Journl of Industril nd Intelligent Informtion Vol., No., Jnury 0 Appliction of AHP in the Anlysis of Flexible Mnufcturing System Rjveer Singh, Prveen Shrm, nd Sndeep Singhl Ntionl Institute of Technology/Mechnicl Engineering Deprtment, Kurukshetr, Indi Emil: {rjveer.singhme0, i.prveenshrm} @gmil.com; sndeep_singhl_reck@rediffmil.com It is essentil for n orgniztion to crry out vrious mnufcturing processes in smooth nd efficient mnner, to fulfill customer demnds timely nd ccurtely []. Advnced informtion technology nd improved informtion infrstructures hve mde it possible for smooth nd result centric implementtion of flexible mnufcturing systems. Decision-mking techniques re very useful for study of flexible mnufcturing. In order to mintin competitive position in the ntionl & globl mrkets, orgniztions hve to follow strtegies to chieve shorter led times, reduced costs nd higher qulity. Therefore flexible mnufcturing nlysis plys key role in chieving corporte competitiveness nd s result of this the considertion of the right mnufcturing process tht constitutes criticl component of these new strtegies is possible. In these new strtegies, uthors re using the AHP method. The AHP is decision- iding method developed by Sty (90) nd is often referred to eponymously s the Sty method []-[]. It focuses on quntifying reltive Eigen vlues for given setoff lterntives on rtio scle. The nlyticl hierrchy process s potentil decision mking method is used in flexible mnufcturing. The AHP is decided with the behvior of decision-mker. The strength of this pproch lies in considertion of tngible nd intngible fctors in systemtic wy nd provides structured yet reltively simple solution to the decision mking problem [] for ny industry. The objective of this pper is to integrte ppliction of AHP in the flexible mnufcturing nlysis. The pper briefly reviews the concepts nd ppliction of the multiple criterion decision nlysis. This pper lso presents logicl nd systemtic procedure to evlute the bsic concepts of flexible mnufcturing processes in terms of system specifictions nd cost by using the techniques for order preference in similrity to idel AHP method. The primry need of AHP is to construct mtrix of the vribles for their pir-wise comprison, nd then the priority weights for different criteri re determined using AHP method which is subsequently used for rriving t the best decision regrding nlysis of the proper flexible mnufcturing processes using AHP method []. Abstrct In recent yers, the re of mnufcturing hs become more intensive nd competitive. Now--dys ll the service fields re ttempting to find wys to improve their flexibility by chnging their mnufcturing strtegy. The min im of Flexible Mnufcturing is to dopt effective nd efficient strtegies to fulfill the demnds of consumers. In this highly competitive globl mrket the industries re forced to focus more on incresing productivity nd qulity coupled with decresing cost by right selection of efficient mnufcturing system. Present study highlights logicl procedure to select the effective flexible mnufcturing process in terms of vrious spects s qulity improvement, fster delivery, profitbility, etc. by using Anlyticl Hierrchy Process (AHP) method. The AHP is used in flexible mnufcturing s potentil decision mking tool. The primry requirement of AHP is to mke mtrix of the vribles for their pired comprison. There re lot of AHP processes, but here only the two of them i.e. Additive Normliztion Method nd Geometric Men Method re being used by nlyzing the flexible mnufcturing with respect to micro nd mcro vribles. Index Terms flexible mnufcturing systems (FMS), AHP, multi-criteri decision mking, dditive normliztion process, geometric men process, dvnced mnufcturing technologies. I. INTRODUCTION Flexible mnufcturing is considered s cost effective process tht cn be used to perform repetitious, difficult nd unsfe mnufcturing tsks with high degree of ccurcy. Selection of proper mnufcturing process is one of the criticl issues for chieving high competitiveness in the globl mrket. The min dvntges of nlysis of proper mnufcturing process lie not only in incresed production nd delivery, but lso in improved product qulity, incresed product flexibility nd enhnced overll productivity. In this pper uthors nlyze the flexible mnufcturing for pplying the concept of AHP method []. According to the flexible mnufcturing processes, customer s utmost stisfction hs become the min objective of vrious industries & orgniztions tht hve to dopt effective nd efficient strtegies to fulfill the demnds of the customers. Flexible mnufcturing is considered s strtegic pproch to chieve the ultimte objective i.e. customer stisfction. II. In round 90 s mny product oriented deprtment produced the stndrd product in mny mchine Mnuscript received Jnury 0, 0; revised My, 0. 0 Journl of Industril nd Intelligent Informtion doi: 0.0/jiii...-0 FLEXIBLE MANUFACTURING SYSTEMS (FMS )
