OPTIMIZATION OF PROCESS PARAMETERS IN MICRO-WIRE ELECTRICAL DISCHARGE MACHINING

(1)

OPTIMIZATION OF PROCESS PARAMETERS

IN MICRO-WIRE ELECTRICAL DISCHARGE

MACHINING

1

_{Mukesh Kumar Sharma}

1

_{Assistant Professor}

1

_{Department of Mechanical Engineering}

1

_{TempleCity Institute of Technology and Engineering, Bhubaneswar, India}

Abstract: Micro wire EDM is a trending innovation in the field of Micro-machining to create complex smaller scale items. It is an intricate procedure including the diverse procedure parameters. In the present examination an enhancement of micro wire EDM has been completed utilizing Grey Taguchi technique. The parameters included are voltage, capacitance, feed rate and wire speed.MRR and kerf width are taken as the response criteria. The experiment has been done in multi-process Micro-Wire EDM machine. Wire electrical discharge machining process is an exceptionally perplexing, time changing and stochastic procedure. This is utilized in the fields of kicks the bucket, molds ; accuracy assembling and form cutting and so forth any mind boggling shape can be produced with high evaluation of precision and surface complete the process of utilizing CNC WEDM. The yield of the procedure is influenced by huge number of informatio n factors. Henceforth an appropriate determination of information factors for the wire electrical discharge machining (WEDM) process relies vigorously upon the administrator's innovation and experience. WEDM is widely utilized in machining of conductive materials when accuracy is of prime significance. Unpleasant cutting activity in wire EDM is exceptionally testing one since progress of more than one execution measures viz. Metal removal rate (MRR), surface finish and cutting width (kerf) are of prime significance. This paper proposes ideal parameter setting. Utilizing Taguchi's parameter plan, noteworthy machining parameters influencing the presentation measures are distinguished as pulse peak current, pulse on time, and duty factor. The impact of each control factor on the presentation measure is examined independently utilizing the plots of sign to the plots of signal to noise ratio. The investigation shows that the WEDM procedure parameters can be balanced in order to accomplish better metal removal rate, surface finish, electrode wear rate.

IndexTerms – EDM, WEDM, Taguchi Method, OA

I. INTRODUCTION

Electrical discharge machining (EDM) is one of the most extensively used non- conventional, thermo-electric metal removal process which encodes material from the work place by a series of discrete spark between a work and a tool electrode immersed in a liquid dielectric medium. Electrical energy is used directly to cut the material in final shape. Melting and vaporization takes place by theses electrical discharges. The minute a mounts of the work material is then ejected and flushed away by the dielectric medium. The sparks occur at high frequency which continuously and effectively removes the work prices material by melting and evaporation. To initiate the machine process electrode and work piece are separated by a small gap known as ‘spark gap’ which results into a pulsed discharge causing the removal of material. The dielectric acts as a deionizing medium between two electrodes and its flow helps in vacating the debris to assure optimal conditions for spark generation. In micro-wire EDM operation the work piece metal is cut with a special metal wire electrode that is programmed to travel along a definite path. Spark discharges and generated between a small wire electrode and a work piece to produce complex two dimensional and three-dimensional shapes according to a NC path. A very thin wire in the range of 0.02 to 0.3 mm in diameter as an electrode is used in the wire-cut EDM. It machines a work piece with Electrical discharge machining (EDM) is one of the most extensively used non- conventional, thermo-electric metal removal process which encodes material from the work place by a series of discrete spark.The CNC system of wire EDM has the duty to provide the function of geometry trajectory, sequential control, pulse generator control, wire feed and wire tension control and machining process control. The wire transport system of a wire EDM guarantees a smooth wire transport and constant tension of wire. The machine consists of a work piece contour movement control unit, work piece mounting table and wire driven part which ensures accurate movement of the wire oat constant tension. The purpose of WEDM is to achieve better stability and higher productivity, higher machining rate with accuracy. A large number of variables are involved in the process.

