An Empirical Study on Selection of Supply Chain Partner by Multi-Criteria Decision Making Method VIKOR - A Case of Automotive Industry

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1 K.G. Raasekaran et al. / Internatonal Journal o Engneerng and Technology (IJET) An Emprcal Study on Selecton o Supply Chan Partner by Mult-Crtera Decson Makng Method VIKOR - A Case o Automotve Industry K.G. Raasekaran 1, G.B.Bhaskar 2, S.Mural 3, M.Chandrasekaran 4 1 Research Scholar, Department o Mechancal Engneerng, Sathyabama Unversty, Chenna, Inda. kgraasekaran16@gmal.com 2 Assocate Proessor, Department o Producton Engneerng, Anna Unversty, MIT Campus, Chenna, Inda. 3 Assocate Proessor, Department o Mechancal Engneerng, Vels Unversty, Chenna, Inda. 4 Proessor, Department o Mechancal Engneerng, Vels Unversty, Chenna, Inda. Abstract:A supply chan s a network o enttes drectly or ndrectly nterlnked and nterdependent n perormng actvtes n movng a product or servce rom suppler to customer. In recent tmes, the role o purchasng n supply chan contnues to receve growng attenton. The suppler selecton process s a mult-obectves problem, encompassng many tangble and ntangble actors nclude quanttatve and qualtatve data n a herarchcal manner. In ths study, a methodology s proposed to establsh the suppler selecton crtera and rankng o selected supply chan partners based on these crtera. Ths s acheved through the employment o powerul mult crtera decson makng (MCDM) method VIKOR that wll help decson makers n the procurement to attan better qualty o products. A case study s carred out to exhbt the eectveness o the developed method n a rm nvolved n manuacturng the automotve components. Keywords: Supply chan management, suppler selecton, Mult crtera decson makng, VIKOR. I. INTRODUCTION Over the last two decades the busness envronment has been consderably changed by ncreasng trend n ntrcacy, uncertanty and unpredctablty. Organsatons are now understandng that no longer they able to mantan a compettve advantage n the markets [1]. The present compettve envronment, makng pressures on rms to adopt the eectve supply chan management [2], buld up long-term strategc relatonshps wth a capable and poneerng supplers and work n partnershp wth them n non-core process outsourcng n order to mprove overall perormance and generate sustanable compettve advantage. It ndcates that one o the competences mportant to the supply chan success s an eectve partner or suppler selecton decson. A supply chan s a system o organzatons, people, technologes, actvtes, normaton and resources nvolved n movng a product or servce rom suppler to customer. Supply chan management, whch encompasses the plannng and management o all the actvtes nvolved n sourcng, procurement, converson & logstcs management and also nclude the collaboraton wth the supplers, ntermedares, thrd-party servce provders and customers. Supply chan actvtes nvolve transormaton o natural resources, raw materals and parts nto a nshed product that s delvered to the customer. Hence, mantanng a perect supply chan across all ts operatons, thus becomes essental or any busness. Procurement or purchasng n the supply chan may be termed as the eectve acquston o goods or servces and nvolves buyng the raw materals and components or the organzaton. It s mportant that the goods or servces procured at the lowest possble prce to meet the needs o the purchaser n terms o qualty, quantty, tme and locaton. Accordng to De Boer et al. [3], a suppler selecton task conssts o our stages, namely, problem denton, ormulaton o crtera, evaluaton o supplers and nal selecton o the ultmate suppler. Based on ths background, the man purpose o the present study s to denty the supply chan partner selecton crtera and select the best suppler by rankng o supplers through MCDM method. II. RESEARCH BACKGROUND The procurement task has gan mportance n the supply chan management due to the actors such as globalzaton, ncreased value addng n supply and accelerated technologcal change. Many reasons aect a organsaton s ablty to select the rght suppler and hence there s a need to understand and realze the mportance o the suppler selecton crtera. Cox [4], dented some o the crtera whch aect the suppler selecton, such as trust and commtment, adequate nance, qualty, relable delvery tmes and adequate logstc DOI: /et/2016/v86/ Vol 8 No 6 Dec 2016-Jan

