Multi-Parameter Analysis and Modeling of Surface Roughness in Electro Discharge Machining of AISI D2 Steel

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1 Iteratoal Joural of Scetfc & Egeerg Research, Volume 3, Issue 6, Jue-01 1 Mult-Parameter Aalyss ad Modelg of Surface Roughess Electro Dscharge Machg of AISI D Steel B B PATEL, K B RATHOD Abstract Whereas the effcecy of tradtoal cuttg processes s lmted by the mechacal propertes of the processed materal ad the complexty of the worpece geometry, electrcal dscharge machg (EDM) beg a thermal eroso process, s subject to o such costrats. Surface roughess (Ra) s a sgfcat upshot the maufacturg process ad t materalzes a major part the maufacturg system. It depeds o dfferet machg parameters ad ts predcto ad cotrol s a query to the researchers. Ths paper hghlghts the developmet of a comprehesve mathematcal model for correlatg the teractve ad hgher order flueces of varous electrcal dscharge machg parameters through respose surface methodology (RSM), utlzg relevat expermetal data as obtaed through expermetato of surface roughess. The adequaces of the above proposed model have bee tested through the aalyss of varace (ANOVA). Idex Terms Cetral composte desg, EDM, Surface roughess, Respose surface methodology. 1 INTRODUCTION Electrcal dscharge machg (EDM) s a o-tradtoal maufacturg process based o removg materal from a part by meas of a seres of repeated electrcal dscharges (created by electrc pulse geerators at short tervals) betwee a tool, called the electrode, ad the part beg mached the presece of a delectrc flud. At preset, EDM s a wdespread techque used dustry for hghprecso machg of all types of coductve materals [1]. The worg prcple s based o the thermo electrc eergy. The thermo electrc eergy ( form of spar) s created betwee a worpece ad a electrode submerged a delectrc flud wth coducto of electrc curret. The worpece ad the electrode are separated by a specfc small gap, the so called spar gap, ad pulsed dscharges occur ths gap flled wth a sulatg medum []. Durg machg, the dscharge eergy produces very hgh temperature at the pot of the spar o the surface of the worpece, ad removes the materal by meltg ad vaporzato. The top surface of worpece resoldfes ad cools subsequetly at very hgh rate. Ths process leads to the slghtly dmpled surface (.e. creasg surface roughess), whch facltates crac tato o the surface. After electrcal dscharge treatmet, hgh tesle resdual stresses ofte duce damage such as mcro-cracs or pholes the surface layer, reducg ts stregth. Y.H. Guu et al. [3] proved that AISI D steel coated by TN exhbted cosderably creased hardess, a better surface fsh, ad decreased superfcal tesle resdual stress, or added compressve resdual stress o the surface, creasg ther fatgue lmt. Y.H. Guu et al. [4] B B Patel s curretly Assstat Professor Saalchad Patel college of Egeerg, Vsagar, Ida, Emal: bbpatel.mech@spcevg.ac. K B Rathod curretly Assstat Professor Faculty of Egeerg Techology ad Research, Bardol, Ida. E-mal: Rathod_b@yahoo.co. further studed the effect varous machg parameters o SR of AISI D steel. Expermetal results dcate that the thcess of the recast layer, ad surface roughess are proportoal to the power put. Y.H. Guu et al. [5] studed the three-dmesoal mages of AISI D tool steel mached by the EDM process was aalyzed by meas of the atomc force mcroscopy techque. The AFM study of the surface morphology of the EDM specme has revealed that hgher dscharge eergy results a poorer surface structure. To avod excessve mached damage, low dscharge eergy should be used. M. K. Pradha ad C. K. Bswas et al. [6, 7] developed regresso model ad two artfcal eural etwors (ANNs) amely: Bac propagato ad radal bass fucto to predct surface roughess electrcal dscharge mached surfaces. S. Prabhu ad B.K. Vayagam et al. [8] used sgle-wall carbo ao tube mxed wth delectrc fluds EDM process to aalyss the surface characterstcs le surface roughess, mcro cracs AISI D tool steel a wor pece materal whch s very much used moulds ad des. A excellet mached ao fsh ca be obtaed by settg the mache parameters at low pulse eergy. EXPERIMENTAL SET- UP A umber of expermets were coducted to study the effects of varous machg parameters o EDM process. These studes were udertae to vestgate the effects of varous machg parameters o surface roughess. The selected worpece materal for the research wor s AISI D tool steel. D steel was selected due to ts emerget rage of applcatos the feld of maufacturg tools mould dustres. Durg the heat treatmet, the materal was heated to C at a heatg rate of 0 0C m-1. The, the materal was held at C for 1 h ad was queched. After quechg, the specmes were tempered at 350 0C for h ad the ar

