerosenea W 38 10 5 No

14 H11 Kerosene W 57 50 8 Gr

15 H11 Refined mineral oil W 85 100 2 Al

16 H11 Kerosene Cua 57 100 2 No

17 H11 Refined mineral oil Cua 85 10 5 Gr

18 H11 Kerosenea Cua 38 50 8 Al

19 HCHCr Kerosenea Cu 57 100 5 No

20 HCHCr Kerosene Cu 85 10 8 Gr

21 HCHCr Refined mineral oil Cu 38 50 2 Al

22 HCHCr Kerosene W 85 50 2 No

23 HCHCr Refined mineral oil W 38 100 5 Gr

24 HCHCr Kerosenea W 57 10 8 Al

25 HCHCr Refined mineral oil Cua 38 10 8 No

26 HCHCr Kerosenea Cua 57 50 2 Gr

27 HCHCr Kerosene Cua 85 100 5 Al

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2.3 Measuring and test equipment

The MRR was measured using a weighing machine withleast count as 0.001 g. The MRR of each sample wascalculated using the weight difference of workpiece beforeand after each trial using Eq. 1.

MRR ¼ 1; 000 wi � wfð Þr� t

mm3=min ð1Þ

where wi=initial weight of the workpiece material (ingrams), wf=final weight (after experimentation) of work-piece material (in grams), ρ=density of workpiece in gramsper cubic centimeter, and t=machining time in minutes.

TWR was calculated using Eq. 2 given by

TWR ¼ A� L

tmm3=min ð2Þ

where A is front area of the electrode, L is loss in length ofthe electrode, and t is machining time in minutes.

Surface roughness was measured in terms of roughnessaverage Ra, using the Perthometer (Make: Mahr, M4Pi,Germany, Stylus type contact measurement, cutoff lengthused 0.8 mm). For each sample, SR was measured at fourlocations at the center of the machined region and wasaveraged for further analysis.

3 Results and discussion

3.1 Example of ANOVA for a dummy-treated factor

The two-level factors accommodated in L27, which isprimarily a three-level array, needed a modified varianceanalysis method. In this analysis method, the difference in

the responses for the repeated level serves as an additionalsource of error. The sum of squares for factors B and Cwhich were dummy treated was calculated using themodified Eq. 3 for sum of squares (SS) that takes care ofthis additional error component.

SSC ¼ C1 þ C#1

� �2

nC1 þ nC1#þ C2

2

nC2þ C2

3

nC3� T 2

Nð3Þ

where SSe is the sum of squares due to factor C, C1 is thesum of responses when factor C is set at first level and nC1is the number of tests when factor C is at the first level andso on. T is the sum of all responses and N is the number oftotal tests (27 for L27 OA)

The symbols for C1 and C#1 both indicate the same test

condition for factor C. The random error due to therepetition of factor C at level 1 was calculated in the samemanner as a two-level factor and is given in Eq. 4. Thedenominator of the fraction is the total number of testsinvolved in the comparison [24].

SSe ¼C1 � C#

1

� �2

nC1 þ nC1#ð4Þ

where SSe is the sum of squares due to the error thatappears due to variation of responses using factor C at firstlevel and its corresponding dummy level.

3.2 Analysis of variance for responses

The effect of control factors, namely, (a) workpiece, (b)dielectric fluid, and (c) electrode material and someprocess parameters, namely, (d) pulse on time, (e) pulseoff time, (f) current, and (g) suspended powder along withsome of their interactions were evaluated using ANOVAand factorial design analysis. The MRR, TWR, and SR foreach of the 27 treatment conditions with one repetition aregiven in Table 5. The ANOVA results for mean MRR,TWR, and SR are given in Table 6. The table also showsthe realized significance levels, associated with the F testsfor each source of variation. The principle of the F test isthat the larger the F value for a particular parameter,greater is its effect on the process performance. The

Table 4 Chemical composition of electrode materials

Electrode % composition

W Cu Ni Ti

Tungsten–copper 80.4 19.46 0.121 0.014

Copper – 99.9 0.045 0.029

Table 3 Chemical composition of workpiece materials

Workpiece % composition

Fe C Si Mn P S Cr Mo Ni Co Cu Ti V W

EN31 92.3 0.3 1.0 0.4 0.04 – 5.0 – – – – – 1.0 –

H11 91.7 0.39 1.0 0.5 0.03 0.02 4.75 1.1 – 0.01 0.01 – 0.5 –

HCHCr 83.5 1.6 0.5 0.55 0.03 0.03 13.3 0.05 0.07 0.01 0.05 0.02 – 0.02

Int J Adv Manuf Technol (2012) 61:537–548 541

purpose of the ANOVA and significant factors plot was toidentify the important parameters in estimating the fourresponses. This analysis helped to identify the best set of

predictors based on their F value for estimating theresponse value.