2 K.G. Raasekaran et al. / Internatonal Journal o Engneerng and Technology (IJET) and technologcal capabltes. Other crtera such as materals delvery, prce, nancal poston, communcaton, technology, consstency, credblty and product development are also studed n the prevous studes. Ths shows that the rms are shtng ther ocus rom solely concentratng on quanttatve ssues to qualtatve crtera [5].Many researchers [6] ponted out that the actors such as multple crtera, assocaton o many alternatves and nternal/ external constrants make the supply chan partner selecton process more complcated and t takes a lot o work, eort and endurance to buld up ths collaboraton. The supplers who can delver the materals or servces at rght quantty, at the rght tme, at the rght prce and at the rght qualty are termed as potental suppler. It s clear that the eectve suppler selecton must deal wth a mass o quanttatve and qualtatve actors that may be n conlct wth one another [6]. A. Suppler Selecton Crtera Stanley and Gregory [7] proposed the model or suppler selecton whch conssts o the crtera such as () Cost - ncludes purchase o materal or part, transportaton cost, taxes and operatonal costs, () Techncal capablty - ncludes supplers techncal competency, producton plannng ablty, mantenance actvtes o supplers and plant layout [5], () Qualty - reecton rate, qualty assessment n producton, nspecton and expermentaton and qualty assurance n supply chan [8]. (v) Organzatonal prole - ncludes attanment o sales and marketng goals, nancal perormance and strategy or technology age, (v) Servce level - ncludes attrbutes such as delvery, lead tme and easy o communcaton [8], (v) Suppler s prole - comprses the perormance and past hstory o the supplers ncludes nancal status, response o customers etc., (v) Rsk Factor ncludes exogenous actors such as geographcal locaton and poltcal stablty[4] help n takng decsons or the selecton o supply chan partner. Bhutta and Huq [9] ound that, explct crtera such as qualty, servce, delvery and prce and mplct crtera such as reputaton and locaton are the mportant actors that nluence the suppler selecton. Accordng to Tracey and Tan [2], the rm perormance and customer satsacton are enhanced by selecton o supplers based on the crtera such as qualty, delvery relablty and product perormance. Petron and Bragla [10] studed and evaluated the perormance o supplers based on management capabltes, producton acltes, technology, prce, qualty and delvery complance. Lammng et al. [11] recommended that the management o supplers or unctonal products must ocus on cost and qualty ssues, whereas or unque nnovatve products, the emphass s on speed and lexblty. Kotabe and Murray [12], revealed that suppler's competency, servce qualty control, transacton-cost drvers, suppler's brand mage and suppler's country characterstcs are more mportant crtera than others. Shahadat [13] ound that prce and tmely delvery are prmarly nluenced crtera ollowed by the relablty o the suppler and the qualty o products. Kannan and Tan [14] revealed that cost and prce are havng greater mpact than the suppler commtment.prevous research studes ound that the suppler evaluaton and selecton vares depends upon the actors such as products and servces, but there was a smlarty n the actor purchase decsons [15,16]. From the