(2)

1.iiiElectrodeiweariisinegligible. 2.iiiFormingielectrodeitoiproduceishapeiisinotirequired. 3.iiiMachinedisurfaceiareiveryismooth. 4.iiiDimensionaliandiGeometricaliTolerancesiareiveryitight. 5.iiiStraightiholeiproductioniisipossibleiwithihigheriprecision. 6.iiiRelativeitoleranceibetweenipunchiandidieiisimuchihigheriandidieilifeiisiextended. 7.iiiTheimachineicanibeioperatediunattendediforilongitimeiatihighirate. 8.iiiNoispecialiskillsiareirequireditoirunitheimachine. 9.iiiAnyielectricallyiconductiveimaterialicanibeimachinediirrespectiveiofiitsihardness. 10.iThisiprocessiallowsitheishapingiandimachiningioficomplexistructureiwithihighimachiningiaccuracyiiniorderiofimicron. TABLE-I:iPROCESSiPARAMETERSiOFiMICRO-WIREiEDMiPROCESS

S.No. Parameters Range

1. Frequency _0-200KHz 2. Pulseiwidth 1-10i s 3. Gap%iofiVoltage 60-100% 4. Gain 0-100 5. Pulseipeakicurrant 40A 6. OutputiVoltage 60-250V 7. Dwellitime 0.205 8. Polarity +/- 9. Holeidiameter 0.05-1mm 10. Spindleispeed 100-1000irpm MachineiParameters: 1.iiiTableifeed. 2.iiiPulseionitime. 3.iiiPulseioffitime. 4.iiiFlushing WireiParameters 1.iiiMaterialiofiwire. 2.iiiDiameteriofiwire. 3.iiiWireispeed. 4.iiiWireitension Figurei1:iWireiElectricaliDischargeiMachine OPTIMIZATIONiTECHNIQUES

Taguchiimethod:iTaguchiimethodiisianiefficientitooliforitheidesigniofihighiqualityimanufacturingisystem. Dr.G.iTaguchi,aiJapaneseiengineerihasidevelopediaimethodibasedioniorthogonaliarraysi(OA).

(3)

eeksitoiminimizeitheinoiseibecauseitheieliminationiofinoiseifactoriisiimpractical.iThisimethodiprovidesimuchireducediiivarianceiiifo riiitheiiiexperimentiiiwithiiioptimumiisettingiii

ofiprocessicontroliparameters.Taguchiiphilosophyiisibasedioniintegr-ationiofidesigniofiexperiments(DOE)iwithiparametricioptimizationiofiprocessesitoigetitheidesirediresults. AithreeistageidesignioperationiisidoneiiniTaguchiimethoditoidetermineitheitargetivalueiandtolerancefor relevantiparametersiinitheiproduct.iTheithreeistageidesignsiare-

1.iiiSystemidesign 2.iiiParameteridesign 3.iiiToleranceidesign

Systemidesign:iaiprototypeofitheiproductiisicreatediusingiscientificiandiengineeringiprinciple.iThisiisidoneion the basisiofifunctionalirequirement.

Parameteridesign:iTaguchiidefinesiiiiaiperformanceimeasureiknowniasitheisignalitoinoiseiratio(S/N).Theitargetiofithei parameteridesigniisitoifinditheioptimalisettingiofitheiproductianditheiprocessiparametersisoithatitheiperformanceivariabilityiisiminimi zed.iSelectioniofiparametersiisidoneitoimaximizeitheiS/Niratio.iSignalirepresentsitheisquareiofitheimeanivalueiofithei

qualityicharacteristiciwhileinoiseiisitheimeasureiofitheivariabilityiofiicharacteristics.

ToleranceiDesign:iAfteritheisystemidesignianditheiparameteridesignitoleranceidesigniisidoneiinitheithirdistage.inithisistepiwe isetitolerancesiinitheirangeiofiadmissibleivaluesiarounditheitargetivalueiofitheicontroliparameters.iTaguchi

signalitoinoiseiratioiareitheilogarithmicifunctionsiofidesiredioutput.Itiisitakeniasitheiobjectiveifunctioniforioptimization. Orthogonaliarrayiprovidesiaisetiofiwellibalancediexperiments.S/Niratioiisitheiratioiofitheimeanitoistandardideviation.Herei meanirefersitoisignaliandistandardideviationirefersitoinoise.theiratioidependsionitheiqualityicharacteristiciofitheiproduct/process itoibe