2 Iteratoal Joural of Scetfc & Egeerg Research, Volume 3, Issue 6, Jue-01 coolg. Expermets were coducted o JOEMARS Z 50 JM- 3 de sg mache usg reverse polarty. The flushg pressure was 0.5 Kg/cm. The copper wth a dameter of 15 mm was used as a tool electrode ad De-electrc flud-9 (DEF-9) was used as de electrc flud. The test codtos are depcted Table-1. I preset aalyss surface roughess s measured o a mtutoyo mae portable dgtal surface fsh tester (model: surftest set o: e). 3 RESPONSE SURFACE METHODOLOGY RSM s a collecto of mathematcal ad statstcal techques that are useful for modelg ad aalyss of problems whch the respose of terest s flueced by several varables ad objectve s to optmze ths respose [9]. The cetral composte rotatable desg (CCRD) s useful tha full factoral desgs, sce t requres much fewer tests ad show to be suffcet to descrbe the resposes [10]. Thus, CCRD was chose to determe the relatoshp betwee four operatg varables amely, pulse curret, pulse o-tme, pulse off-tme ad spar gap voltage. I order to study the effects of the EDM parameters o the above metoed machg crtera, secod order polyomal respose surface mathematcal models ca be developed. I the geeral case, the respose surface s descrbed by a equato of the form: Y 0 x 1 1 x j j x x Where Y s the correspodg respose, varables, X j r X s the put ad X are the squares ad teracto terms, X j respectvely, of these put varables. The uow regresso coeffcets are 0,, j ad. I order to determe the equato of the respose surface, expermetal desg has bee developed wth the attempt to approxmate ths equato usg the smallest umber of expermets possble. I ths vestgato, expermetal desg was establshed o the bass of factoral, where s the umber of varables, wth cetral composte-secod-order rotatable desg to mprove the relablty of results ad to reduce the sze of expermetato wthout loss of accuracy. Thus, the mmum possble umber of expermets (N) ca be determed from the followg equatos: a dstace c = 1/ from the cetre pot of the desg to a star pot ad o parameter meas the umber of cetre pots at the org ad ca be get from tables accordg to the umber of depedet varables [11]. I ths case = 4 ad thus c = = 16 corer pots at ±1 level, a = = 8 axal pots at c = ±, ad a cetre pot at zero level repeated 7 tmes (o). Ths volves a total of 31 expermetal observatos. The coded levels for all process parameters used are show Table-1. TABLE 1 CODING LEVELS OF PROCESS PARAMETERS N c a c a..., Where c parameter defes the umber of factoral pots or corer pots. Oe cetral composte desg cossts of cube pots at the corers of a ut cube that s the product of the tervals [-1, 1]. The a parameter defes the umber of axal pots or star pots alog the axes or outsde the cube at

3 Iteratoal Joural of Scetfc & Egeerg Research, Volume 3, Issue 6, Jue-01 3 TABLE PLAN FOR CENTRAL COMPOSITE ROTATABLE SECOND-ORDER DESIGN Ra Ip To Toff V Ip Ip To To 8 03 Toff Toff V V Ip To 6 03 Ip Toff.59 0 Ip V To Toff To V Toff V TABLE-3 ANOVA TABLE FOR SR BEFORE ELIMINATION The uow coeffcets are determed from the expermetal data as preseted Table-3. The stadard errors o estmato of the coeffcets are tabulated the colum SE coef. The F ratos are calculated for 95% level of cofdece. For mprovg the value of R the uusual observato wth large stadardzed resdual (.e. 7, 8, 10, ad ) were elmated. The regresso model s reevaluated by determg the uow coeffcets, whch are tabulated Table-4. The fal respose equato for SR s gve below equato. The ANOVA table for the curtaled quadratc model (Table- 4) depcts the value of Coeffcet of determato R as 98.38%, whch sgfes that how much varato the respose s explaed by the model. The hgher of R, dcates the better fttg of the model wth the data. However, R adj s 96.49%, whch accouts for the umber of predctors the model descrbes the sgfcace.

4 Predcted Ra(µm) Iteratoal Joural of Scetfc & Egeerg Research, Volume 3, Issue 6, Jue-01 4 TABLE 4 ANOVA TABLE FOR SR AFTER ELIMINATION come close to form a straght le, t mples that the data are ormal. It ca be see that the regresso model s reasoably well ftted wth the observed values Expermetal Ra(µm) Fg.1. Predcted vs. expermetal SR It s mportat to chec the adequacy of the ftted model, because a correct or uder-specfed model ca lead to msleadg coclusos. By checg the ft of the model oe ca chec whether the model s uder specfed. The model adequacy checg cludes the test for sgfcace of the regresso model, model coeffcets, ad lac of ft, whch s carred out subsequetly usg ANOVA o the curtaled model (Table-5). TABLE 5 ANOVA TABLE FOR THE FITTED MODEL Fg.. Effect of Ip & To o SR The effect of the machg parameters (Ip, To Toff ad V) o the respose varables SR have bee evaluated by coductg expermets as descrbed the prevous secto ad aalyzed usg Mtab software. ANOVA s used to chec the suffcecy of the secod-order model. SR obtaed from the expermet s compared wth the predcted value calculated from the model Fg. 1. Sce all the pots o plot Fg. shows the estmated respose surface for Surface Roughess relato to the process parameters of Ip ad To whle Toff ad V rema costat at ther mddle value. It ca be see from the fgure, the SR teds to crease sgfcatly wth the crease Ip for ay value of To. However, the SR teds to crease wth crease To, especally at hgher Ip. Hece, mmum SR s obtaed at low pea curret ad low pulse o tme. Ths s due to ther domat cotrol over the put eergy,.e. wth the crease Ip ad To geerates strog spar for loger tme, whch create the hgher temperature ad crater, hece rough surface the worpece ad low Ip creates small crater ad therefore smooth surface. Fg. 3 shows the estmated respose surface for Surface Roughess relato to the process parameters of Ip ad Toff whle To ad V rema costat at ther mddle value. It ca