lterature survey, t s ound that most o the studes were consdered qualty, prce, delvery and servce as prme actors when evaluatng supply chan partners. III. MULTI CRITERIA DECISION MAKING METHODS In busness enterprses and everyday le, decsons nvolvng multple crtera are the most dcult to make and yet they are oten the most crucal. Multple crtera decson makng (MCDM) theores ntegrate logc reasonng, mathematcs, computer scence, operaton research and management to solve the problems o mult attrbutes decson makng. Identyng the crtera relevant to the decson and determnng ther relatve mportance usually requres both expert udgment and specalzed technques. The MCDM approach nvolves problem dentcaton, preerence settngs, evaluaton o alternatves and selecton o the best alternatve. The MCDM method uses many technques lke Smple Average Weght (SAW), Analytcal Network Process (ANP), Analytcal Herarchy Process (AHP), Technque or Order Perormance by Smlarty to Ideal Soluton (TOPSIS), Data Envelopment Analyss (DEA), Interruptve Structural Modelng (ISM), Hybrd approaches and VIKOR (VseKrterumskaOptmzaca I KompromsnoResene n Serban, meanng Mult-crtera Optmzaton and Compromse Soluton). Peltola et al. [17] used two decson support systems Graphc State Select (GSS) and AHP or mprovng the perormance o buyer-suppler relatonshp. Yang et al. [18] appled an ntegrated uzzy MCDM technque or solvng vendor selecton problem. Banar et al. [19] used ANP to choose best alternatve or land llng. Gencer and Gurpnar [20] proposed ANP or selectng supplers n an electronc ndustry. Shh et al. [21] proposed the TOPSIS technque to a group decson envronment. Ln et al. [22] presented a uzzy aglty ndex (FAI) based on aglty provders usng uzzy logc. Deng et al. [23] presented a moded TOPSIS method to evaluate and rank the relatve perormance o competng companes n Chna. Desheng et al. [24] proposed three technques to evaluate the rsks n the supply chan such as chance constraned programmng (CCP), data envelopment analyss (DEA), and mult obectve programmng (MOP). Many researchers have studed some other MCDM methods such as PROMOTHEE, ELECTRE and Fuzzy rankng DOI: /et/2016/v86/ Vol 8 No 6 Dec 2016-Jan

3 K.G. Raasekaran et al. / Internatonal Journal o Engneerng and Technology (IJET) methods or mult crtera decson makng problems [25, 26]. Wth ths background, ths study proposes a novel approach based on MCDM to denty the suppler selecton actors and also to select the best supply chan partner or the leadng rm engaged n manuacturng automotve products. IV. RESEARCH OBJECTIVE The man obectve o ths study s to establsh the most mportant crtera aectng the selecton o supply chan partners and to evaluate and select the potental supplers to meet rm's needs consstently n the procurement o materals and components. V. RESEARCH METHODOLOGY In ths study, the suppler selecton crtera are dented through lterature revew and branstormng wth top management steerng team o company. The outcome ths exercse results that eght crtera have been dented under a set o sx attrbutes as shown n the Table I. Then the MCDM method VIKOR s employed to acheve the nal rankng o supply chan partners. Fgure 1 ndcates the steps nvolved n the proposed methodology. And the proposed method s demonstrated through a case study nvolvng the materals procurement department o automotve products manuacturng rm. Establshment o suppler selecton crtera Lterature revew and Branstormng wth company executves Determnaton o relatve mportance o selected crtera Identcaton o supplers Rankng o supplers by employng VIKOR (MCDM) method Fg.1. Proposed Methodology VI. DESCRIPTION OF VIKOR VIKOR method was developed by Oprcovc and Tzeng [27], Faculty o Cvl Engneerng, Belgrade Unversty, SERBIA. O the varous tools, the VIKOR method s used because o the ollowng characterstcs: Best alternatve s nearest to the postve deal soluton and arthest rom the negatve-deal soluton. Best alternatve has the maxmum group utlty or decson makers and ensures the least regret. Ths method consders weghtage n crtera and the maxmum group utlty (v) n decson makng. VIKOR method determnes the compromse rankng soluton and ocuses on rankng and selectng rom a set o alternatves n the presence o conlctng attrbutes. It ntroduces the multple attrbute rankng ndexes based on the partcular measure o nearness to the deal soluton. When compared wth TOPSIS and SAW, the most mportant derence s the usage o the utlty weght v, and the value o v can be adusted accordng the atttude o decson-makers. In general, the value o v s gven 0.5 as a compromse value and the same may be larger or less than 0.5, depends upon the atttude o maorty. Tong et al. [28] ponted out that VIKOR s appled to derve an ntegrated qualty measurement o several conlctng and compromsng responses. Ln et al. [29] appled VIKOR method to make the decson on ERP system suppler selecton. DOI: /et/2016/v86/ Vol 8 No 6 Dec 2016-Jan

4 K.G. Raasekaran et al. / Internatonal Journal o Engneerng and Technology (IJET) A. Steps o VIKOR [27] Step 1.Formulaton o DecsonMatrx: The decson matrx s ormulated by a team o evaluators comprsng the executves o the company. The experts n the decson makng team wll rate every alternatve s attrbute on a scale o 1-5. The average o the entre expert s ratng s used to orm the decson matrx. Step 2.Normalzaton o DecsonMatrx: Assumng that there are m alternatves, and n attrbutes, the varous alternatves are denoted as x. For alternatve x, the ratng o the th aspect s denoted as x,.e. x s the value o the thattrbute. The normalzed value s calculated usng the equaton (1) n x 1 x 2, 1,2,... m & 1,2,... n 1 Step 3.Determne the Weghts o the Attrbutes: The weghts o the attrbutes must be calculated to express ther relatve mportance. Step 4.Determne the Best and Worst Values:For all the attrbute unctons the best value was worst value was, that s, or attrbute = 1-n, we get equatons: max mn, 1,2,... m, 1,2,... m where s the postve deal soluton (PIS) or th crtera and 2 3 and the s the negatve deal soluton (NIS) or th crtera. Step 5.Compute Dstance o Alternatves to the Ideal Soluton:Ths step s to calculate the dstance rom each alternatve to the postve deal soluton and the negatve deal soluton usng the equatons(4) and (5). S n 1 w R max w 4 5 Step 6.Calculate the VIKOR values:the VIKOR values Q or =1,2,,m, are calculated usng the equaton(6) Q v S S S S R R 1 v R R Where S - = max S, S =mn S, R = mn R,R - = max R and v s the weght o the strategy o the maorty o crtera (or the maxmum group utlty ) relectng the atttude o the decson makers. Step 7.Rank the alternatves by Q values: Accordng to the Q values calculated by step (4), we can rank the alternatves and thereby make the decson. VII.CASE ANALYSIS In ths study, the case company under consderaton s one o the leadng automotve glass products manuacturng company located n South Inda, oerng varous types o automotve products and servces. A case study on selecton o supply chan partners n an automotve ndustry s conducted to valdate and llustrate the easblty o the proposed VIKOR method. The case company purchases large number o raw materals and components rom the outsde. Whenever the quantty o these tems alls below a sgncant level, the procurement department places an order to any one o the supplers rom the database. Ths process happens n an unorganzed manner and thereby the company aces problems n mantanng qualty, delvery, relablty, new product development, etc. The company has a lst o seven supplers say A1, A2, A3, A4, A5, A6 and A7 or the supply o these tems. O these supplers, the company places the order to the suppler say or example A3 randomly wthout takng nto account ts ablty regardng qualty, delvery tme, perormance hstory, techncal capablty, etc. On delverng these tems, the reecton levels were ound to be 66.67% and the responsveness to new product development was also ound to be low thereby denotng poor qualty and poor 6 DOI: /et/2016/v86/ Vol 8 No 6 Dec 2016-Jan