Journl of Industril nd Intelligent Informtion Vol., No., Jnury 0 The weightges of the fetures re obtined by clculting the Eigen vectors weights for the judgment mtrix. The yields normliztion mtrix Aw, Eigen vector c is initite out by splitting the summtion of ll the ingresses in rows i with m no. of constituents of normliztion mtrix. After computing Aw nd c, then clculte the AC s given below in the following forms. Here, C = Eigen vector, J=column, Aw= Yield normlized mtrix, I =Row = Number of elements of normlized mtrix m... im i i ()............ Aw............ m mm m... i i im mnufcturing compnies to reduce the trnsporttion time nd efforts. Thus it cn be observed s the beginning of the group technology/ flexible mnufcturing ge [9]. Group technology / flexible mnufcturing re theory of mngement tht is bsed on the principles nd the things in flexible mnufcturing my be done ccording to these principles. In the present discussion of group technology the context things include design of product, plnning, process, fbriction, ssembly, nd control of production. Generlly the group technology/ flexible mnufcturing should be pplied to ll ctivities inclusive of the dministrtive functions. The group technology / flexible mnufcturing consist of vrious principles tht divide the fcility of mnufcturing into smll groups / btches or cells of mchines. Flexible mnufcturing term in which every cell / unit is dedicted to specified fmily or group of prt types. Generlly the cell / unit re smll group of mchines or ny commodity (normlly not more thn five). In flexible mnufcturing, medium vriety, medium volume, flexible environments nd functionl configurtion of group re tken s most pproprite fctors. Flow line of flexible mnufcturing hs mixed product ssembly line system. Flexible mnufcturing hs the bsic ide bout the mnufcturing technique s clustering the products tht re mde with the sme processes/ the sme equipment nd prts re ssembled into prt fmily zone. These products cn be grouped into cell nd hence the mteril hndling requirements re minimized. III. TABLE I: IRED COMRISON OF SCALE FOR AHP PREFERENCE Intensity of importnce 9 THE ANALYTICAL HIERARCHY PROCESS (AHP) The Anlytic Hierrchy Process (AHP) ws evolved by Sty nd is often referred to eponymously, s the Sty method. In the pst reserch [0] compred AHP nd simple multi- ttribute vlue (MAV), s two of the multiple-criteri pproches. A number of criticisms hve erupted t AHP over the yers. The pproch in order to elicit the weights of the criteri by mens of rtio scle. Sty developed the following steps for pplying the AHP. Step : Specify the problem nd evlute its gol. Step : Ly down the hierrchy from the top (the objective from decision- mkers view point) through the mid levels (criteri on which subsequent levels depend) to the lowest level which usully ccommodte the set of options. Step : Evolve set of pired comprison of mtrices (size n x n ) for ech of the bottom levels with one mtrix for every constituent in the level promptly bove by dopting the comprtive scle mesurement shown in Tble I. The pired comprisons re done in terms of which constituent influences the other. Step : There re m / (m-) judgment needed to construct the set of mtrix in step. Complementry re utomticlly llocte in every pired comprison. Step : Hierrchicl incorporte is now utilized to weigh the Eigen vectors by the weights of the stndrd nd the summtion is tken overll weighted Eigen vector ingress correlting to those in the next bottom level of the hierrchy. 0 Journl of Industril nd Intelligent Informtion Definition Explntion Especilly The conformtion dvising one over the other is of excessive possible vlidity Very strongly to especilly When greement is needed Very strongly Experience nd judgment very strongly fvor one over the other. Its importnce is demonstrted in prctice very strongly Strongly to When greement is needed Strongly Modertely to strongly Modertely Eqully to modertely Eqully Experience nd judgment strongly fvor one over the other When greement is needed Experience nd judgment slightly fvor one over the other When greement is needed Two fctors contribute eqully to the objective. Eigen vector cn be clculted s per the procedure shown in the given mtrix c... m c im i i... m...... c............ m... im i i m c m () Step : In this step uthors ssemble the pir-wise comprisons nd then the consistency is resolved by pplying the Eigen vlue λmx.... m c x c x ()... m Ac.................................... m m... mm cm xm
Journl of Industril nd Intelligent Informtion Vol., No., Jnury 0 index (CI) with the proper vlue s given in Tble II. By determining proper vlue of rndom consistency index (RCI), for mtrix size using Tble II, uthor finds RCI nd computes the consistency rtio, CR, s shown. CI () CR RCI The CR is dequte, if the vlue of consistency rtio is more thn 0% or 0.0, the given judgment mtrix is uncceptble nd inconsistent nd if it is less, then judgment mtrix is consistent nd cceptble. Step : Steps - re ccomplish for ech of elevtion in the hierrchy. Now, consistency index (CI) is determined s follows m () CI mx m where m = Size of mtrix mx m ithentryin AC () ithentryin AC mx X i mci Consistency of Judgment cn be evluted by processing the consistency rtio (CR) of consistency TABLE II: RANDOM CONSISTENCY INDEX (RCI) IV. Size of Mtrix 9 0 Rndom consistency index 0 0 0.90......9 mnufcturing system depends re Qulity Improvement, Fster Delivery, Stisfction of customer, Product Vriety, Lbor Cost, Production Time, Mchine Utiliztion, Profitbility, nd therefore to simplify clcultions, these fctors re used in flexible mnufcturing processes nlysis. On the bsis of gol, criteri, nd mnufcturing, uthors re rrnged mnufcturing processes ccording to the criteri tht re tking in the mnufcturing processes nlysis. The hierrchies of mnufcturing processes re doing by selecting nd nlyzing the best mnufcturing processes on the bsis of their mnufcturing performnce. The rrngement tht is discussed in this cse study is discussed below. The hierrchy is sequenced mnully or utomticlly by the AHP softwre, nd s per the expert choice. Step-: Arrnging the pir-wise comprison nd then computing the Eigen vector for criterion such s Qulity Improvement. Step-: Clculting the Consistency rtio (CR), λmx nd Consistency index (CI). Step-: choosing proper vlue of the rndom consistency index (RCI). Step-: Scnning the consistency of the pired comprison mtrix to evlute the decision-mkers comprisons were consistent or not. LTI-CRITERIA DECISION ANALYSIS (MCDA) The elements of the problems re numerous nd the interreltionships mong the elements re extremely complicted. Reltionship between elements of problem my be highly nonliner nd chnges in the elements my not be relted by simple proportionlity. Therefore the humn vlue nd judgment system re integrl elements of flexible mnufcturing problems []. Therefore the bility to mke sound decisions is very importnt to the success of process for mnufcturing nlysis. Multiple-criteri decision mking (MCDM) pproches re mjor prts of decision theory nd nlysis. Author seeks to tke explicit ccount of more thn one criterion in supporting the decision process. The im of MCDM methods is to help decision-mkers to lern bout the problems tht they fce, to lern bout their own nd other prties personl vlue systems, to lern bout orgniztionl vlues & objectives nd exploring these in the context of the problem to guide them in identifying course of ction[]-[]. V. RESULT AND DISCUSSION Cse study: Here the nlysis is done to evlute the best flexible mnufcturing process in terms of specifictions nd cost t the opertionl level. Selecting nd nlyzing the best flexible mnufcturing processes on the bsis of performnce nd efficiency, we select the most pproprite mnufcturing process s per the uthor s expecttions. The evlution of effective flexible mnufcturing processes is bsed on the AHP method. It ims in identifying homogenous set of good systems by criticlly nlyzing ech mnufcturing process. The use of AHP method is to discriminte between the vrious flexible mnufcturing processes. These good systems cn be further evluted for the selection of the best mnufcturing processes mongst them in the decisionmking process. The min input nd output mesures for ssessing the mnufcturing process tht is considered to be effective nd hve better technicl specifictions. The technicl fetures (output) on which the performnce of 0 Journl of Industril nd Intelligent Informtion A. Additive Normliztion Method (ANM) Additive normliztion method is very populr becuse of the simple procedure of this method nd lso it is very esy to understnd. This method is lso widely used due to its simplicity. Ech constituents of mtrix is normlized by dividing every element in column by the summtion of the constituents lie in the sme column to crete the normlized pired comprison mtrix. The Eigen vector C is obtined by dividing the totl summtion of the constituents in ech row of mtrix by the number of the mtrix size. The dditive normliztion method hs three bsic steps of procedure in order to obtin the priorities or the Eigen vector. The steps for this method re s given below:
Journl of Industril nd Intelligent Informtion Vol., No., Jnury 0 Lbor Cost, Production Time, Mchine Utiliztion-, Profitbility Firstly uthors determine the mtrix tht should be mde for pired comprison with the given pproprite vribles nd then vlues should be entered on the bsis of findings for flexible mnufcturing lyout s follows in Tble III: Step : Add the vlues of ech constituent in ech column of the mtrix. Step : Split or divide every constituent in column of mtrix pired comprison mtrix by the totl summtion of the given column (vlues obtined in step ). The obtined normlized mtrix is generted t the end of this step. Step : Clculte the verge of ll the constituents in every row of the mtrix to ttin the Eigen vector C. TABLE III: CONSEQUENCE FOR FLEXIBLE MANUFACTURING LAYOUT Vrible B. Geometric Men Method (GM) This method is one of the methods implement in deriving estimtes of rtio-scles from positive reciprocl mtrix nd this lso evluted by Sty. This method is lso known by nother nme s logrithmic lest squres method or pproximte Eigen vector method. The Eigen vector is the normlized vector obtined fter process is completed. The steps for this given method re s follow: Step : Multiply every constituent in ech row nd then power of /n. Step : Summtion of ll the vlues obtined in i. Step : Divide the vlue of every row obtined by the totl summtion of the vlues in order to obtin the Eigen vector c. Now, the step first is considered for crrying out the work is to decide the determinnts on the bsis of the considered lyout tht hs to be nlyzed with the help of findings through the reserch conducted. The determinnts tht re considered during the deciding the effective nd efficient lyout re: Qulity Improvement-,Fster Delivery-, Stisfction of customer-, Product Vriety-, / / / / / / / / / / / / / / / / / / / / / / / / ½ / / ½ After prepring the mtrix uthors will convert this mtrix into stndrd mtrix, therefore the clcultion required by the dditive normliztion method implement in AHP cn be done in very simple nd esy mnner. Therefore the stndrd mtrix find for the flexible mnufcturing lyout s shown in Tble IV. Now, fter finding the stndrd mtrix, the three steps re to be obtined nd then the Eigen vectors ccording to the dditive normliztion method nd then uthors lso provide the rnk to ll vribles considered ccording to the flexible mnufcturing lyout. The performed steps re s follows: Step-: Add the vlues of ech constituent in ech column of the mtrix. TABLE IV: STANDARD MATRIX FOR FLEXIBLE MANUFACTURING LAYOUT Vribles 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. TABLE V: OBTAINED VALUES AFTER THE STEP Vribles 0.09 0.00 0.00 0.0 0.09 0.0 0.099 0.0 0. 0. 0.0 0.0 0.09 9 0.9 0. 0. 0. 0. 9 0.0 0. 0.09 0.0 0.0 0.0 0.09 0.0 0.099 0.0 0. 0. 0.0 0. 0.90 9 0. 0. 0.0 0.00 0.0 0.0 0.09 0.0 0.099 0.09 0. 0.0 0.0 0. 0.0 9 0.09 9 0. 0.00 0.0 0. 0.09 0.0 0.0 0.09 column = +++++++ = column = 0.+ ++++0.++0. =.99 0 Journl of Industril nd Intelligent Informtion column=0.+0.++0.+0.+0.+0.+0. =.99
Journl of Industril nd Intelligent Informtion Vol., No., Jnury 0 column = +++++++ = column= 0.+ 0.++0.++0.++0. =. column = +++++++ = 9 column = 0.+++0.++0.++ =.9 column = 0.+++0.++++ =. Step : Now divide every constituents of the column with the summtion of column. Authors find the given vlues fter performing step in the Tble V. Step : Now clculte the verge of ll constituents in every row of the Tble to find the Eigen vector. C=(0.09+0.00+0.00+0.0+0.09+0.0 +0.099+0.0)/ = 0.09 C=(0.+0.+0.0+0.0+0.09+ 9+0.9+0.)/ = 0. C=(0.+0.++0.++9 +0.0+0.) = 0. C=(0.09+0.0+0.0+0.0+0.09+0.0 +0.099+0.0) = 0.0 C=(0.+0.+0.0+0.+0.90+ 9+0.+0.) = 0.09 C=(0.0+0.00+0.0+0.0+0.09+0.0 +0.099+0.09) = 0.00 C=(0.+0.0+0.0+0.+0.0+ 9+0.09+9) = 0.9 C=(0.+0.00+0.0+0.+0.09+0.0 +0.0+0.09) = 0.099 The totl summtion of every Eigen vector in ech method should be equl to. The obtined vlues by uthors re lso correct s the summtion of ll Eigen vector results in. Totl sum of the Eigen vector =.000, Now, uthors clculte the vlue of λmx tht re obtined equl to. nd by implementing the vlue of it, the consistency index (CI) is clculted by using the formul: correct nd efficient. If ny firm desires to dopt the given fctors in the order find nd cn implement flexible mnufcturing in their firm for effective nd efficient outcomes. Now uthors provide rnking order to ll the fctors considered in the study tht re bsed on uthor s clcultions s shown in the Tble VI. Geometric men method of AHP techniques: In this method uthors considered Tble IV nd in this method multiply re done of ech constituent in ech row nd then power of /n. According to the bove clcultion in the Additive normliztion method, Authors do the clcultion s in the sme procedure nd now uthors provide rnking order to ll the fctors considered in the study tht re bsed on uthor s clcultions s shown in the Tble VII. TABLE VII: RANKING ORDER OF FACTORS ON THE BASIS OF EIGEN VALUES FOR FLEXIBLE MANUFACTURING BY GEOMETRIC MEAN METHOD λ mx m m CI = (.-) / (-) = 0.0 Now, uthors finlly clculte the consistency rtio (CR) by implementing the given formul s follows. CI RCI CR = 0.0/. = 0.09 TABLE VI: RANKING ORDER OF FACTORS ON THE BASIS OF EIGEN VALUES FOR FLEXIBLE MANUFACTURING BY ADDITIVE NORMALIZATION METHOD Determinnts considered Eigen vlues Rnk Qulity Improvement Fster Delivery Stisfction of customer Product Vriety Lbor Cost Production Time Mchine Utiliztion Profitbility 0.09 0. 0. 0.0 0.09 0.00 0.9 0.099 Rnk Qulity Improvement Fster Delivery Stisfction of customer Product Vriety Lbor cost Production Time Mchine Utiliztion Profitbility 0.0 0. 0. 0.0 0.0 0.0 0. 0.0 VI. CONCLUSIONS It is crystl cler nd understndble tht selection nd nlysis of n pproprite mnufcturing technique for given mnufcturing ppliction involves huge number of considertions nd the use of AHP method hs been perceived to be entirely competent nd lso computtionlly fcile to determine nd nlyze proper mnufcturing processes from given set of lterntives. This work lso lys down the mesures of the considered criteri with their reltive importnce in order to rrive t the finl rnking of the lterntives of flexible mnufcturing. Thus, this more intensive multi criteri decision nlysis tht re recognized from the AHP method nd consist the two effective nd efficient here uthors explin the concept of AHP s by clculting the vlue of CR.The vlue of CR is less thn 0% or 0.0(CR 00); therefore the vlue obtined by uthors is 0 Journl of Industril nd Intelligent Informtion Eigen vlues From the Tble VI nd Tble VII uthors nlyze tht the implementtion of dditive normliztion method nd geometric men method hve the similrity in the result tht re obtined from the bove clcultion. The rnking of these fctors re pproximtely sme in both the processes, therefore uthors concluded tht the fctors hve sme rnking in both the processes, but ech fctors hve their own rnk seprtely, thus uthors sid tht flexible mnufcturing process cn be improve nd mking effective nd efficient by dopting the these fctors ccording to their rnk nd utiliztion. Any firm dopts these fctors in orders tht re obtined in the bove clcultion nd pply/ implement flexible mnufcturing lyout in their firm for better outcomes, nd improve their flexibility, responsiveness nd lso fulfill the demnds of consumer. CI CR Determinnts considered 9