5 Iteratoal Joural of Scetfc & Egeerg Research, Volume 3, Issue 6, Jue-01 5 be see from the fgure, the SR teds to crease sgfcatly wth the crease Ip, the explaato s same, as stated earler. However, wth the crease Toff, SR decreases. It s because t taes tme before ext spar ad reduces the crater effect due to hgher temperature. Fg. 5. Effect of Ip & V o SR Fg. 3. Effect of Ip & Toff o SR 4 CONFORMATION TEST TABLE 6 COMPARISON OF PREDICTED VS. EXPERIMENTAL Fg. 4. Effect of Ip & V o SR Fg. 4 represets SR as a fucto of To ad Toff, whereas the Ip ad V remas costat at ts mddle level. It s observed that the SR values are low whe To s low wth hgher Toff or Toff s low wth hgher To. From the aalyss t s sad that the teracto of To ad Toff s sgfcat. Although the fluece of ths two parameter s very less whe compared wth the effect of Ip o SR. It ca be observed that there s o sgfcat varato of SR wth the varato of voltage. From ths observato, t ca be cocluded that Ip ad To are drectly proportoal, ad Toff s versely to the SR for the gve rage of expermets coducted for our test. 5 CONCLUSION I the preset study, the process parameters wth sgfcat fluece o Surface roughess were determed by usg RSM. Ths paper hghlghts the developmet of a comprehesve mathematcal model for correlatg the teractve ad hgher order flueces of varous electrcal dscharge machg parameters through respose surface methodology (RSM), utlzg relevat expermetal data as obtaed through expermetato of surface roughess. The lower value of surface roughess s acheved wth Ip = 6 A, To = 75 μs ad Toff = 70 μs wth the expermetal doma. The research fdgs of the preset study based o RSM models ca be used effectvely machg of AISI D tool steel order to obta best possble EDM effcecy. 6 REFERENCES [1] Puertas. C.J. Lus. G. Vlla Spacg roughess parameters study o the EDM of slco carbde, Joural of Materals Processg Techology : [] R. K. Garg. K. K. Sgh. Ash Sachdeva. Vshal S. Sharma. Kuldeep Ojha. Sharajt Sgh Revew of research wor sg EDM ad WEDM o metal matrx composte materals, It J Adv Mauf Techol 50:

6 Iteratoal Joural of Scetfc & Egeerg Research, Volume 3, Issue 6, Jue-01 6 [3] Y.H. Guu. H. Hocheg Improvemet of fatgue lfe of electrcal dscharge mached AISI D tool steel by TN coatg, Materals Scece ad Egeerg A318: [4] Y.H. Guu, H. Hocheg, C.Y. Chou, C.S. Deg Effect of electrcal dscharge machg o surface characterstcs ad machg damage of AISI D tool steel, Materals Scece ad Egeerg A358: [5] Y.H. Guu AFM surface magg of AISI D tool steel mached by the EDM process, Appled Surface Scece 4: [6] M. K. Pradha ad C. K. Bswas Predctve modellg ad aalyss of surface roughess electrodscharge machg of d tool steel usg regresso ad eural etwors approach, Iteratoal Joural o Desg ad Maufacturg Techologes.3: 0-9. [7] M. K. Pradha, ad C. K. Bswas Modelg ad Aalyss of process parameters o Surface Roughess EDM of AISI D tool Steel by RSM Approach, Iteratoal Joural of Egeerg ad Appled Sceces 5: [8] S. Prabhu ad B.K. Vayagam Aalyss of surface characterstcs of AISI D tool steel materal usg Electrc Dscharge Machg process wth Sgle wall carbo ao tubes, Iteratoal Joural of Egeerg ad Techology Vol. : [9] D. C. Motgomery Desg ad aalyss of expermets, Joh wlly ad Sos Ic. [10] Ulaş Çaydaş & Ahmet Hasçal Modelg ad aalyss of electrode wear ad whte layer thcess de-sg EDM process through respose surface methodology, It J Adv Mauf Techol 38: [11] Sameh S. Habb Study of the parameters electrcal dscharge machg through respose surface methodology approach, Appled Mathematcal Modellg 33: