Effect of Machining Parameters of AISI D2 Tool Steel on Electro Discharge Machining

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1 Research Artcle Iteratoal Joural of Curret Egeerg ad Techology E-ISSN , P-ISSN INPRESSCO, All Rghts Reserved Avalable at Effect of Machg Parameters of AISI D2 Tool Steel o Electro Dscharge Machg Sajay Kumar Majh Ȧ*, T.K.Mshra Ȧ, M.K.Pradha Ḃ ad Hargovd So Ȧ Ȧ Departmet of Mechacal, Gya Gaga Isttute of Techology & Scece, Jabalpur, Ida Ḃ Departmet of Mechacal, Maulaa Azad Natoal Isttute of Techology, Bhopal, Ida Accepted 0 Jauary 14, Avalable ole 01 February 14, Vol.4, No.1 (February 14) Abstract AISI D2 tool steel s a hgh-carbo ad hgh-chromum cold-wor tool steel alloyed wth molybdeum ad vaadum. It has may propertes such as hgh wear resstace, hgh compressve stregth, ad hgh stablty hardeg ad good resstace to temperg bac. The chemcal composto of AISI D2 tool steel s (1. % C, 0.3 %S, 0.4 %M, 11.8 % Cr, 0.8 % Mo, ad 0.8 % V). The applcato of AISI D2 s Deep drawg ad formg des, cold drawg puches, hobbg, blag, lamato ad stampg des, shear blades, burshg rolls, master tools ad gauges, slttg cutters, thread rollg & wre des, extruso des etc. The uque features of ths alloy have made t useful all type of dustres. Due to these characterstcs ths alloy dffcult to perform machg by tradtoal method. Electro dscharge machg s the oe of the most machg, whch that materal ca be used. Purpose of ths study s the effect of machg parameters such as pulse o tme (T o ), pulse off tme (T off ) ad dscharge curret (I p ) o the materal removal rate (MRR), tool wear rate (TWR) ad surface roughess (SR) of AISI D2 tool steel. For the expermetato were used grey relatoal aalyss ad etropy measuremet method based o respose surface method. The expermets sgfy that the parameters of pulse o tme, pulse off tme ad dscharge curret, have a drect mpact o materal removal rate (MRR), ad wth ther crease, MRR creases as well. Wth the crease of pulse off tme tool wear rate (TWR) decreases. The aalyss of results for surface roughess shows that pulse o tme ad off tme have the hghest mpact o the surface roughess of AISI D2 tool steel. Keywords: AISI D2 tool steel, Electro dscharge machg, Respose surface method, etropy measuremet aalyss, materal removal rate, tool wear rate, surface roughess. 1. Itroducto 1 AISI D2 s oe of the most popular hgh-chromum ad hgh-carbo steels of D seres ad t s characterzed by ts hgh compressve stregth ad wear resstace, good through-hardeg propertes, hgh stablty hardeg ad good resstace to temperg-bac. Cold wor tool steels of Seres D, also ow as de steels, are hgh alloy steels Fe-Cr-C-base. Ths alloy has the ablty to preserve ts desrable mechacal propertes tact upo cyclg over a rage of temperatures, whch ca be a advatage for applcatos cludg, percg ad blag des, puches, shear blades, spg tools, slttg cutters, as well as varety of hgher-ed wood worg tools (V. Sstaet al. 11, Wuu-Lg Pa et al. 18, K.H. Prabhudev 12) Despte good mechacal propertes of D2 steel, the lfetme of peces ad accessores fabrcated wth ths alloy s egatvely affected by the crease the severty of operatg codtos due to cotug evoluto of dustral processes ad corrosve operato evromets (G. Ramírezet al. 12).. *Correspodg author: Sajay Kumar Majh Electro Dscharge Machg (EDM) s a brllat soluto to ths problem; t s geerally used to mache dffcultto-mache materals, hgh stregth, temperature resstat alloys ad maufacturg of tools ad des for machg cavtes ad couter shapg ad cuttg, As log as the Wor materal s coductve. It s a wdely appled ad very useful techque based o eroso of metal caused by the dscharge occurrg betwee the electrode ad the process part. The electrcal spar s geerated ad materal removal