Utility Fuzzy Multiobjective Optimization of Process Parameters for CNC Turning of GFRP/Epoxy Composites

Transcription

1 5 th Internatonal & 26 th All Inda Manufacturng Technology, Desgn and Research Conference (AIMTDR 2014) December 12 th 14 th, 2014, IIT Guwahat, Assam, Inda Utlty Fuzzy Multobjectve Optmzaton of Process Parameters for CNC Turnng of GFRP/Epoxy Compostes Har Vasudevan 1*,Naresh Deshpande 2, Ramesh Rajguru 3, Sandp Mane 4 1*,2,4 Department of Producton Engneerng, D.J. Sanghv College of Engneerng, Mumba, Inda, * E-mal:prncpaldjs@gmal.com; 2 E-mal: ncdeshpande72@yahoo.co.n; 3 Department of MechancalEngneerng, D.J. Sanghv College of Engneerng, Mumba, Inda, E-mal: ramesh.rajguru9@gmal.com; 4 E-mal:sandp_dabade@yahoo.co.n Abstract Although Glass Fbre Renforced Plastc (GFRP) compostes are usually moulded near-net shape for obtanng close fts and tolerances, certan amount of machnng has to be carred out on them.a number of axsymmetrc GFRP composte parts are fnsh machned by turnng. These nclude axles, spndles, columns, rolls, bearngs, drag lnks and steerng columns. Qualty and productvty are two mportant, but contradctory parameters whle performng machnng operatons. Hence, t becomes essental to evaluate the optmal cuttng parameters settng n order to satsfy contradctory requrements of qualty and productvty.in ths study,a hybrd multobjectve optmzaton algorthm nvolvng utlty and fuzzy coupled wth Taguch methodology s used. Four process parameters, each at three levels are selected for the study vz. cuttng tool nose radus, cuttng speed, feed rate and depth of cut. Surface roughness parameter Ra, cuttng force Fz and materal removal rate MRR are the chosen output performance measures. The expermental plan s lad accordng to Taguch s orthogonal array L27. Woven fabrc based GFRP/ Epoxy tubes produced usng hand layup process are fnsh turned usng Poly Crystallne Damond (PCD) cuttng tool. Utlty values of the three performance measures are converted nto a sngle Mult Performance Characterstcs Index (MPCI) usng Mamdan type fuzzy nference system. Ths MPCI s then optmzed usng Taguch analyss. The parameter combnaton of A2B3C1D2,.e. tool nose radus of 0.8 mm, cuttng speed of 200 m/mn, feed rate of 0.05 mm/rev and depth of cut of 1mm, s evaluated as the optmum combnaton. The confrmatory experment at these settngs gves maxmum value of MPCI valdatng the results. Keywords: GFRP/Epoxy, Utlty values, Fuzzy nference system, Multobjectve optmzaton. 1 Introducton Machnng of GFRP s dfferent n comparson to that of metals. Most homogeneous and ductle metals can be machned by shearng and plastc deformaton. Contnuous chps are usually formed durng machnng of such metals. Machnng of GFRPs, s usually characterzed by uncontrolled ntermttent fracture. Oscllatng cuttng forces are typcal, because of the ntermttent fracture of the fbres (Jamal, 2009). Qualty and productvty are two mportant, but contradctory parameters whle performng machnng operatons. Qualty manly concerns wth dmensonal accuracy and surface roughness of the machned part, whereas productvty s drectly related to Materal Removal Rate (MRR) durng machnng. Mnmzng the cuttng force s also mportant as t affects tool wear, tool lfe and stablty of machne tool. Surface fnsh seems to be nversely related to MRR; hence t becomes essental to evaluate the optmum cuttng parameters settng n order to satsfy contradctory requrements of qualty and productvty. Isk and kentl (2009) proposed a multple crtera optmzaton approach usng senstvty. Mnmzng cuttng forces and maxmzng the materal removal were consdered as objectves, whle turnng of undrectonal glass fber renforced polyester rods. Palankumar et al. (2007) used grey relatonal grade & Taguch method for mnmzng tool wear, surface roughness and specfc cuttng pressure, whle maxmzng materal removal. They carred out turnng on GFRP/Epoxy compostes usng carbde (K10) tool.routara et al. (2010) appled utlty concept coupled wth Taguch method n order to evaluate the best process envronment,whch could smultaneously satsfy multple requrements of surface qualty. They presented a case study on CNCend mllng of UNS C34000 medum leaded brass.har Sngh and Pradeep Kumar (2006) used the utlty concept coupled wth Taguch method for optmzng multple qualty characterstcs durng turnng of En24 steel

