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Value stream mapping 4.0

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CIRPAnnals-ManufacturingTechnology66(2017)413–416ContentslistsavailableatScienceDirect

CIRPAnnals-ManufacturingTechnology

journalhomepage:http://ees.elsevier.com/cirp/default.asp

Valuestreammapping4.0:HolisticexaminationofvaluestreamandinformationlogisticsinproductionTobiasMeudt*,JoachimMetternich,EberhardAbele(1)InstituteofProductionManagement,TechnologyandMachineTools,TUDarmstadt,GermanyARTICLEINFOABSTRACTArticlehistory:

Availableonline9June2017Keywords:ProductionAnalysisValuestreammappingValuestreammappingisawidelyusedandprovenmethodthatenablesthemappingandanalysisofprocesschainsandhelpstoderivepotentialsforimprovement.ThedigitalisationofproductionaccordingtoIndustrie4.0promisesnewopportunitiestodevelopmoreefficientproductionlines.Particularlycompanieswhichdigitallyupgradeexistingoperationsneedtobeintroducedtoanewapproach.ThisholisticapproachextendsprovenmethodsofLean-Productionwhilesystematicallymappingopportunitiesfordigitalisationtoderivemeasuresforimprovement.Acomprehensiveviewatinformation-logisticwasteisshownwhileregardingrecording,handling,processing,analysingandoptimising(information-)processes.ß2017PublishedbyElsevierLtdonbehalfofCIRP.1.IntroductionIndustrie4.0(I4.0)promisesnothinglessthanthe4thindustrialrevolution.Throughcyberphysicalsystems(CPS)anewleveloforganisation,controlthroughoutvaluechainsandcompletelifecycleofproductsisexpectedtobeachieved.Estimatedresultsaredynamic,realtimeoptimised,self-organisedproductionsystemsandnetworksthatcanbesetupaccordingtodifferentcriteria[1,2].IncontrasttoI4.0leanproduction(LP)isbasedonstandardisedprocesses,findingabnormalities,problemsolvingandcontinuousimprovementinordertoreducewasteactivitiesandtoachievehigherlevelsofflow[3,4].ParticularlycompanieswithanexistingLP-systemneedorientationhowtoreacttothenewchallengesraisedthroughI4.0.ThisarticleoffersanupgradedValuestreammapping(VSM)methodtothosecompanies.ThisallowsthemtosystematicallyunderstandopportunitiesofferedbydigitalisationandI4.0todeveloptheirleanproductionapproachtothenextlevel.Inavaluestreamamaterialflowisalwaysconnectedwithaninformationflow,e.g.toscheduleproductionortoevaluateperformanceinformation.OftendifferentIT-Systemsorevenpaperisusedtostoreinformation.Naturally,datamanagementthroughoutthevaluestreamisaccompaniedbywastefulactionsthathinderatrulyleananddigitalisedproduction.TheworldsofLP,digitalisationandI4.0areaddressedbylookingatthebasicanddigitalvaluecreationusingthevaluestreammapping4.0.1.1.Leanproduction,digitalisationandIndustrie4.0TheclassicToyotaapproachforLPisorientedtowardstheidealofawaste-freevaluestreamforallimprovementactivities:100%valueadding,0errors,onepieceflowinthesequenceofcustomerdemandandtheappreciationoftheemployees.ThebasicwayofLPisto:(1)stabiliseproductionprocesses(e.g.variantcycletimesorfrequentmachinedowntimes)to(2)preparetheconditionforproductionflowandto(3)supportthisbyacontinuousimprovementofprocesses(step1–3,Fig.1).InLPprovenmethods–asvaluestreammapping–addressproblemsina‘‘learningtosee’’manner(digitaldevelopmentpath(A),Fig.1)[4].Optimisationofproductioncanalsobesupportedbydigitalisa-tionordigitaltoolsthatsimplifyandenhanceinformationusageandavailability.AgoodexampleareAugmentedRealityworkassistancesystemstostabiliseandlevelcycletimesinemployee-intensiveareassuchasassembly.Furthermoreanacceleratedflow*Correspondingauthor.E-mailaddress:meudt@ptw.tu-darmstadt.de(T.Meudt).http://dx.doi.org/10.1016/j.cirp.2017.04.0050007-8506/ß2017PublishedbyElsevierLtdonbehalfofCIRP.Fig.1.IncorporationofIndustrie4.0approachesinleanproduction.414T.Meudtetal./CIRPAnnals-ManufacturingTechnology66(2017)413–416ofinformationcancontributeaflowofproductiontoreduceprocessingtime,e.g.byuseofe-Kanban.AgoodverticalintegrationofITsystemsineachworkspacesupportsthisstep(digitaldevelopmentpath(B),Fig.1)[1,2].TheapproachofI4.0sumsupthesedigitalsolutions.ItisbasedondigitalisationofproductionwithafocusonInternettechnolo-gies,automationandadeepintegrationofcustomersinaninterconnectedproductionweb.However,thebeneficialrelianceofdigitalisationrequirestheavailabilityofnecessaryproductiondataprovidedbyahorizontalandverticalintegrationofITsystemsaswellasdataflowsthroughoutavaluestream.ThusanefficientlayoutofvaluestreamprocessesfocusingondatamanagementisnecessaryforasuccessfulrealisationofI4.0(digitaldevelopmentpath(C),Fig.1)[2].ForcompaniesitisanidealopportunitytoanalysethepotentialsofimprovementofferedbyLP,digitalisationandI4.0.Theyaimatoptimisingavaluestreamandshouldbeunderstoodaspartsofahierarchicalimprovementmodel(seeFig.1):ExistingvaluestreamsareoptimisedusingLPmethodswhiletakingintoaccountdataflowsinordertoallowafollowingdigitalisationandimplementationofI4.0solutions.Inthisregard,thequestionarises,howLPcanincorporateI4.0approachestogetclosertothepostulatedToyotaideal.Weproposethreemainapproaches:Firstly,itisnecessarytoexaminehowtheclassicToyota7+1wastetypescanbesuitablyaddressedandreducedbyLP,digitalisationorI4.0.Secondly,informationlogisticwastes(seeSection2)mustbeanalysedandeliminated.Thirdly,theoptionsofI4.0aretobeexaminedinordertosupporttheimplementationofaleanvaluestreamaudit(Fig.1).ThehereshownmethodallowstofindsystematicallyproblembasedopportunitiesofferedbyLP,digitalisationorI4.0toreachthenextimprovementlevel.1.2.ValuestreammappingOnlyfewmethodsforoptimisingproductionofferaholisticmappinganddesignapproachsuchasthevaluestreammethodproposedbythebook‘‘Learningtosee’’byRotherandShook[5].Thebooktitleaptlydescribestheaimofvaluestreammapping:itshouldenablethesystematicidentificationofwasteinconsecutiveproductionprocessesanddetectionofimprovementpotentials.LearningtoseeisnoteasytodiscussinviewofthesubjectI4.0.Nevertheless,forthesystematicandreasonableapplicationofdigitalsolutionsfortheoptimisationofprocess,materialandinformationflows,thecurrentstateofmanufacturingmustbecaptured.Otherwiseanon-purposefuloptimisationmightbeforced.Thevaluestreammapping4.0introducedinthisarticleopensupnewpossibilities.TheclassicvaluestreammappingistherebyextendedthatithelpstograspandclearlydepictInformation-logistic-wastes(ILW)(describedbelow)aswellasdigitalimprovementopportunities.OntheonehandwastesuncoveredbyclassicvaluestreammappingareexaminedwhetherLPoradigitalsolutionleadstopossibilitiesofimprovement.Ontheotherhand,wastesarefounddealingwithdataandinformation.Thismeansforexampleredundantsystemsandmemorymediaormediabreaksarerecognisedwiththedataprocessing.2.AnewwaytoidentifyinformationlogisticalwastesInformationlogistics(IL)areunderstoodastheplanning,management,realisationandcontrolofthetotalityofinformationflowsaswellasthestorageandprocessingoftheseinformation.EspeciallyinformationflowsfordecisionmakingaretakenintoaccountforIL[6].The‘‘data-information-knowledgemodel’’describesthewayhowsignsareinterpretedasdata,arecompactedintoinformationandthentoknowledgeinordertofinallyenabledecisionmaking[7].Correspondingly,thereareindividualtypesofwaste/-categoriesthatcanoccurontheprocessfromsigns,dataandinformationtowardsknowledgeandactions.InaliteratureresearchofelevenjournalsandbooksbelongingtothedefinitionofILWwasshownthatfiveauthorscopiedthe7+1classicleantypesofwastetodescribeproblemswithinIL.Fourauthorstriedtoderivenewpointofviewsoutoftheclassicleanwastesandonlytwoauthorsdefinednewwastes.AtargetbasedapproachforanalysingIL-processes,basedonthepurposeofthedata-information-knowledgemodelwasdevelopedtogetthecategoriesofwastesalongtheinformationflowprocessatitself.Thiswasmissedinliteraturebefore.ThereforeILWwereclassifiedinthreeeasierunderstandablegroups:datagenerationandtransfer,dataprocessingandstorageanddatautilisation,whichrepresentthelifecycleofinformation.Eachgroupisdividedinmultiplesubcategories[8]:Datagenerationandtransfer:Thisgroupincludesacontinualprocessfromdataselection,overdataqualityanddatacollectiontodatatransfer.Throughthisprocessabasisissetforadditionalprocessingandutilisationofdata.Dataselectiondescribestheselectionadaptedtoinformationpurposesofdatatobecollectedespeciallywithaviewtotheutilisationofdataitself(customerperspective).Whichmeanstocollectasmuchdataasnecessaryandaslittleaspossible.Dataqualityrequiresanevaluationofdataaccordingtotheircontent,meaning,origin,use,granularity,collectionfrequency,consistency,etc.ineachcaseofaprocess.Datacollectionconsidersautomationdegreeandwhetherthedatacollectioniscompletelyautomated,semi-automated(i.e.withaninputmask)ormanual/paper-based.Especiallymanualactivitiesshouldbeavoidedandseenaswastefulactions.Datatransferincludesallmediaandsystemsinvolvedindatatransportandespeciallyconsidersdataconsistency.Mediaandsystemdiscontinuitiesshouldbeavoided.Dataprocessinganddatastorage:InLPoneofthemaintopicsistoenableacontinuousmaterialflowforexampletoreduceleadtime.Thisissuecanbesupportedbyaconstantinformationflow.ThereforesomeLPwastestypescanbetransmittedinanewcontextwithinthisgroup.Wasteinformofwaitperiodsandinventorymattersparticularlywithregardtodataavailabilityinrealtime.Latenciesinthesystemaswellasunprocesseddataleadtodelayswhichcanaffectmanufacturingprocesses.Transfer,movementandsearchincludeespeciallymanualactivitiescausedbyinefficientILthroughcomplexandpartiallynotvalue-addingtransportroutes,manualinterventionsorsearchprocesses.Informationisnotavailableinrealtime,especiallywhenitiswrittenonpaper.Datautilisation:Finallywastesaresummedupinthisgroupinconjunctionwithoverarchingtasksofdecisionsupport.Withintheframeworkofdataanalysiswastehasanimportantroletoplaybyomittingdataanalysis.Newinsights,whichenablecontinuousimprovementwithinmanufacturingprocesses,canonlybegainedbylinkingdatawithfurtheranalysis.Decision-making-support.Onlywhendataandfurtheranalysesaresuitablefordecisionmaking,itispossibletoimproveprocessescontinuously.Ideally,datawillbepreparedinawaythatFig.2.Cycleofinformationlogisticwasteanalysis.T.Meudtetal./CIRPAnnals-ManufacturingTechnology66(2017)413–4115