ioptimized.theistandardiS/Niratiosiareiasifollows iiiiNominaliisitheibest

iiiiLoweritheibetter iiiiHigheritheibetter

GRAYiBASEDiTAGUCHIiMETHOD

Theimultipleiperformanceicharacteristicsiproblems,theitaguchiimethodiisicouplediwithigreyirelationalianalysis.GreyibasediTaguch iiisiwidelyiusediinidifferentifieldiofiengineeringitoisolveimultiiresponsei optimizationiproblem. GreyiRelationaliAnalysis:iInigreyirelationalianalysisiexperimentalidataiareifirstinormalizediinitheirangeiofi0itoi1.Thisiprocessi isiknowniasigreyirelationaligeneration.Greyirelationalicoefficientiareicalculateditoirepresentitheicorrelationibetweeniidealiandi theiactualinormalizedidata. GreyiRelationaliGeneration:iAccordingitoitheinor malizationithreeitypesiofidatainormalizationiareid one I.iiiiLoweritheibetteri(LB)

II.iiiiHigheritheibetteri(HB) III.iiiiNominaliisitheibesti(NB)i ForiLBicriteria: 𝑥𝑖(𝑘) = max 𝑦𝑖(𝑘)−𝑦𝑖(𝑘) max 𝑦𝑖(𝑘)−min 𝑦𝑖(𝑘) (1) Forihigheritheibetteri(HB)icriteria, 𝑥𝑖(𝑘) = 𝑦_𝑖(𝑘)−min 𝑦_𝑖(𝑘) max 𝑦_𝑖(𝑘)−min 𝑦𝑖(𝑘) (2) Wherei_xii(k)iisitheivalueiafteritheiGreyirelationaligeneration,imini_yii(k)iisitheismallestivalueiofi_yi (k)iforitheikthiresponseiandimaxi_yii(k)iisitheilargestivalueiofi_yii(k)iforitheikthiresponse.

𝜉𝑖(𝑘) =

∆_𝑚𝑖𝑛+𝜓∆𝑚𝑎𝑥

∆_𝑜𝑖(𝑘)+𝜓∆_𝑚𝑎𝑥 (3)

Aniidealisequenceiisi_x0(k)i(k=i1,i2,i3...,i25)iforitheiresponses.iTheidefinitioniofiGreyirelationaligradeiinitheicourseiofiGreyirelatio nalianalysisiisitoirevealitheidegreeiofirelationibetweenithei25isequencesi_[x0(k)iandi_xi(k),ii=1,i2,i3...,]

ᵧ_𝑖=1

𝑛∑ 𝜉𝑖(𝑘) 𝑛

𝑘=1 (4)

whereini=inumberiofiprocessiresponses.iForicalculatingitheiS/Niratio,ihavingicriteriailargeritheibetterieicanibeiused

−10 𝑙𝑜𝑔[1 𝑛∑ 1 𝑦_𝑖2] 𝑛 𝑖=1

AccordingitoitheiTaguchiidesignimethodi_L9iOrthogonaliarrayiwasichoseniforitheioptimizationiofitheiprocess.iFouricontro lifactorsiwereichoseniatithreeilevels-i

(4)

III. Wireifeed(C) IV. Wireispeed(D)

iTwoiresponseiparametersimeasurediwere-

I.iiiiiiKerf II.iiiMRR MRRicanibeicalculatediby,i MRRi=iK×H×FR×ρi,i WhereiK=Kerfiwidth,i FR=wireifeed, iH=sheetithicknessi(0.5mm),i ρi=densityiofistainlessisteeli(=8000ikg/m3) . TableiI.iiMachiningiparametersianditheirilevels

SYMBOL PARAMETER UNIT LEVEL-1 LEVEL-2 LEVEL-3

A Voltage Volts 80 100 110

B Capacitance Microifarad 0.00001 0.001 0.1

C WireiFeed Micron/sec ei6.0 ei8.0 ei10.0

D Wireispeed 15% 20% 25% TableiII.iiExperimentaliResults Runiorder Kerf MRR 1 0.50 0.105 2 0.60 0.168 3 0.65 0.124 4 0.50 0.145 5 0.85 0.240 6 0.82 0.165 7 0.65 0.178 8 0.75 0.126 9 0.74 0.195

(5)

DATAiANALYSIS:

Kerf and MRR are the output values from the Grey Ralation.