2 Utlty Fuzzy Multobjectve Optmzaton of Process Parameters for CNC Turnng of GFRP/Epoxy Compostes It s observed that the machnablty of composte materals s hghly nfluenced by the type of fbre, type of resn, fbre orentaton and method of manufacturng. The extant lterature survey also reveals that woven glass fbre renforced epoxy compostes manufactured by hand lay-up process have not been wdely explored for ther machnng characterstcs, despte ther wde applcatons. The present study s an attempt to brdge ths gap. 2 Methodology The methodology used for ths study s as shown below n Fg. 1. Ishkawa fsh bone dagram was constructed for the turnng process of GFRP compostes to sort out the process parameters nfluencng the cuttng force, roughness and materal removal rate. As the outcome of ths cause and effect analyss, process parameters selected for the study are cuttng tool nose radus, cuttng speed, feed rate and depth of cut. The range of values for these parameters, areselected afterperformng plot experments and referrng to the past contrbutons of researchers n ths context. The experments are planned usng Taguch s desgn of experments (DOE). The total degrees of freedom (DOF) for four parameters, each at three levels are eght. Hence, a three level orthogonal array (OA) wth at least eght DOF s to be selected. The L27 OA (DOF = 26) s thus selected for ths study. The factors are assgned to column no. 1, 2, 5 and 8 respectvely. The unassgned columns are treated as error. Also the trals are carred out n random order.thee process parameters selected for the present work and ther levels are as gven n Table 1. Label Table 1 Control factors and ther levels Process parameters Unts A Tool nose radus mm B Cuttng speed m/mn C Feed rate mm/rev D Depth of cut mm Levels L 1 L 2 L Fgure 1 Methodology used for the study. 2.1 Expermentaton The work materal selected for the study s glass fbre renforced epoxy composte. The E-glass renforcement s of woven fabrc form havng followng specfcatons. Type of weave: plan, weght: 180±5 gm/m 2 and 0.18mm thckness. Epoxy resn manufactured by Huntsman, product Araldte LY3297 and hardener Aradur 3298 s used as polymer matrx materal. The work specmens are tubular n shape, 50 mm long, wth nner dameter of 20 mm and outer dameter of 55 mm. They are manufactured usng hand lay-up process and cured at room temperature. The volume fracton of the renforcement s 70%. The work specmens before & after machnng are as shown n Fg. 2 & Fg. 3 respectvely. The cuttng tool selected for turnng s Poly Crystallne Damond (PCD) nsert of the fne grade. Three dfferent types of nserts are used. They have ISO codng as CNMA , CNMA and CNMA 221-2

3 5 th Internatonal & 26 th All Inda Manufacturng Technology, Desgn and Research Conference (AIMTDR 2014) December 12 th 14 th, 2014, IIT Guwahat, Assam, Inda dynamometer to a computer and usng KstlerDynoware type- 2825A software. The materal removal rate s calculated as per Eq. (1), by measurng the weght of component before and after turnng operaton, wth precson dgtal weghng machne and recordng the machnng tme wth a stop watch. Fgure 2 Work specmens before machnng Fgure 3 Work specmen after machnng The tool holder s of WIDEX-ID1G wth ISO codng, PCLNL 25X25 M12. The experments are conducted on a Ace Jobber XL CNC lathe machne wth the followng specfcatons: swng over bed 500 mm, swng over carrage 260 mm, max. turnng da. 270 mm, max. turnng length 400 mm, max. spndle speed 4000 rpm, spndle motor power 7.5 KW and Fanuc seres O-TD Mate CNC controller. The machnng tests are carred out wthout any coolant. The work pece s mounted on specally desgned mandrel, whch s subsequently clamped by the lathe chuck. One repeat run s conducted for each of the 27 trals. The response measures selected are, surface roughness parameter Ra, tangental cuttng force Fz and materal removal rate MRR. The surface roughness parameter s measured usng Taylor Hobson Talysurf-5 wth Gaussan flter, cut-off length of 0.8mm, 5 cut-offs, and total traverse length 4mm. Data acquston s accomplshed by connectng ths profler to computer and usng SESURF software. The tangental cuttng force s measured wth KstlerPezo electrc dynamometer of type-5233a wth bult n, charge amplfer up to 10 KN and a least count of 1mN. Data acquston s accomplshed by connectng ths W Wf M. R. R. = ( gms / sec) (1) t Where, W s the ntal weght of work specmen n gms; W f s the fnal weght of work specmen after machnng n gms. and t m s the machnng tme n sec. Table 2 shows L27 OA used for ths expermentaton. Table 2 Taguch L27 OA. Exp. Factors levels (coded) No. A B C D Optmzaton Utlty Theory Utlty refers to the satsfacton that each attrbute provdes to the decson maker. Thus, utlty theory assumes that any decson s made on the bass of the utlty maxmzaton prncple, accordng to whch the best choce s the one that provdes the hghest satsfacton to the decson maker (Kaladhar et m 221-3

