روش های فازی برای گسترش کارکرد کیفیت برای طراحی محصول جدید

For new product development, quality function deployment (QFD) is a useful approach to maximize customer satisfaction. The determination of the fulfillment levels of design requirements (DRs) and parts characteristics (PCs) in phases 1 and 2 is an important issue during QFD processes for new product design. Unlike the existing literature, which mainly focuses on the DRs, this paper proposes fuzzy nonlinear programming models based on Kano's concept to determine the fulfillment levels of PCs with the aim of achieving the determined contribution levels of DRs in phase 1 for customer satisfaction. In addition, to deal with the design risk, this study incorporates failure modes and effects analysis (FMEA) into QFD processes, and treats it as the constraint factor in the models. To cope with the vague nature of product development processes, fuzzy approaches are used for both FMEA and QFD. The applicability of the proposed models in practice is demonstrated with a numerical example.

Quality functiondeployment(QFD)isausefulcustomer-drivenproductdevelopmenttoolfortranslatingtheneeds of thecustomerintoefficientcommunicationthroughthevariousstagesofproductplanning,design,engineering,and manufacturingtoachievehighercustomersatisfaction.QFDwasconceivedinJapaninthelate1960sbyAkaoand then disseminatedworld-wide [1]. Ithasbeensuccessfullyintroducedinmanyindustriestoimproveproductdesign, decision makingprocess,andcustomersatisfaction [12,16,22]. AtypicalQFDprocessconsistsoffourphases.Inthe newproductdesignstage,aQFDteamisorganizedtoimplementthefirsttwophases,i.e.,productplanningandpart deployment,ofQFDprocesses,whichmirrortheproductdesignprocesstoachievegreatcustomersatisfaction.The twophasesarecloselyrelatedatthedesignstage,sincetheoutcomefromthelatterphaseshouldmakethedecisions from theformerphaseapplicable.However,mostoftheexistingliteratureonlyfocusesonthefirstphaseofQFD,so this studywillconsiderthetwophasesinQFDactivitiesforanewproductdesign.The houseofquality(HOQ)isanimportanttoolforQFDactivities,containinginformationon“what”,“how”, relationship between“what”and“how”,and,therelationshipbetweenthe“how”factorsthemselves.Forexample,for the developmentofphase1,theQFDteamdeterminesasetof“what”,i.e.,customerrequirements(CRs),and“how”, i.e., designrequirements(DRs),thataffectCRs,andthenconstructstherelationstrengthbetweenCRsandDRsandthe relationships betweentheDRsthemselves.TheobjectiveofthefirstphaseistodeterminethefulfillmentlevelofDRs to maximizethecustomersatisfaction.Inphase2,theDRsareconsideredas“what”,andpartscharacteristics(PCs) are “how”factorsdesignedtomaximallyachievetherequirementlevelofDRs.IntraditionalQFD,themeasurements of importanceof“what”andtheassociatedrelationshipsareassessedonascalesystemsuchas1–3–9,or1–5–9, indicating “weak”,“moderate”,and“strong”,respectively [11,16]. Nevertheless,gatheringsufficientknowledgeand information aboutthemeasurementsisusuallydifficult [9,10]. Thishasledtotheintroductionoffuzzyapproaches into QFDstudies [5,6,9,10,18]. However,theseexistingstudiesstillsufferfromanumberofdrawbacksinapproaches and methodologies,asmentionedbyChenandWeng [9]. In practice,effectivedesignprocessescanleadtotheachievementofmaximumcustomersatisfaction.Forinstance, in phase1ofQFD,DRsareabletoachievebettereffectivenessofthedesignplanningwhentheirperformanceishighly correlated withCRstomeetexternalcustomersatisfaction.TheeffectofPCsonDRsinphase2iscomparabletothat of DRsonCRs.However,thefulfillmentlevelsofDRsandPCsarenotnecessarilyproportionallyconsistentwithCRs’ and DRs’satisfaction,respectively.Kanoetal. [17] proposed thatqualityperformanceofaproductorservicehasthree differentrelationships(i.e.,attractive,one-dimensional,andmust-be)withcustomersatisfaction.Someresearchers incorporated Kano’sideaintoQFDforassigningweightstodifferent“what”toexplainhowtheyimpactcustomer satisfactionindifferentways [15,25,30–32]. Instead,recentlyChenandKo [8] adopted Kano’sconcepttocategorize DRs intheirfuzzymodels.Referringto [8], thisstudyappliesKano’sconcepttoclassifyvarious“how”intothree categoriesbasedontheirimportanceranking,sincetheperformanceofvarious“how”achievesdifferentlevelsof external/internalcustomersatisfaction. Furthermore, inordertodecreaserisksinherentinofnewproductdesign,theriskanalysisofDRsisnecessaryatthe design stageofnewproductdevelopment.Theoutcomesofphase1,i.e.,thefulfillmentlevelsofDRs,areappliedto phase 2astheconstraintfactorsindeterminingtheachievementlevelsofPCs.Withthisconsideration,failuremodeand effectanalysis(FMEA)isappliedforriskanalysis.TheinfluenceofDRs’risklevelsonPCsinphase2isconsideredin the decisionmodels.FMEAisasystematictechniqueforidentifying,prioritizingandactingonpotentialfailuremodes before thefailuresoccur.SeveralresearchershavediscussedFMEAanditsapplicationstoQFD [2,13,29,30]. However, these studiesareonlylimitedtodescriptiveanalysestoobtainthequalityandresourcebenefits.Themethodstocarry out theaggregationoftheQFDandFMEAarenotmentioned,andtheuncertaintyatthenewproductdesignstageis not considered,either.Inthisstudy,weconstructthefuzzynonlinearmathematicalprogrammingmodels,referringto Kano’sconceptinphase1;furthermore,weintroduceFMEAintothefuzzyQFDapproach,andproposeanideato link thefunctionrelationshipbetweenphases1and2oftheQFDindeterminingtheachievementlevelsof“how”in phase 2tomaximizetheinternalandexternalcustomersatisfactionundertherelevantconstraints.Anexampleofa semiconductor packingcaseisgiventoillustratetheproposedmodels. In thefollowingsection,afuzzyapproachtoQFDisintroduced.InSection3,afuzzynonlinearmodelinphase1 of theQFDprocessisproposedbasedonKano’sconcepttocategorize“how”intothreecharacteristics.Inthefourth section, thefuzzyFMEAapproachisintroducedandafuzzynonlinearprogrammingmodelisdevelopedtodetermine the achievementdegreeofPCs,constrainedbytheneedofDRsinphase1andtheriskratingofPCsaccordingto the developmentofFMEAonDRs.Anexampleofasemiconductorpackingcaseispresentedtodemonstrateour approaches inSection5.Finally,theconcludingremarksareprovidedinSection6.