maly occurs due to the thermal eergy of the spar. I EDM, materal removal depeds o maly thermal propertes of the wor materal rather tha ts stregth, hardess etc. Amog several attempts RSM was employed (Pradhaet al. 11) to vestgate the fluece of processg varables o the resposes MRR & SR. (Ragaatha&sethvela 11) used TM to optmzato of SR, TWR & MRR ad study the effect of cuttg speed, feed rate, depth of cut, ad wor pece temperature. (Pradha&Bswas 10) have establshed Emprcal models varables wth MRR & SR. (L B et al. 02). Optmzed the machg parameters le wor pece polarty, pulse o tme, duty factor, ope dscharge 1 Iteratoal Joural of Curret Egeerg ad Techology, Vol.4, No.1 (Feb 14)

2 Sajay Kumar Majhet al Effect of Machg Parameters of AISI D2 Tool Steel o Electro Dscharge Machg voltage, dscharge curret ad delectrc flud wth resposes MRR, SR, ad electrode wear rato use of orthogoal array wth GRA. (Raoet al. 0) used GRA etropy measuremet for determato of eed-yag laser cuttg process parameters. (Sgh et al. 04) optmzg MRR, TWR, SR, taper, radal o EDM by GRA. (Reddy Sreevasuluet al. 13 revew paper) obta the optmal levels of processparameters that yeld the burr sze ad hole qualty drllg ofalumum 61 alloy & ehace the effectveess of the drllg process usg desg ofexpermets based grey relatoal aalyss. (L Shchaget al. 11) optmze the fermetato medum of hgh-yeldg L-lactc acd stras usg Respose surface method. (SauravDattaet al. 10) study the effect of parametrc fluece of wre EDM o MRR, SR ad wdth of cut to establsh mathematcal models & smulato. (Sharma &Yadava 12) preset a hybrd approach of RSM & TM for modelg ad TM, GRA coupled wth etropy measuremet method for optmzato of cut qualty durg pulsed Nd: YAG laser cuttg of th Al-alloy sheet for straght profle. 2. Expermetato For the expermet a de sg EDM mache model electroc electraplus S0 smart CNC s used. Evaluatg the machg performace such as MRR, TWR, ad SR s cosdered. All three performace characterstcs correlated wth machg parameters such as pulse o tme, pulse off tme ad pulse curret. AISI D2 tool steel was selected as a worpece due to ts emerget rage of applcatos the maufacturg tool ad moulds dustres ad a pure copper was used as a tool electrode, commercal grade EDM ol ( specfc gravty=0.63, freezg pot 4 o C was used as a delectrc feld.) The expermets were coducted wth three varables, havg a total rus three blocs. The dfferet level of parameters cosdered for ths study s lsted table 1. The machg tme for all expermets was ept costat of 1 m. Table 1 ut parameters ad ther levels Parameters Uts Level 1 Level 2 Level 3 Dscharge curret (I p ) A Pulse o Tme (T o ) μs Pulse off Tme (T off ) μs Measuremet Of Respose 2.1.1Materal Removal Rate MRR s calculated by usg the volume loss from the wor pece dvded by the tme of machg. The calculated weght loss s coverted to volumetrc loss mm3/m as per equato -I Vw Ww MRR (1) t wt Where Vw = volume loss from the wor pece, Ww = the weght loss from the wor pece t = the durato of the machg process, the desty of the wor pece Tool Wear Rate w = 00g/m 3 TWR s expressed as the volumetrc loss of tool per ut tme, expressed as Vt Wt TW R (2) T t gt Where Vt = the volume loss from the electrode, Wt = the weght loss from the electrode, T= the durato of the machg process, t = 8g/m3 the desty of the electrode Surface Roughess Surface roughess s a measure of the techologcal qualty of a product, whch mostly fluece the maufacturg cost of the product. Roughess measuremet was carred out usg a portable stylus type proflometer, Talysurf. It s defed as the arthmetc value of the profle from the ceterle alog the legth, expressed as 1 L SR [ y( x)] dx (3) 0 L Where L= samplg legth, Y= profle curve, = profle drecto. 