4 Utlty Fuzzy Multobjectve Optmzaton of Process Parameters for CNC Turnng of GFRP/Epoxy Compostes al., 2011).The preference number or utlty value can be expressed on a logarthmc scale as follows: X U = A log X ` Here, s the value of any qualty characterstcs or attrbute, s the just acceptable value of qualty characterstc or attrbute and A s a constant. Value of A can be found by the condton that f (where s the optmum or best value), then therefore, A = 9 * X log X ` The ndvdual utlty values are usually aggregated to calculate the overall utlty usng the followng Eq. (4). Here, U O s the overall utlty value, U utlty value of the th s the ndvdual qualty characterstc and n s the total number of responses. W s the weght for th attrbute. Sum of all the attrbute weghts should be equal to unty. Subject to the condton: n o = = 1 U WU n = 1 W = 1 However, the problem n treatng overall utltyu O, as equvalent aggregated qualty ndex s n assgnng prorty weghts of varous responses. Extant lterature survey confrms that prevous nvestgators have determned optmal settng of process parameters by maxmzng U O wthn the expermental doman. Results obtaned by such method can be naccurate, as the exact value of prorty weght to be assgned to each and ndvdual responses s dffcult to predct. Therefore, slght change n prorty weght may shft the optmal settng, f these weghts are found senstve to predct the optma. To avod ths uncertanty, fuzzy nference system s used n the present study to couple ndvdual utltyvalues nto a sngle performance ndex.e. MPCI Fuzzy Inference System Fuzzy sets and systems were ntroduced by Prof. Lotf A. Zedah n A fuzzy rule based system conssts of four parts: Fuzzfer, knowledge base, nference engne and defuzzfer. Detaled analyss on fuzzy can be found n numerous lterature (Zadeh 1976; Mendel 1992). Ths study has made an attemptto use fuzzy nference system to estmate the MPCI, when values (2) (3) (4) (5) of U are gven as nputs to the system. The gven model s a MISO (Mult Input and Sngle Output) model as shown n Fg. 4. Fgure 4 The FIS model The number of nput varables (U ) obtaned n utlty value analyss & labelled as U 1, U 2, U 3, etc. are used as nputs. In three nputs (U ) and one output (MPCI) system, both the nputs and the output are taken n the form of lngustc format. A lngustc varable s a varable, whose values are words or sentences n a natural or man-made language. Forexample, d 1 = {low, medum, hgh}, d 2 = {low, medum, hgh}, and d 3 = {low, medum, hgh).the output (MPCI) s smlarly dvded nto MPCI = {very low, low, medum, hgh, very hgh}. Fuzzy values are determned by the membershp functons, however so far there has been no standard method for choosng the proper shape of the membershp functons for control varables. In the proposed model, Gaussan type membershp functons are used for nput as well as output varable, In ths proposed model, centrod of area (COA) method of defuzzfcaton s used for determnng the output.ths crsp value s the MPCI. Table-3 shows the observatons and calculatons of ths method. Ra ndcates the average of roughness parameter, Fz ndcates the average tangental cuttng force, and MRR ndcates the average of materal removal rate as calculated usng Eq. (1), for each of the 27 trals. U_Ra, U_Fz, and U_MRR are the ndvdual utlty values of the responses vz. roughness, tangental cuttng force and materal removal rate respectvely.mult performance characterstcs ndex MPCI values are as gven by the FIS. The Sgnal-to-Nose ratos (S/N) of MPCI are calculated usng hgher the better crtera as per Taguch method Taguch Optmzaton To determne the optmal parameter settngs, t s requred to fnd out the hghest MPCI. Optmzaton of MPCI has been carred out usng Taguch method.taguch method converts response value ntocorrespondng S/N rato. The Sgnal-to-Nose (S/N) rato s the rato of mean to devaton of the response 221-4