3.2.1 MRR

A review of the results for mean MRR after ANOVAreveals that current, pulse on time, workpiece material, andpulse off time significantly affected the mean MRR. One ofthe interactions between the electrode material and sus-pended powder (F value 47.16) was also observed to besignificant. The other factors, electrode material, dielectric,and suspended powder did not have any significant effecton the MRR. The main effects and interaction plot for theMRR are shown in Fig. 3a, b. The plots present thevariation of MRR with the change in input parameters. Ascan be seen, MRR increased with an increase in the currentand pulse on time. EN31 and HCHCr exhibited highest andthe lowest MRR, respectively. Lower MRR was observedwith increased pulse off time. Also, the interaction betweenthe electrode material and suspended powder was observedto be significant. The electrode material independently hadno effect on MRR but in combination with the suspendedpowder affected the MRR significantly. MRR is a “higherthe better” response meaning thereby those levels of thesignificant factors should be chosen that resulted in highestMRR. Pulse on and off time and current were identified assignificant factors and highest MRR was observed whencurrent and pulse on time was set at level 3 and pulse offtime was set at level 1 (see Fig. 3a). The significantinteraction between electrode material and powder was alsoselected the same way using Fig. 3b. The best levels for thesignificant factors and interaction are given in Table 7. Forthe plot for interaction between the electrode and thepowder, the maximum MRR was observed for trials wherewith W–Cu electrode and no powder was mixed in thedielectric. However, one of the key objectives of thisexperiment was to improve surface properties usingPMEDM. The next best combination levels for electrodeand powder (Cu electrode and Al powder) were thereforeselected. With this combination, the MRR was marginallylower than with the trials with no powder. MRR being a

Table 5 Results for MRR, TWR, and SR (two repetitions)

Trial no. MRR (mm3/min) TWR (mm3/min) SR (μm)

R-I R-II R-I R-II R-I R-II

1 5.16 6.23 0.22 0.21 5.26 4.88

2 13.11 13.38 1.12 1.13 7.27 7.24

3 27.29 26.09 1.95 1.72 10.3 10.2

4 28.31 27.68 2.19 2.10 8.12 7.90

5 0.264 1.32 0.30 0.32 1.86 1.87

6 12.85 14.83 0.72 0.74 6.85 6.12

7 13.25 13.38 1.29 1.33 8.82 7.25

8 27.55 27.42 1.50 1.61 9.54 9.49

9 3.88 2.79 0.20 0.21 4.59 4.31

10 17.09 18.42 1.74 1.82 7.90 7.83

11 1.939 1.69 0.33 0.34 4.92 5.11

12 9.69 8.42 0.77 0.79 5.32 6.59

13 14.18 13.45 1.05 1.06 5.23 4.48

14 12.25 14.61 1.43 1.48 6.86 6.42

15 3.77 4.00 0.52 0.53 6.39 6.17

16 4.73 4.61 1.12 1.13 5.70 5.25

17 8.36 6.06 1.21 1.23 6.09 6.11

18 28.73 28.97 1.91 1.91 7.96 8.04

19 18.19 19.6 1.73 1.74 7.58 8.58

20 2.51 1.08 1.45 1.46 3.31 4.61

21 3.77 3.95 0.38 0.39 4.78 4.47

22 5.39 4.00 0.20 0.22 5.52 4.72

23 19.57 18.89 0.80 0.77 6.70 6.52

24 1.75 1.88 1.03 1.04 7.76 7.91

25 11.49 10.65 2.09 2.09 5.35 5.54

26 0.549 0.53 0.26 0.25 1.82 2.05

27 15.09 14.42 1.35 1.36 7.57 7.19

R-I response-I, R-II response-II, MRR material removal rate, TWR toolwear rate, SR surface finish

Fig. 2 Ground workpiece andtool used for experimentation aworkpiece (size 100×50×10 mm), b Cu tool, c W–Cu tool(electrode size, Φ 20 mm,50 mm length)

542 Int J Adv Manuf Technol (2012) 61:537–548

higher the better response can be obtained by setting thesignificant factors at their most appropriate levels and isgiven in Eq. 5.