3. Methodology I ths research, there are three methods employed for estmatg the effect of process parameters of EDM o AISI D2 tool steel. 1- Respose Surface Method (RSM) 2- Grey Relatoal Aalyss (GRA) 3- Etropy Measuremet Aalyss 3.1 Respose Surface Method Respose surface methodology (RSM) s a collecto of mathematcal ad statstcal techques for emprcal model buldg. (Box ad Draper 18) were troducg RSM 11. Ths methodology s based o expermetal desg wth the fal goal of evaluatg optmal fuctog of dustral facltes, usg mmum expermetal effort. Here, the puts are called factors or varables ad the outputs represet the respose that geerates the system uder the causal acto of the factors. Afterwards, the use of the RSM was show the desg of ew processes ad products. I RSM secod-degree polyomal model s used. Ths model s ow as quadratc model, whch s as follows:- 2 Y 0 j j (4) 1 1, j1, j Where s the lear put varables, 2 ad j are the squares ad teracto terms, respectvely; of these put varables, ε s the ose or error observed the respose Y. The uow secod order regresso coeffcets are β o, β, β j ad β, whch should be determed the secod-order model, are obtaed by the least square Iteratoal Joural of Curret Egeerg ad Techology, Vol.4, No.1 (Feb 14)

3 Sajay Kumar Majhet al Effect of Machg Parameters of AISI D2 Tool Steel o Electro Dscharge Machg method. The Mtab Software was used to aalyze the data (03)[1]. 3.2 Grey Relatoal Aalyss Grey system theory troduced by Deg (182). Grey relatoal aalyss uses a specfc cocept of formato. It defes stuatos wth o formato as blac ad those wth perfect formato as whte. However, ether of these dealzed stuatos ever occurs real world problems. I fact, stuatos betwee these extremes are descrbed as beg grey. Grey aalyss does ot attempt to fd the best soluto, but does provde techques for determg a good soluto, a approprate soluto for real world problem. Whe the rage of the sequece s too large or the stadard value s too eormous, t wll cause the fluece of some factors to be eglected. Also, the sequece, f the factors goals ad drectos are dfferet the relatoal aalyss mght also produce correct results. Therefore, preprocessg of all the data s ecessary. Ths process s called as Grey relatoal geeratg. The rage of data processg s zero to oe (0-1). There are three dfferet types of data pre-processg lower s better, hgher s better, ad omal the best. But ths research oly two codtos are requred, lower s better & hgher s better. Hgher s better * m () max m Lower s better * max (6) max m Nomal the best 1 ( ) ( ) * 0b () max 0b( ) Where I = 1, 2, = 1, 2, y, p; * () s the ormalzed value of the th elemet the th sequece, max * () s the largest value of (), ad m * () s the smallest value of (), 0 b () s desred value of the th qualty characterstc, s the umber of expermets ad p s the umber of qualty characterstcs. After the data pre-processg, calculated grey relatoal co-effcet, whch shows the teracto betwee optmal & actual ormalzed expermetal results. GRC ca be preseted- m max ( x0( )) (8) max 0, I=1;... ; ; = 1;... ; p Where Δ 0, () = x 0 () x () s the dfferece of the absolute value called devato sequece of the referece sequece x 0 () ad comparablty x (). The ξ s the dstgushg coeffcet or detfcato coeffcet 0 1. I geeral, t s set to 0.. The GRG s a weghtg-sum of the grey relatoal coeffcets ad t s defed as- 1 0, x ) ( x0, x ) ( x () Where β represets the weghtg value of the th performace characterstc, ad Etropy Measuremet Method I GRA, for the determato of weghts of each qualty characterstcs, etropy measuremet method was used. Ths s a objectve weghtg method. Suggested by we et al. dscrete type of etropy s used grey etropy measuremet for properly coduct weghtg aalyss. Etropy method s used for calculatg grey relatoal grade. For the calculatos of weghts of each characterstc seve steps are gve below- 1- Compute the summato of each attrbute s value for all sequeces, D - D m x 1 (10) 2- Compute the ormalzato coeffcet K- 1 K 0. (11) ( e 1) Where represets the umber of attrbutes. 3- Fd the etropy for the specfc attrbute, e - 1 x e f ( K 1 D 4- Compute the total etropy value E- E e 1 (12) (13) - Determe the relatve weghtg factor - (1 e ) (14) E 6-The ormalzed weght of each attrbute ca be calculated as- (1) 1 For calculato of GRG, grey relatoal co-effcet multplyg wth correspodg weght of qualty characterstcs. 4. Result ad Dscusso The expermetal values are obtaed from expermets coducted as per pla preseted Table 2. Normally, hgher value of MRR ad lower value of TWR & surface roughess are desred. Thus, the ormalzed equato () are used for hgher the better (MRR) ad lower the better for TWR & SR s used equato (6). I ormalzato, the orgal sequece must be ormalzed the rage of zero to oe. Calculato of grey relatoal co-effcet, grey relatoal grade & ra are gve table 3. The grey relatoal co-effcet was calculated from equato (8). before calculatg GRG, must be fd weghtage of each characterstc used by etropy measuremet method. GRG calculated by equato (). Statstcal aalyss of GRG was performed by usg Mtab software. Effect of process parameters o MRR, TWR & SR are show fgure 1, 2, ad Iteratoal Joural of Curret Egeerg ad Techology, Vol.4, No.1 (Feb 14)

4 Mea of SR Mea of TWR Mea of MRR Sajay Kumar Majhet al Effect of Machg Parameters of AISI D2 Tool Steel o Electro Dscharge Machg Table 2 Expermetal results for three varables coded uts Sl. No. To MRR TWR SR roughess lttle crease up to after that decrease. Ad wth the crease of pulse off tme surface roughess very lttle crease up to the decrease Ma Effects Plot (data meas) for MRR Fg. 1 ma effect plot for materal removal rate 4 To Table 3 Grey relatoal co-effcet, grey relatoal grade ad ra 6.0 Ma Effects Plot (data meas) for TWR To GRC MRR GRC TWR GRC SR GRG RANK Fgure 1 show that the effect of process parameters o materal removal rate. I ths fg. wth the crease of pulse curret ad pulse o tme, materal removal rate s sharply creased. Ad whe pulse off tme crease, materal removal rate decrease up to after that crease. Fgure 2 show that the effect of pulse curret, pulse o tme ad pulse off tme o the tool wear rate. Wth the crease of pulse curret ad pulse o tme, tool wear rate crease. Ad wth the crease of pulse off tme tool wear rate slghtly decrease up to after that lttle crease. Fgure 3 show that ma effect plot for surface roughess. Wth the crease of pulse curret surface roughess slghtly crease, ad whe pulse o tme crease surface Fg. 2 ma effect plot for tool wear rate Ma Effects Plot (data meas) for SR To Fg. 3 ma effect plot for surface roughess 22 Iteratoal Joural of Curret Egeerg ad Techology, Vol.4, No.1 (Feb 14)

5 Sajay Kumar Majhet al Effect of Machg Parameters of AISI D2 Tool Steel o Electro Dscharge Machg. Cocluso I ths study, the effect of put parameters of EDM machg process such as pulse curret, pulse o tme ad pulse off tme o the output parameters le MRR, TWR, ad SR of machg of AISI D2 tool steel. I performg the expermet, the techques was used ths study s GRA ad etropy based o RSM order to obta the process resposes. It was demostrated ths research that the most sgfcat & effectve factors the MRR of AISI D2 steel mached by copper tool are the pulse curret ad pulse o tme, whose crease tesfes the specfc eergy & crease the MRR. Wth the crease of pulse curret, surface roughess creases. Ad wth the crease of pulse o tme & pulse curret, tool wear crease. The crease of pulse off tme causes the reducto of tool wear ad