5 5 th Internatonal & 26 th All Inda Manufacturng Technology, Desgn and Research Conference (AIMTDR 2014) December 12 th 14 th, 2014, IIT Guwahat, Assam, Inda Table 3Utlty Fuzzy calculaton table Ex. Ra Fz MRR No. (mcrons) (N) (gms/sec) U_Ra U_Fz U_MRR MPCI S/n MPCI Fgure 5 Man effects plot for S/N ratos of MPCI 221-5

6 Utlty Fuzzy Multobjectve Optmzaton of Process Parameters for CNC Turnng of GFRP/Epoxy Compostes from targeted value. Optmal parametrc combnaton has been evaluated from the plot n Fg.5. The optmum settngs are A2B3C1D2. The estmated mean of the response characterstc S/N rato (η) could be computed by usng the followng Eq. (6), (Phadke M.S., 1989). Where = overall mean of S/N rato (η) for MPCI, A 2 = average value of S/N rato (η) for MPCI at second level of nose radus, B 3 = average value of S/N rato (η) for MPCI at thrd level of speed and C 1 = average value of S/N rato (η) for MPCI at frst level of feed. A, B & C are the most sgnfcant factors, affectng the S/N rato (η) for MPCI. η = η + (A -η) + (B -η) + ( C η) (6) opt Predcted value (S/N Rato) of MPCI becomes17.14 (hghest among all entres of values n Table 3.), whereas n confrmatory test t has been computed as18.51,thus ndcatng that the qualty has beenmproved by ths optmal settng (ncrement of S/N rato). References Har Sngh and Pradeep Kumar (2006), Optmzng mult-machnng characterstcs through Taguch's approach and utlty concept, Journal of Manufacturng Technology Management, Vol. 17 Issue 2, pp Işık B. &Kentl A. (2009), Multcrtera optmzaton of cuttng parameters n turnng of UD-GFRP materals consderng senstvty, Int J AdvManufTechnol, Vol.44, pp Jamal Y. Shekh-Ahmad (2009), Machnng of Polymer Compostes, Sprnger, New York. Kaladhar M., Subbaah K.V., RaoC.S.andRao K. N. (2011), Applcaton of Taguch approach and Utlty Concept n solvng the Mult-objectve Problem when turnng AISI 202 Austentc Stanless Steel, Journal of Engneerng Scence and Technology Revew, Vol. 4, Issue1, pp Mendel J. M. (1992), Fuzzy logc systems for engneerng: A tutoral, Proceedngs of the IEEE, Vol.83, pp Palankumar K., Karunamoorthy L. &Karthkeyan R.(2007), Multple Performance Optmzaton of Machnng Parameters on the Machnng of GFRP Compostes Usng Carbde (K10) Tool, Materals and Manufacturng Processes, Vol.21, Issue 8, pp Phadke M. S. (1989), Qualty Engneerng Usng Robust Desgn, P T R Prentce-Hall, New Jersey. Routara B. C., Mohanty S. D., Datta S., BandyopadhyayA.andMahapatra S. S.(2010), Optmzaton n CNC end mllng of UNS C34000 medum leaded brass wth multple surface roughnesses characterstcs, Sadhana, Vol.35, Issue 5, pp Zadeh L. A. (1976), Fuzzy-algorthm approach to the defnton of complex or mprecse concept, 3 Concluson In ths study, the fuzzy rule based model has been developed usng three nput varables and one output varable.e. MPCI. By ths way, a mult-response optmzaton problem has been converted nto an equvalent sngle objectve optmzaton problem, whch has been solved by Taguch phlosophy. The proposed procedure s smple and effectve n developng a robust fnsh turnng process for GFRP/Epoxy compostes. The proposed approach converts numercal response nto a lngustc term so that the ssue of response correlaton could be avoded. Wthn the selected expermental doman the optmal parameter settngs obtaned by usng ths approach are A2B3C1D2,.e. tool nose radus of 0.8 mm, cuttng speed of 200 m/mn, feed rate of 0.05 mm/rev and depth of cut of 1mm. Internatonal Journal of Man-Machnes Studes,Vol.8, pp