Journl of Industril nd Intelligent Informtion Vol., No., Jnury 0 [0] V. Belton nd T. Ger, On shortcoming of Sty s method of nlyticl hierrchy, Omeg, vol., no., pp. -0, 9. [] M. W. Lifson nd E. F. Shifer, Decision nd Risk Anlysis for Construction Mngement, New York: Wiley, 9. [] V. Belton, A comprison of the nlytic hierrchy process nd simple multi-ttribute vlue function, Europen Journl of Opertionl Reserch, vol., pp. -, 9. [] V. Belton, Multiple criteri decision nlysis prcticlly the only wy to choose, in Opertionl Reserch Tutoril Ppers, L. C. Hendry nd R. W. Eglese, Eds, 990, pp. -0. [] V. Belton nd T. Ger, The legitimcy of rnk reversl comment, Omeg, vol., no., pp. -, 9. [] J. S. Russell, Surety bonding nd owner contrctor prequlifiction, comprison, Journl of Professionl Issues in Engineering, vol., no., pp. 0-, 990. [] J. S. Russell nd M. J. Skibniewski, Decision criteri in contrctor pre-qulifiction, Journl of Mngement in Engineering, vol., no., pp. -, 9. processes s dditive normliztion method nd geometric men method tht cn be successfully employed for solving ny type of decision mking problems hving ny number of criteri nd lterntives in the mnufcturing domin. As future scope, n AHP methodology my be developed to id the decision mkers. The pper hs grnted the AHP s n effective decision mking method tht permits the delibertion of numerous considertions of multiple criteri. From the results nd discussion section the uthors nlyze tht the implementtion of dditive normliztion method nd geometric men method hve the similrity in the result tht re obtined from the bove clcultion. The rnking of these fctors re pproximtely sme in both the processes, therefore uthors concluded tht the fctors hve sme rnking in both the processes, but ech fctor hve their own rnk seprtely, thus uthors sid tht flexible mnufcturing process cn be improved nd mke it more effective nd efficient by dopting these fctors ccording to their rnk nd utiliztion. Any firm which dopts these fctors in the order tht re obtined in the bove clcultion nd pply towrds the implementtion of flexible mnufcturing lyout in their firm for better outcomes, nd improve their flexibility, responsiveness nd lso fulfill the demnds of consumer. Sndeep Singhl is presently working s Associte Professor in Deptt of Mechnicl Engg., Ntionl Institute of Technology (NIT), Kurukshetr, Hryn, Indi. NIT is n institution of ntionl importnce. At present he is the Chirmn of ISTE, Hryn Chpter. He is Ph.D from NIT, Kurukshetr. He hs more thn yers of teching, reserch nd professionl experience. He hs uthored more thn 0 reserch ppers in reputed ntionl & interntionl peer reviewed journls nd conferences. He hs uthored book on Entrepreneurship. His res of interest re Supply Chin Mngement, ERP, TQM, Entrepreneurship, Fcility Mngement, Productivity Mngement, Product Development etc. He hs worked with All Indi Council for Technicl Eduction (AICTE), the pex regultory body for technicl eduction in vrious cpcities for yers. He hs lso worked with Ntionl Bord of Accredittion (NBA) nd ws closely ssocited with Wshington Accord. He hs guided / guiding reserch scholrs t M.Tech nd Ph.D levels. He ws the Member Secretry for Ntionl Inititive on Institutionl Competitiveness nd worked in number of committees relted to technicl nd higher eduction. REFERENCES Athwle, A topsis method bsed pproch to mchine tool selection, in Proc. Interntionl Conference on Industril Engineering nd Opertion Mngement, Dhk Bngldesh, 00. [] V. Pthk, An integrted AHP pproch in SCM for helth centre, in Proc. Ntionl Conference on Recent Advnces in Mnufcturing, SVNIT, 0. [] T. L. Sty, The Anlyticl Hierrchy Process, New York: McGrw Hill, 90. [] T. L. Sty, Decision Mking for Leders, Belmont, Cliforni: Life Time Lening Publictions, 9. [] T. L. Sty, Axiomtic foundtion of the nlytic hierrchy process, Mngement Science, vol., no., 9. [] T. L. Sty, How to mke decision: The nlytic hierrchy process, Europen Journl of Opertionl Reserch, vol., pp. 9-, 990. [] M. J. Skibniewski nd L. Cho, Evlution of dvnced construction technology with AHP method, Journl of Construction Engineering nd Mngement, vol., no., pp. -9, 99. [] Atmni nd R. S. Lshkri, A model of mchine-tool selection nd opertion lloction I FMS, Interntionl Journl of Production Reserch, vol., pp. 9-9, 99. [9] B. Ozden, Use of AHP in decision-mking for flexible mnufcturing systems, Journl of Mnufcturing Technology Mngement, vol., no., pp. 0-9, 00. [] 0 Journl of Industril nd Intelligent Informtion Prveen Shrm is presently working s Reserch Scholr in Deptt of Mechnicl Engg., Ntionl Institute of Technology (NIT), Kurukshetr, Hryn, Indi. Rjveer Singh is presently working s PG Scholr in Deptt of Mechnicl Engg., Ntionl Institute of Technology (NIT), Kurukshetr, Hryn, Indi. 0