humangetactionsdisplayedorintuitivelyvisualisedtoselectthebestone.Evidencebaseddecisionmakingisdeterminedbyagooddatabasiswhichcanbecontinuouslyimprovedbyabetterdataselection(step1,Fig.2).Fig.2representstheiterativeprocesscycleofastructuredILW-analysis.Inthefieldofdatagenerationand-transfer,itisessentialtocreateaccurate,necessaryandglobalavailabledatasets,tohandlethemefficientlyinthefieldsofdataprocessingand–storageandtofinallyuseallcollecteddataeffectivelytogaingooddecisionmaking.3.Thesixstepsofvaluestreammapping4.0(VSM4.0)Thefocusofthemethodisthatthekindofdatacollection,thehandlingofinformation,thestoragemedia,thekeyperformanceindicators(KPI)andtheutilisationofthecollectedinformationcanberepresentedvisually.BesidesmaterialflowalsoILprocessesofavaluestreamcanbecollected,visualisedandanalysedwiththeVSM4.0.System-relevantinformationcanbeeasilyrecordedandthenotationisquicktolearnwithfewnewsymbols.FromitILWofavaluestreamcanberecognisedandmeasurescanbederived.ThesixstepsofasubstantialVSM4.0arerepresentedbelow[9].Firststep:Aclassicvaluesteammappingisconducted.Thisstepisessentialtogetageneralunderstandingofavaluestream.Atthesametimepotentialstoimprovematerialflowarerecognised,thesocalledKaizen.Kaizenincludesallactivitiestoimproveproductionprocesses,whichareideallyexerciseddailyandconsecutively[3,5].TheresultisavaluestreamrepresentationofachosenproductwithvisualisedKaizenopportunities,withfocusontheclassicToyota7+1wastes[4].RelevantKPIanddatapoints,whichaccrueduringtheorderprocessingofaproductionorlogisticprocess,arerepresentedinanextendednotationofprocessboxes,seeFig.3.Secondstep:AllstoragemediausedforrecordingofdatapointsandKPIsarelisted.Examplesforstoragemediaarepaper,employees,ERP-systems,manufacturingexecutionsystems,stor-ageofdatainotherIT-systemlikeMSExcel1,etc.Thecategoryemployeeisusedifemployeesmustnoticeinformationorrecogniseconditionsinproductionandhavetoactwithadefinedprocedure(e.g.therecognitionoflowstockwithsubsequentautonomousrestocking).Foreachstoragemediumhorizontallines,so-calledswimlanes,arepulledbelowthedrawnprocesses.Thirdstep:Datapoints,KPIsandallfurtherlocallycollecteddataofproductionandlogisticprocesseswithitsstoragemediamustbeconnectedthroughverticallinesandjunctions.Unrecog-niseddatapoints/KPIshavetobemarkedbyemptyfields.Subsequentlythetypeofdatarecordingwillbecharacterisedthroughthefrequencyofdatarecording,thetypeofrecordingandtheactualvalueofthedetermineddatapoints/KPIs(seeFig.4).Fourthstep:Itservestodeterminatetheusageofdata.InthisStepthepurposeofcollectingdatapoints/KPIsischecked.Examplesforthisareshopfloormanagement,processregulationorprocessqualification.Itcanbederivedwhichinformationiscollectedwithoutadirectusage.ForeverykindofutilisationFig.3.Boxesofvaluestreamnotation4.0.Fig.4.Valuestreammap4.0sectionofprocesslearningfactoryCiP.swimlaneswillbedrawnandconnectedverticallywiththeparametersthroughdashedlines.Datapoints/KPIswhicharealsousedbydepartmentsoutsideoftheanalysedproductionprocessaremarkedbyseparateswimlanes.Thesearenamedbytheprocessoftheexternaldepartment.Fifthstep:ThetypesofILWforallprocessesandlogisticelementsarecollected(seeSection2).ThedeterminedtypesofwastesarelistedinadefinedareaforProduction-andIL-Kaizenbelowthemarkedswimlanes(seeFig.4).Afterwastesaredescribedsubjectivelyadetailedviewontheconnectionbetweenprocessesandswimlanesisneeded.ThereforethreeKPIswillobjectiviseproblemcausesinILandtheusageofinformation.ThefirstKPIisthe‘‘DataAvailability’’(DA)withthetargettogetapercentagevalueofastandardsetofKPIsanddatapointswhicharecollectedinprocesses.Thisstandardsethastobedefinedforspecificprocessesofacompany(e.g.differentKPIsareneededformilling-,turning-orassemblyprocesses).Onlydatapointstakenintocalculationwhichbelongtothestandardsetofdatapoints/KPIstoavoidmisuse,informofcollectingjustsomedatapointstogaingoodDA-values.AgoodDA-valueisthegatewayforcontinuousimprovementprocessesanddecisionmaking.PnDAðProcessxÞ¼P1ProcessxdatapointinÂ100½%󰀃1ProcessxplanneddatapointiThesecondKPIislinkedtoDAandmeasurestheinformationusage–‘‘DataUsage’’(DU).ThisKPIaimsthateveryplanedandcollecteddatashouldbeusede.g.forcontinuousimprovementprocessesordecisionmaking.IfaKPI/datapointismultiple-usedithastobecalculatedasoneusage(binary)toavoidfalseinterpretationofDUduemultiple-usage.LowDU-valuesareanindicatorforanonKPI-drivenand/orevenworkingshopfloormanagement.PnDUðProcessxÞ¼P1ProcessxdatapointusageinÂ100½%󰀃1ProcessxplanneddatapointiThethirdKPIhelpstomeasuretheDigitalisationRate(DR)ofalldatatransmissionprocesses.Thereforethenumberofalldigitalcollecteddatapoints–withoutapaper/employeemediabreak–intheanalysedvaluestreamissummarisedanddividedbythewholenumberofcollecteddatapoints.LowDR-valuesareanindicatorfortheexistenceofwastesinthewastegroupsdatagenerationandtransformationaswellasdataprocessingandstorage.PnDRðvaluestreamÞ¼P1digitaldatapointProcessindatapointÂ100½%󰀃1allProcessi416T.Meudtetal./CIRPAnnals-ManufacturingTechnology66(2017)413–416Sixthstep:Potentialsandspheresofactivityareratedfrombothcarriedoutanalysis-resultsthroughcost-benefit-analysisandanactionplanisderivedfortheproductionimprovement.TheshowncalculatedKPIsoffertwoapproachesforimprovementactivities:eitherlookatthebottleneckprocessesorlookforthesmallestKPI-valuestostartwithprojectsforadigitalisedproduction.4.Practicalapplicationofvaluestreammapping4.0Inthecourseofeightpracticalapplicationsatwell-knownindustrialenterprisesofmechanicalengineering,electronic-,transport-andprocessindustrythemethodwasinitiallysuccessfullytested.AcompleteapplicationandvisualisationoftheVSM4.0occurredsubsequentlywithinthescopeofresearchprojectsintheprocesslearningfactoryCiPattheTechnischeUniversita¨tDarmstadt.Theresultsofthisanalysisaredescribedbelow.TheprocesslearningfactoryCiPisarealproductionfacilityinwhichforresearchaswellaseducationofstudentsandindustrypurposesavaluestreamisimplementedtoproduceindustrialpneumaticcylinders.Thecylindersaremountedineightvariants;besides,thecylinderbottomsandpistonrodsareproducedin-house,theothercomponentsarepurchased.Acustomertactof60sisassumed.ObjectiveoftheapplicationoftheVSM4.0isinthisspheretoindicatepotentialsoftheprocessstabilisation,tofindoutthecurrentstateofmanagementofinformationinthevaluestreamandtomakeinefficientandineffectiveinformationflows(ILW)clear.Subsequentlyarowofthefirstactionrecommenda-tionsisderived,byateamofexperts.ThemethodofVSM4.0wasexecutedstepbystep,withthedifferencethatinthelearningfactoryCiPnocustomerexists.Hence,enterprise-externalmaterialandinformationflowswillnotbetakenintoaccount.InthevaluestreaminformationstoragemedialikePaper,Employee,Kanban-cards/FIFO,softwareQS-stat,CAD–CAM-Soft-wareToolandERPsystemareinsertedandinformationaboutshopfloormanagementareusedforprocess/continuousimprovementandforqualitymanagementorprocessqualification,seesectioninFig.4.Thedashedlinesintheinformationflowareashowwhichcapturedinformationisused.Inthelowersectionproduction-andIL-Kaizenareappliedaccordingtothevaluestreamprocessandbuffer.Fig.4showsindetailthreeprocesses,twoFIFOlanesandasupermarketwhichincludesbothin-houseandexternalmanufacturingpartsforthedownstreamassembly.Thisvaluestreamsectionisoperatedbytwoemployees.DuringthenextstepadetailedanalysisofILofthelearningfactoryCiPwillbeexplained,withtheshownformulaofstepfive(Section3).ThereforetheKPIDAandDUwillbecalculatedforthethreeprocesses(seeTable1).ThevaluesoftheDAarebetween40and78%whichshowsthatmanagersoftheCiPdonotgetprofoundinformationtounderstandtheactualcapabilitiesofworkingprocesses.Consideringusageofthecaptureddata(KPIDU)itisnotablethatevenasmalleramountofKPIsisusedforimprovementoftheprocessesinCiP.FromallvaluestreamprocessesalargepartoftheconceivableKPIsisneitherregisterednorused.Partiallyalsorecordedinformationlikethegoodamountorprocessqualityassurancefindnouse.Thereisnocontributionmadetoimprovethesystem;whichmeansthatonedoesnotlearnfromthemistakesmade.TheDigitalisationrate(DR)oftheshownvaluestreamsectionis6%.Fig.4showsanearlycompletedataconnectionviathestoragemediapaperandemployeeswhichcausedthelowDRvalue.LowDRcanalsocauseILW,asdescribedinSection2.Inthelaststepthementionedimprovementideasaretobejudgedforcompany-individualcost-benefitratiosandhavetobeprioritisedbyateamofexpertsofacompany.FortheProcessLearningFactoryCiPe.g.thecapacitivebottleneckprocess(millingTable1EvaluationofinformationlogisticofprocesslearningfactoryCiP.MillingCleaningQualitycontrolDatapoint725Useddatapoint412Planeddatapoint958Dataavailability(DA)78%40%63%Datausage(DU)44%20%25%Theboldvalues(DAandDU)arecalculatedbyusingtheformulaofDAandDU(shownonthepreviouspage).E.g.thevalueofDAfromprocessMilling,7/9=0,778=78%andDUfromprocessMilling,4/9=0,44=44%.process)neitherOEE(overallequipmentEffectiveness)noravailabilityarecaptured.SuchaconsiderationisindispensabletodischargethebottleneckofCiP;thiscouldeasilyhappenondigitalisedwaywithoutadditionalburdenontheemployees.FurthermoreinthiscasetheCAD–CAM-chaintothemillingprocessisconnectedthroughanotworkinginterface,whileemployeeshavetoenterdatatothemachinebyaself-writtensoftwarewhichcancauseadditionalfailures,coststimeandshouldberemedied.5.ConclusionandnextstepsWiththeValueStreamMapping4.0(VSM4.0)anobjectiveandeasilyunderstandablemethodwasintroducedtoanalyseandvisualiseacurrentstateofvaluestreams,intermsofmaterialandespeciallyforinformationflows.Wastesknownbyleanproduction(LP)aswellasInformationlogisticalwastes(ILW)canbecapturedandaddressedtoprocesseswiththismethod.Thereforealsoatarget-orientedwaytoanalyseILWwasintroduced.CompanieswhichliketodigitaliseandimproveproductionprocessescanusetheVSM4.0toobtainanoverviewaboutthemainpotentialsinproductionprocessesandinformationlogistics.Withthiscombinedinformationitiseasiertoderiveabestcost-benefitratiofornextstepslikeshorttermcontinuousimprove-mentactivitiesoralongtermoptimisationproject.InsightsfromVSM4.0canalsobeusedtoexaminecertainofficeprocesses(e.g.salesordesigndepartment).Guidelinesneedtobespecifiedinordertoproperlyanalyseaconnectionbetweenofficeandproductionprocessestosubsequentlyfindfurtherwastereductionpotential.Incontinuingresearchprojectsprincipleswillbeworkedoutandclassifiedfordefiningidealstatesofinformationflows,ITinfrastructuresandguidelinesfortheusageofVSA4.0inofficeprocesses.References

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