Determining thefulfillmentlevelsofthe“how”isanimportanttaskinthefirsttwophasesoftheQFDprocesses, when QFDisappliedtothenewproductdesign.However,mostrelatedstudieshaveonlyfocusedonthepriorityor achievementlevelsofDRsinphase1.Unliketheexistingresearchworks,bothphases1and2areconsideredinthis paper.ConsideringKano’sconcept,thispaperproposesafuzzynonlinearmodeltodeterminetheperformancelevels of the“how”basedontheexistingfuzzylinearmodel.The“how”canbecategorizedintothreeclassesbasedonKano’s concept. Throughthemodificationofthedecisionvariablesdenotingtheperformancelevel,thefuzzynonlinearmodels can beconstructedforphases1and2inafuzzyenvironment.Comparedwithfuzzylinearmodelswithoutconsidering Kano’sconcept,fuzzynonlinearmodelscanachievebettersatisfactiondegree. Toreducethedesignrisk,riskanalysisofDRs,namelyafuzzyFMEA,istakenintoaccountinthephase2modelas a constraintfactor.Inaddition,thispaperconsidersthecloselinkbetweenthetwophasestobuildupafuzzynonlinear programming modelforphase2indeterminingthefulfillmentlevelsofPCs.ThesatisfactionofDRj determined in phase 2isgreaterthanorequaltothecontributionofDRj in phase1inordertorealizecustomersatisfaction.The proposed modelisillustratedwithanumericalexampletodemonstrateitsapplicabilityinpractice.Theresultingranges of satisfactiondegreesandthepossiblerangesoffulfillmentlevelsofthe“how”inbothphasescanprovidetheQFD team withusefulinformationfornewproductdesign.BesidesKano’sconceptandFMEA,infutureresearchother considerations, suchasmeans-endchain(MEC),theintegrationofmorephasesofQFDactivity,andsoon,couldbe modeled intheQFDprocessesforthenewproductdesignanddevelopment.Inaddition,moreelaborateapproaches could bedevelopedtosolvetheproblem,inwhichallfuzzyevaluationsareusedasinputsinthemodelsinorderto obtain completeinformation.