5 K.G. Raasekaran et al. / Internatonal Journal o Engneerng and Technology (IJET) techncal competence. Thus the company aces problem n selectng the rght vendor or each component o ther product.hence, the company needs to mplement more accurate and eectve method or selectng the rght suppler n order to mantan the qualty and thereby enhancng the customer satsacton. In ths study, the suppler selecton crtera are dented through lterature revew and branstormng wth top management steerng team o company (decson makers) whch are presented n the Table I. Dmensons Qualty TABLE I. SET OF ATTRIBUTES AND CRITERIA Crteron Weght % C1. Durablty 30 C2. Reecton levels 15 Cost C3.Value Cost Reducton 10 Delvery Servce C4.Geographcal Locaton 7 C5.Lead Tme 7 C6. Readness to accept and replace the reectons 15 C7. Cooperaton n case o emergences 8 Management C8. Suppler evaluaton audt score 8 There are 7 alternatves and 8 attrbutes or the materals o glass products. (A represent th alternatve, = 1,2,,7,C represents the th attrbute, = 1,2,,8). Let the alternatves be the supplers A1, A2, A3, A4, A5, A6 and A7 and the crtera be C1: Durablty; C2: Reecton levels; C3: Value Cost Reducton; C4: Geographcal Locaton; C5: Lead Tme; C6: Readness to accept and replace the reectons; C7: Cooperaton n case o emergences and C8: Suppler evaluaton audt score. The team o evaluators (decson makers) comprsng the managers o varous departments such as purchase, qualty control, product engneerng and producton engneerng o case company determned the weghts o the attrbutes based on the respectve crtera to express ther relatve mportance whch s depcted n the Table I. Each and every alternatve s th attrbutes are evaluated wth 1-5 ponts by evaluators; One can get the average mark o th alternatve s th attrbute and thus the decson matrx ormulated by the expert team s gven n the Table II. TABLE III. DECISION MATRIX C1 C2 C3 C4 C5 C6 C7 C8 A A A A A A A Table III shows the resultant normalzed matrx, accordng to ormula (1). TABLE III. NORMALISED MATRIX Accordng to the equatons(2) and (3), the results are shown n the Table IV. DOI: /et/2016/v86/ Vol 8 No 6 Dec 2016-Jan

6 K.G. Raasekaran et al. / Internatonal Journal o Engneerng and Technology (IJET) TABLE IV. BEST AND WORST VALUES C1 C2 C3 C4 C5 C6 C7 C8 w A A A A A A A Table V shows the results, accordng to the equatons (4) and (5). TABLE V. DISTANCES OF S I ANDR I Alternatve Dstance o PIS (S ) Dstance o NIS (R ) A A A A A A A TABLE VI. VIKOR VALUES Alternatve V- value Q Rankng A A A A A A A Note: In general v = 0.5 And the VIKOR values are calculated usng the equaton (6) and are presented n the Table 6. From the Table VI, t s clear that Q4 > Q1 > Q5 > Q6 > Q7 > Q3 > Q2 and hence the rankng s shown n the Table 7. As can be seen n Table VII, alternatve A4 s ranked rst and alternatves A1, A5, A6, A7, A3 and A2 are ranked second, thrd, ourth, th, sxth and seventh respectvely. Thus t s clear that alternatve 4 s the best suppler and alternatve 2 s the worst selecton. DOI: /et/2016/v86/ Vol 8 No 6 Dec 2016-Jan

7 K.G. Raasekaran et al. / Internatonal Journal o Engneerng and Technology (IJET) TABLE VII. RANKING OF ALTERNATIVES Alternatves Rank A4 1 A1 2 A5 3 A6 4 A7 5 A3 6 A2 7 Hence, t s ound that the VIKOR method s very approprate or supply chan partners selecton. By ths method, the case company acqured the best partners and also can exemply the approach o decson-makers by adustng the value o utlty weght v. The VIKOR method realzes the combnaton o quanttatve and qualtatve analyss, whch makes t, be a better MCDM method than others. VII. SOFTWARE DEVELOPMET The above evaluaton s very specc and has been done only or case organzaton. In order to make the rankng generc, smple sotware has been developed by usng C language. When any changes n perormance o supplers on selecton crtera, the entre process or rankng o supplers s to be carred out agan or ndng out the best suppler. Now t s elt that a standard smulaton sotware whch could perorm the above processng steps s essental or mnmzng the tme and cost o selecton process. Wth ths am, the standard sotware TC (Turbo C) was developed n to meet the current requrement. Ths sotware package can be smulated several numbers o tmes wth changng the values o the nput parameters to get optmal soluton. VIII. CONCLUSION Evaluaton and selecton o supply chan partners s a-crtcal busness competency. Industral rms use these results as a means to oster communcatons and a startng pont or suppler development and perormance mprovement. In ths study, an attempt has been made to optmze the supply chan partner by nvolvng MCDM method VIKOR. The best supply chan partner selected by VIKOR method s ound to be closer to the postve deal soluton and arthest away rom the negatve deal soluton and hence more accurate suppler ratng can be obtaned when compared to any other method. Wth the am o mnmzng the tme and cost o suppler selecton process, sotware was developed by usng C language consderng varous actors such as qualty, cost, delvery, servce and management as nput to select the best suppler as an output. REFERENCES [1] R.B. Handeld, and E.L. Nchols, Introducton to Supply Chan Management, Prentce-Hall, NJ [2] M. Tracey and C.L.Tan, Emprcal analyss o suppler selecton and nvolvement, customer satsacton, and rm perormance,supply Chan Management: An Internatonal Journal, vol. 6 (4), pp ,2001. [3] De Boer, E.Labro and P.Morlacch, A revew o methods supportng suppler selecton, EuropeanJournal o Purchasng and Supply Management, vol. 7(2), pp [4] A.Cox Power, Value and SCM, Supply Chan Management: An Internatonal Journal, vol.4(4), pp [5] L.H. Harps, The Haves and the Have Nots: Supply Chan Practces or the New Mllenum, Inbound Logstcs Journal, pp [6] R.Vera, and M.E.Pullman, An analyss o the suppler selecton process, Omega: Internatonal Journal o Management Scence, vol. 26(6), pp [7] E.G.Stanley, and M.M. Gregory, 2001, Achevng World Class Supply Chan Algnment: Benets, Barrers and Brdges, A CompledResearch Report [8] B.Beamon, Measurng supply chan perormance, Internatonal Journal o Operatons and Producton Management, vol.19 (3), pp [9] K.S.Bhutta, and F.Huq, Suppler selecton problem: a comparson o total cost o ownershp and analytcal herarchy process approach, Supply Chan Management: An Internatonal Journal, vol.7, pp [10] A.Petron, and M.Bragla, Vendor selecton usng prncpal component analyss, Journal o Supply Chan Management, vol. 36(2), pp [11] R.C. Lammng, T. Johnsen, J.Zheng, and C.Harland, An ntal classcaton o supply networks, Internatonal Journal ooperatons and Producton Management, vol. 20(6), pp [12] M.Kotabe, and J.Y.Murray, Outsourcng Servce Actvtes, Journal o Marketng Management, vol.10(1), pp [13] K.Shahadat, Suppler choce crtera o executng agences n developng countres, Internatonal Journal o Operatons andproducton Management, vol. 16(4), pp [14] V.R. Kannan, and K.C.Tan, Atttudes o US and European managers to suppler selecton and assessment and mplcatons or busness perormance, Benchmarkng: An Internatonal Journal, vol.10(5), pp [15] M. Bevlacqua, and A.Petron, From tradtonal purchasng to Suppler Management: A Fuzzy Logc- based approach tosupplerselecton, Internatonal Journal o Logstcs Research and Applcatons, vol. 5(3), pp [16] C.Kahraman, U. Cebec, and Z.Ulukan, Mult-crtera suppler selecton usng uzzy AHP, Logstcs Inormaton Management, vol. 16(6), pp DOI: /et/2016/v86/ Vol 8 No 6 Dec 2016-Jan