surface roughess. To obta the least amout of surface roughess, the least values of pulse curret & pulse o tme should be chose ad pulse off tme betwee two pulses should be decreased. I the machg of AISI D2 steel usg copper tools, the hghest value of pulse curret & pulse o tme were selected to obta the maxmum MRR. To crease the suffcecy f the EDM process, MRR should be hgh. But wth the crease of MRR, tool wear rate also creases, ad accordg to obtaed results, the qualty of the mached surface wll decrease as well. Therefore, t would ecessary to carry out the process several stages, frst, by creasg the curret ad pulse o tme, MRR s creased utl the worpece gets closer to ts fal shape ad the the fal & fshg stage, the worpece s mached wth other tools & by applyg a lower pulse curret ad pulse o tme, so that the TWR s reduced ad a hgher qualty surface fsh s acheved by the EDM process. Refereces V. Ssta, O. Kahvecoglu, O.L. Erylmaz, A. Erdemr, S. Tmur. (11) Th Sold Flms., 182 Wuu-Lg Pa, Ge-Pg Yu, Ja-Hog Huag, (18) Surf. Coat.Techol K.H. Prabhudev (12). Hadboo of Heat Treatmet of Steels, Mc-Graw-Hll Compay, NY. G. Ramírez, A. Mestra, B. Casas, I. Valls, R. Martíez, R. Bueo, A. Goez, A. Mateo, L. Llaes (12). Surf.Coat. Techol. 6,6. Pradha, M. K. ad Bswas, C. K. (11).Mult-respose optmzato of EDM AISI D2 tool steel usg respose surface methodology.iteratoal Joural of Machg ad Machablty ofmaterals (IJMMM), :66 8. Ragaatha, S. ad Sethlvela, T. (11).Mult-respose optmzato of machg parameters hot turg usg grey aalyss.the Iteratoal Joural of Advaced MaufacturgTechology, 6: M. K. Pradha ad C. K. Bswas, (10 )Ivestgatg the effect of machg parameters o EDMed compoets a RSM approach, Iteratoal Joural of Mechacal Egeerg, vol., pp. 4 64,. J. L ad C. L, (02) The use of the orthogoal array wth grey relatoal aalyss to optmze the electrcal dscharge machg process wth multple performace characterstcs, Iteratoal Joural of Mache Tools ad Maufacture, vol. 42, pp Rao R, Yadava V. (0) Mult-objectve optmzato of Nd: YAG laser cuttg of th super alloy sheet usg grey relatoal aalyss wth etropy measuremet. Opt Laser Techol; 41(8):22. Sgh, S., Maheshwar, S., ad Padey, P. (04). Some vestgatos to the electrc dscharge machg of hardeed tool steel usg dfferet electrode materals. Joural of MateralsProcessg Techology, 14(1-3):22 2. Reddy Sreevasulu ad Ch. SrvasaRao (13)Desg of Expermets based Grey Relatoal Aalyss Varous Machg Processes - A Revew. Research Joural of Egeerg Sceces, ISSN Vol.2(1),21-26, Res. J. Egeerg Sc. L Shchag, Zhu Zhaoyag, GuShaob, Lu Hogxa, Wag Dogdog (11) Applcato of respose surface methodology (RSM) for optmzato of hgh-yeldg L-lactc acd stras selected by low-eergy o mplatato.afrca Joural of Food Scece ad Techology (ISSN: ) Vol. 2(6) pp , Jue. SauravDatta, SbaSaarMahapatra (10) Modelg, smulato ad parametrc optmzato of wre EDM process usg respose surface methodology coupled wth grey-taguch techque. Iteratoal Joural of Egeerg, Scece ad Techology Vol. 2, No., pp Amt Sharma ad VodYadav (12) Modelg ad optmzato of cut qualty durg pulsed Nd: YAG laser cuttg of th Al-alloy sheet for straght profle. Optcs & Laser Techology 441, 168. Elsever J. Cler Maxwell, a Treatse o Electrcty ad Magetsm, 3rd ed., vol. 2. Oxford: Claredo, 182, pp Box, G. E. P. ad N.R. Draper, (18).Emprcal Model-Buldg ad Respose Surfaces, Jo Wley & Sos, New Yor. Mtab14 (03).Mtab User Maual Release 14. State College, PA, USA. J. L. Deg (18), Itroducto to grey system theory, J. Grey Syst., vol. 1, pp. 1 24, November. K. L. We, T. C. Chag, ad M. L. You, (18) The grey etropy ad ts applcato weghtg aalyss, IEEE Iteratoal Coferece o Systems, Ma, ad Cyberetcs vol. 2, pp Iteratoal Joural of Curret Egeerg ad Techology, Vol.4, No.1 (Feb 14)