TableiIV.iGreyiRelationaliGeneration Runiorder Kerf MRR IdealiSequence 1 1 1 0.815 0 2 0.444 0.454 3 0.629 0.659 4 1 0.181 5 0.074 1 6 0 0.303 7 0.740 0.591 8 0.444 0.136 9 0.370 0492

CalculationiofiGreyirelationiCoefficient

𝜉𝑖(𝑘) =

∆𝑚𝑖𝑛+ 𝜓∆𝑚𝑎𝑥

(6)

Main Effects plot for S/N ratios

Optimal setting for maximizing MRR

(7)

Main Effects plot for S/N ratios

Optimal setting for minimizing Kerf

Response table for S/N ratios Smaller is better LEVEL V C 𝑊𝑓 𝑊𝑠 1 3.75882 4.59397 2.84824 3.07617 2 2.951553. 2.47333 3.7146 2.98131 3 3.12976 2.77290 3.27736 3.77275 Delta 0.80735 2.12065 0.86667 0.78242 Rank 3 1 2 4 CONCLUSIONS

OptimizationiofimicroiwireiEDMiprocessionistainlessisteeliusingiTaguchiimethod-basediGreyianalysisiwasistudiediinithisipaper  WireiEDMiisiaicomplexiprocessihavingimanyinumbersiofifactorsiaffectingitheiprocess,ibutiforicurrentistudyithei

mainifactorsiconsiderediare:iVoltage,icapacitance,iwireifeediandiwireispeed.  TheieffectsiofitheseifactorsionikerfiandiMRRihaveibeenistudied.

 iForioptimizingitheiprocessivariablesiGrey-basediTaguchiimethodihasibeeniapplied.

 OptimumiiparameteriisettingsiiobtainiifromiiS/Niiratioiiplotiiareiivoltageii=ii90V,icapacitancei=i0.00001µ F,iwireifeedi10µm/s,iwireispeedi10%.

 Confirmatoryiexperimentihasibeeniperformediandifoundiaigoodiiagreementiibetweenipredictediandiexperimentaliv alue.  AccordingitoiMINITABianalysis,ioptimaliconditioniforiminimizingikerfiisiVi=i90ivolts,iCi=i0.00001iµF,iWFi=i8i µm/s,iandiWSi=i50%.  OptimaliconditionsiforimaximizingiMRRiisiVi=i110ivolts,iCi=i0.001iµF,iWFi=i10iµm/s,iandiWSi=i30% References

[1]iY.S.iLiao,iY.Y.iChuiandiM.T.iYan,iStudyiofiwireibreakingiprocessiandimonitoringiofiWEDM,iInternationaliJournaliofiMachineiTo olsi&iManufacture,i37i(1997)ipp.i555-567

[2]iR.E.Williams and K.P.Rajurkar,study of wire electrical discharged machine surface characteristics,Journal of Materials Processing Technology,28(1991) pp.127-138 AIJREASVOLUME 1,ISSUE 9(2016,SEPT)(ISSN2455-6300)

[3] S.S.Mohapatra,AmariPattnaik,Optimization of WEDM process parameters using Taguchi method,International Journal of Advanced Manufacturing Technology (2006)

[4]iP.JiRoss.iTaguchiiTechniquesiForiQualityiEngineering.iNewiYork,iMcGraw-Hill,1984i

[5]iY.SiLiaoi,iJ.T.Huang,iAistudyionitheimachiningiparameterioptimizationiofiWEDM,iJournaliofiMaterialiProcessingiTechnology,71(19 97)ipp.i487-493i

[6]iMohdiAmriiLajisi,iH.C.D.iMohdiRadzi,iTheiImplementationiofiTaguchiiMethodioniEDMiProcessiofiTungsteniCarbide,iEuropeaniJ ournaliofiScientificiResearchiISSNi1450-216XiVol.26iNo.4i(2009),ipp.609-617i I

[7]iC.L.Lin,iJ.L.lini&iT.C.Koi,OptimizationiofitheiEDMiprocessibasedionitheiOrthogonaliArrayiwithiFuzzyiLogiciandiGreyiRelationali AnalysisiMethod,iInternationaliJournaliofiAdvancedimanufacturingiTechnology,19(2002)ipp.i271