8 K.G. Raasekaran et al. / Internatonal Journal o Engneerng and Technology (IJET) [17] S. Peltola, M. Torkkel, and J.Tumala, Integratng GSS and AHP: experences rom benchmarkng o buyer-suppler relatonshps,proc. 35th Hawa Internatonal Conerence on System Scences, IEEE Computer Socety, pp [18] J.L.Yang, H.N.Chu, G.H. Tzeng, and R.H. Yeh, Vendor selecton by ntegrated uzzy MCDM technques wth ndependent and nterdependent relatonshps, Inormaton Scences, vol. 178(21), pp [19] M. Banar, B.M.Köse, A. Özkan, and I.P.Acar, Choosng a muncpal landll ste by analytc network process, Envronmental Geology, vol. 52(4), pp [20] C.Gencer, and G.Gurpnar, Analytc network process n suppler selecton: A case study n an electronc rm, AppledMathematcalModelng, vol. 31(11), pp [21] H.S.Shh, H.J. Shyur, and E.S.Lee, An extenson o TOPSIS or group decson makng, Mathematcal and Computer Modelng,vol. 45(7-8), pp [22] C.T.Ln, H.Chu, and P.Y.Chu, 2006, Aglty ndex n the supply chan, Internatonal Journal o Producton Economcs, vol. 100(2), pp [23] H. Deng, C.H.Yeh, and R.J. Wlls, Inter-company comparson usng moded TOPSIS wth obectve weghts, Computers & Operatons Research, vol.27 (10), pp [24] Wu. Desheng, and L.O. Davd, Supply chan rsk, smulaton, and vendor selecton, Internatonal Journal o Producton Economcs, vol. 114(2), pp [25] E. Trantaphyllou, Mult-Crtera Decson Makng Methods: A Comparatve Study, Dordrecht: Kluwer Academc Publshers [26] S.Oprcovc, and G.H.Tzeng, Compromse soluton by MCDM methods: a comparatve analyss o VIKOR and TOPSIS,European Journal o Operatonal Research, vol. 178, pp [27] S.Oprcovc, and G.H.Tzeng, Compromse soluton by MADM methods: A comparatve analyss o VIKOR and TOPSIS, European Journal o Operatonal Research, vol.156(2), pp [28] L.I. Tong, C.C.Chen, and C.H.Wang, Optmsaton o mult-response processes usng the VIKOR method, InternatonalJournalo Advanced Manuacturng Technology, vol.31, pp [29] J.H.Ln, G.H. Tzeng, and W.L.Jen, Utlzng VIKOR to make ERP system suppler selecton decson, Agrculture and Economcs, vol. 34(11), pp AUTHOR PROFILE K.G.Raasekaran obtaned hs Bachelor s degree n Mechancal Engneerng rom Madras Unversty, Chenna, Inda, Master s degree n Computer Aded Desgn rom Anna Unversty, Taml Nadu, Inda and currently dong Ph.D n Mechancal Engneerng at SathyabamaUnversty, Chenna, Tamlnadu,Inda. Hs specalzaton ncludes Supply Chan Management and Product Desgn and Development. Dr. G.B.Bhaskar s an Assocate Proessor at the Department o Producton Engneerng, Anna Unversty, MIT Campus, Chenna, Taml Nadu, Inda. He receved hs Ph.D degree n Mechancal Engneerng rom Anna Unversty, Chenna, Tamlnadu, Inda, Master degreen Manuacturng Engneerng rom IIT Madras, Tamlnadu, Inda, and Bachelor degree n Mechancal Engneerng rom Madras Unversty, Taml Nadu, Inda.Hs areas o nterest nclude Supply Chan Management, Product Desgn and Development, Composte Materals, Manuacturng. Dr.S.Mural s an AssocateProessor at the Department omechancal Engneerng, Vels Unversty, Chenna, Tamlnadu, Inda. He receved hs Ph.Ddegree n Manuacturng Engneerng, Bachelor and Master degreen Producton Engneerng rom Annamala Unversty,Chdambaram, Taml Nadu, Inda. He receved hs MBA degree rom Bharathdasan Unversty, Trchy, Taml Nadu,Inda. Hs areas o nterest nclude Producton/ServceOperatons Management, Statstcal Applcatons tomanuacturng and Supply Chan Management, Product Desgn and Development and Materals Processng. Dr.M.Chandrasekaran s Proessorand Drector o Department o Mechancal Engneerng, Vels Unversty, Chenna, Tamlnadu, Inda.He completed hs Master s and Doctorate degree n Producton Engneerng at Natonal Insttute o Technology, Trchy, Inda. Hs areas o nterest nclude Schedulng, Mult Obectve Optmzaton, Supply Chan Management, Computer Integrated Manuacturng and Compostes. DOI: /et/2016/v86/ Vol 8 No 6 Dec 2016-Jan