MRR ¼ workpieceþ pulse on3 þ pulse of f 1

þ current3 þ electrode1 or 3 � powder3ð Þ� 4T ð5Þ

3.2.2 TWR

The results for TWR were analyzed using ANOVA foridentifying the significant factors. The ANOVA for themean TWR is given in Table 6. Current and powder wereidentified as the two factors that affect TWR. All the otherfactors and the interactions were observed to be insignifi-cant. The main effects plot for TWR is shown in Fig. 3c, dwhich shows that TWR increases with an increase incurrent and is lowered with mixing of powder in thedielectric. Powder mixing in dielectric lowers the TWRsignificantly. TWR with tungsten–copper electrode is lowas compared to copper electrode. None of the interactionswere observed to be significant.

3.2.3 Surface roughness

The result for surface roughness with two repetitions in thecenter of the workpiece is shown in Table 5. The results ofANOVA for the mean surface roughness are shown inTable 6. Current, pulse on time, suspended powder,workpiece material, and electrode material have a significanteffect on surface roughness. The type of dielectric and pulse

off time had no effect on SR of the machined surface. All thethree interactions between workpiece material, electrodematerial, and powder material had significant effect on thesurface finish of the machined surface. The main effect andinteraction plots for the significant factors that affect thesurface roughness are shown in Fig. 3e, f. The plots show thevariation in surface roughness with the change in inputparameters. In the plots, the x-axis shows the parametersetting of each factor and y-axis shows the resultant surfaceroughness. Unlike MRR, surface roughness is a “lower thebest” response and the levels of significant factors whichresulted in the lowest SR were selected from Fig. 3e, f. Fromthe plots, it was observed that the surface roughnessincreased with an increase in current and pulse on time.The surface roughness improved with graphite powdersuspended in the dielectric. EN31 was observed to have thebest surface finish among the three workpiece materials usedin this study. The results show that lowest roughness valuewas observed when HCHCr was machined with tungsten–copper electrode at a pulse on time of 10 μs and current setat 2 amp with graphite-mixed powder in dielectric. Accord-ingly, the best levels of SR are depicted in Table 7. Theestimated surface roughness when all the significant factorsare at their best levels for minimum SR is given in Eq. 6.

SR ¼ workpieceþ pulseon1 þ current1 þ powder2þ workpiece� electrodeð Þ þ workpiece� powderð Þþ electrode1 or 3 � powder3ð Þ � 6T ð6Þ

where SR is the estimated value of the surfaceroughness in micrometer when significant factors and

Table 6 ANOVA table for MRR, TWR, and SR

Source dof MRR TWR SR

Variance F (calculated) Variance F (calculated) Variance F (calculated)

Workpiece, A 2 87.45 33.50 0.02 0.95 2.76 91.02

Dielectric, B 1 3.32 1.27 0.07 2.56 0.06 1.92

Electrode, C 1 2.41 0.92 0.32 12.54 0.92 30.26

Pulse off, D 2 42.49 16.28 0.03 1.07 0.06 1.92

Pulse on, E 2 232.43 89.05 0.27 10.59 12.39 408.82

Current, F 2 487.60 186.82 3.82 149.06 23.18 764.81

Powder, G 2 29.50 11.30 0.34 13.39 4.58 150.97

A×C 2 9.14 3.50 0.26 10.29 5.63 185.74

A×G 4 13.18 5.05 0.02 0.74 0.94 31.11

C×G 2 123.09 47.16 0.04 1.37 0.84 27.83

Error 6 2.61 0.03 0.03

Total 26

MRR material removal rate, TWR tool wear rate, SR surface finish

Int J Adv Manuf Technol (2012) 61:537–548 543

interactions are set at their lowest mean values. T is themean of all responses.

3.3 Further analysis

PMEDM is now a widely used machining process tofacilitate complex machining problems in difficult-to-machine materials with improved surface integrity. Someof the reasons for using PMEDM are (a) no physical

contact between the electrode and the workpiece, (b)accurate and precise machining of hardened workpieceswith complicated internal geometries, (c) negligible cuttingforces, and (d) burr free machined surface. The responseobjectives after an EDM process could vary dependingupon the requirements of a particular application. Maxi-mizing the MRR could be the most desirable objective in arough machining process and minimizing the SR could bethe most important objective in a finishing process. The

Mea

n o

f M

eans

HCHCrH11EN31

15

10

5

Transformer oilKerosene WCu

855738

15

10

5

1005010 852

NoGrAl

15

10

5

Workpiece Dielectric Electrode

Pulse off Pulse on Current

Powder

(a)

16

12

8

NoGrAl

WCu

16

12

8

HCHCrH11EN31

16

12

8

Workpiece

Electrode

Powder

EN31H11HCHCr

Workpiece

CuW

Electrode

AlGrNo

Powder

(b)

HC HC rH11EN31

1.5

1.0

0.5

Transformer oilKerosene WC u

855738

1.5

1.0

0.5

1005010 852

NoGrA l

1.5

1.0

0.5

Workpiece

Mea

n o

f M

ean

s

Dielectric Electrode

Pulse off Pulse on C urrent

Pow der

(c)

1.2

0.9

0.6

NoGrAl

WCu

1.2

0.9

0.6

HCHCrH11EN31

1.2

0.9

0.6

Workpiece

Electrode

Powder

EN31H11HCHCr

Workpiece

CuW

Electrode

AlGrNo

Powder

(d)

HCHCrH11EN31

7

6

5

Transformer oilKerosene WCu

855738

7

6

5

1005010 852

NoGrA l

7

6

5

Workpiece

Mea

n o

f M

eans

Dielectric Electrode

Pulse off Pulse on Current

Powder

(e)

7.4

6.2

5.0

NoGrAl

WCu

7.4

6.2

5.0

HCHCrH11EN31

7.4

6.2

5.0

Workpiece

Electrode

Powder

EN31H11HCHCr

Workpiece

CuW

Electrode

AlGrNo

Powder

(f)

Fig. 3 Main effect and interaction plots for MRR (a, b), TWR (c, d), and SR (e, f), respectively

544 Int J Adv Manuf Technol (2012) 61:537–548

process parameters that may result in achievement of any ofthese objectives would need to be identified for each material.The following section describes the methodology for achiev-ing these widely contrasting objectives and has been classifiedinto two types of machining processes, namely, (a) roughmachining with an objective to maximize the MRR and (b)finish machining with an objective to minimize SR.

3.3.1 Rough machining with PMEDM process

When the objective is to maximize the material removalduring PMEDM, the process parameter settings may bechosen using Eq. 5. The calculated mean values at eachlevel setting of all the significant factors taken from Table 2for each response is given in Table 8. By substituting themean values of MRR, TWR, and SR in Eq. 5 at the chosenlevel, the estimated value of each response for the threematerials can be calculated.

For example, optimal MRR in cubic millimeters perminute for EN31 using Eq. 5 will be obtained by settingpulse on time and current at its maximum level (level 3 inthis case) and pulse off time by setting at its minimum level(at level 1) with Cu electrode (level 1) and alumium powder(level 3). The mean values at these settings are (fromTable 8) EN31, 14.711; pulse off at 38 μs, 13.963; pulse onat 100 μs, 16.158; current at 8 amp, 17.432; and thecombined effect of Cu electrode and alumium powder,14.425. To obtain the best estimate for the mean forinteraction between two factors, the trials that included thattreatment conditions were averaged. Referring to Fig. 3bfor interaction of factors, MRR is a “higher the better”characteristic, so copper electrode with aluminum powderElectrode1 or 3 � Powder3 would give the maximum MRRin the experiment. The mean MRR obtained for theinteraction between electrode material and suspendedpowder was calculated as 15.65 mm3/min.

MRR ¼ 14:711 EN31ð Þ þ 16:158 pulse on3ð Þ þ 13:963 pulse of f 1ð Þ þ 17:432 current3ð Þ þ 14:425 electrode1 or 3 � powder3ð Þ � 4T

¼ 30:83 mm3=min

The mean TWR and SR can also be obtained using thesame methodology. The mean MRR, TWR, and SR thusobtained by substituting their mean value in Eq. 5 are givenin Table 9. The comparative values obtained for each of thethree responses shows that the highest MRR is exhibited byEN31 material followed by H11 and HCHCr. Correspond-

ingly, EN31 also had the highest roughness value. TWRcalculated for the three materials showed, however, similarresults. The combination of copper electrode with alumi-num powder mixed with dielectric maximizes the MRR. Nointeraction other than one between electrode and powderwas observed to be significant.

Table 7 Significant factors and their selected levels for rough and finish machining

Factors and interactions, symbol (unit) Rough machining MRRmaximized Finish machining SRminimized

Significance Best level (value) Significance Best level

Workpiece, A √ EN31 or H11 or HCHCr √ EN31 or H11 or HCHCr

Dielectric, B × × × ×

Electrode, C × × × ×

Pulse off (μs), D √ Level 1 (38 μs) × ×

Pulse on (μs), E √ Level 3 (100 μs) √ Level 1 (10 μs)

Current (amp), F √ Level 3 (8 amp) √ Level 1 (2 amp)

Powder, G × × √ Level 2 (graphite)

Workpiece and electrode, A×C × × √ EN31×W–Cu

H11×W–Cu

HCHCr×W–Cu

Workpiece and suspended powder, A×G × × √ EN31×graphite

H11× graphite

HCHCr×graphite

Electrode and suspended powder, C×G √ C1 or 3×G3 (Cu×Al) √ W–Cu×graphite (for EN31, H11, HCHCr)

MRR material removal rate, SR surface finish

Int J Adv Manuf Technol (2012) 61:537–548 545

3.3.2 Finish machining with PMEDM process

When the objective is to minimize SR, the processparameter settings may be chosen using Eq. 6. Bysubstituting the mean values of SR, MRR, and TWR inthis equation at the chosen level given in Table 7, the valuesof each response for the three materials can be calculated.The best settings for minimizing SR are current and pulseon time at their lowest level (2 amp and 10 μs) and graphitepowder with W–Cu electrode for EN31, H11, and HCHCr(see Table 7). The mean SR for EN31, H11, and HCHCrobtained by following the same methodology as describedin Section 3.3.1. The mean MRR, TWR, and SR mathe-matically obtained by substituting these values in Eq. 6 aregiven in Table 9. These calculations for MRR, hereafterdescribed as first iteration, showed negative values forH11 and HCHCr indicating no cut is feasible with the usedparameter setting. Similarly, some TWR and SR valueswere negative with these settings indicating no machined

surface when the current is set at 2 amp and pulse on timeis set at 10 μs. A confirmation experiment was conductedto validate these results. The conformation experimentresults matched with the mathematical findings. As asecond iteration to get optimal results, the current settingwas increased from 2 to 5 amp to produce a cut. The meanMRR, TWR, and SR with this change calculated usingEq. 6 are also given in Table 9 as results of seconditeration. EN31 exhibited a higher MRR with an SR of3.80 μm with small tool wear. This setting has beentreated as optimal for EN31. However, the spark producedwas still unstable and little or no cut was made on H11 andHCHCr. As a third iteration, both current and pulse ontime were increased to 5 amp and 50 μs, respectively, andthe three responses were recalculated using Eq. 6. Withthese settings, an optimal result for both HCHCr and H11was feasible. HCHCr exhibited the smallest MRR with aSR of 2.43 μm. H11 had higher MRR (7.32 mm3/min)with an SR value of 4.16 μm.

Table 8 Mean values of significant factors at their best level for rough and finish machining

Rough machining

For MRR

Workpiece Pulse on3 Pulse off1 Current3 Electrode1 or 3×powder3 T

EN 31 14.711 16.158 13.963 17.432 14.425 (electrode1 or 3 correspondsto factor and its dummy level)

11.4611H11 11.711

HCHCr 8.517

For TWR

EN 31 1.0497 1.2667 1.1123 1.6971 1.08 (electrode1 or 3 correspondsto factor and its dummy level)

1.0711H11 1.1326

HCHCr 1.0362

For SR

EN 31 6.772 7.404 6.179 7.504 6.7776 (electrode1 or 3 correspondsto factor and its dummy level)

6.2263H11 6.242

HCHCr 5.665

Finish machining

For MRR

Workpiece Pulse on1, 2 Current1, 2 Powder2 WP×Ele2 WP×Pow2 Ele2×Pow2 T

EN 31 14.711 (1) 6.065 (1) 3.255 9.505 14.209 13.84067 11.15067 11.4611H11 11.711 (2) 12.170 (2) 13.707 10.3767 7.4848

HCHCr 8.517 8.58 7.1881

For TWR

EN 31 1.0497 (1) 0.9317 (1) 0.3974 0.9463 1.0617 0.9967 0.85 1.0711H11 1.1326 (2) 1.0201 (2) 1.1239 1.0117 1.0033

HCHCr 1.0362 0.6767 0.83167

For SR

EN 31 6.772 (1) 5.058 (1) 4.425 5.431 5.45 6.2116 5.038 6.2263H11 6.242 (2) 6.217 (2) 6.749 5.925 5.9183

HCHCr 5.665 6.5217 4.1683

(1) and (2) for next level values used during iterations as depicted in Table 9

Ai factor A at level ith and so on, MRR material removal rate, TWR tool wear rate, SR surface finish

546 Int J Adv Manuf Technol (2012) 61:537–548

From the above discussion, it can be concluded thatEN31 can be cut with good surface finish even at lowcurrent and pulse on settings. However, it is not possible tomachine H11 and HCHCr at these settings. HCHCrexhibited the lowest MRR and correspondingly best surfacefinish among the three materials studied in this experiment.The minimum settings of current and pulse on time forinitiating a cut in H11 and HCHCr are 5 amp and 50 μsprovided the other parameters are set in accordance withEq. 6. Graphite powder and tungsten electrode were mostsuitable combination for improving the surface finish ofEN31 and H11. Copper electrode with graphite powderworked the best for HCHCr. All the obtained roughnessvalues were above 1 μm Ra which indicate that althoughpowder does have a significant effect on improving thesurface properties [25], it may not be useful in achievingsuperior surface finish (less than 0.8 μm Ra) especially inthe boundary conditions used in this experimental setup.Additional factors may need to be studied to improve thefinish further.

4 Conclusion

The study was undertaken to identify appropriate processparameter settings for rough and finish machining of

HCHCr, H11, and EN31 material for MRR, TWR, andSR. The MRR was observed to be dependent upon pulseoff and on time and current. The interaction between toolmaterial and suspended powder was observed to besignificant. The electrode material independently had noeffect on MRR but in combination with the suspendedpowder affected the MRR significantly. On the other hand,SR was significantly affected by pulse on time, current, andpowder and the combined effect of workpiece, powder, andelectrode. EN31 exhibited maximum MRR as compared tothe other two materials for similar process settings. Copperelectrode used with aluminum powder suspended in thedielectric maximized the MRR. Graphite powder resulted ina lower MRR but improved surface finish. HCHCr requiredhigher current and pulse on settings for initiating amachining cut and works best in combination with copperelectrode and graphite powder for improved finish. TheMRR for H11 was lower than EN31 but significantlyhigher than HCHCr under similar process conditions. Theresearchers may use this methodology to establish processparameters in PMEDM process for rough or finishmachining of die steels.

Acknowledgments Authors sincerely acknowledge the Departmentof Science and Technology (DST), New Delhi for the financialsupport received through the project.

Table 9 Optimum value of the calculated responses for rough and finish machining

Workpiece Rough machining for maximizing MRR along with corresponding TWR and SRResponse ¼ workpieceþ pulse on3 þ pulse of f 1þ current3 þ electrode1 or 3 � powder3ð Þ � 4T

MRRmaximized (mm3/min) TWR (mm3/min) SR (μm) Remarks

EN31 30.83 1.92 9.631 Levels at their best for maximizing MRRH11 27.83 2.00 9.101

HCHCr 24.64 1.91 8.524

Workpiece Finish machining for minimizing SR along with corresponding MRR and TWRResponse ¼ workpieceþ pulseon1 þ current1 þ powder2þ workpiece� electrodeð Þ þ workpiece�ð powderÞ þelectrode1 or 3 � powder3ð Þ � 6T

Iteration MRR (mm3/min) TWR (mm3/min) SRminimized (μm) Remarks

EN31 1st iteration 3.95 −0.19 1.03 Levels set as above additiveequation

2nd iteration (optimized) 14.40 0.53 3.80 Current increased from 2 to 5 amp

H11 1st iteration −9.24 −0.15 0.68 Levels set as above additiveequation

2nd iteration 1.22 0.57 3.00 Current increased from 2 to 5 amp

3rd iteration (optimized) 7.32 0.66 4.16 Current and pulse on time increasedto 5 amp and 50 μs

HCHCr 1st iteration −14.52 −0.75 −1.05 Levels set as above additiveequation

2nd iteration −4.07 −0.03 1.27 Current increased from 2 to 5 amp

3rd iteration (optimized) 2.03 0.1 2.43 Current and pulse on time increasedto 5 amp and 50 μs

MRR material removal rate, TWR tool wear rate, SR surface finish

Int J Adv Manuf Technol (2012) 61:537–548 547

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