shaping the digital twin for design and production engineering
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Shaping the digital twin for design and productionengineering
Benjamin Schleich, Nabil Anwer, Luc Mathieu, Sandro Wartzack
To cite this version:Benjamin Schleich, Nabil Anwer, Luc Mathieu, Sandro Wartzack. Shaping the digital twin for de-sign and production engineering. CIRP Annals - Manufacturing Technology, Elsevier, 2017, 66 (1),�10.1016/j.cirp.2017.04.040�. �hal-01513846�
ShapingtheDigitalTwinforDesignandProductionEngineering
BenjaminSchleicha,NabilAnwerb,LucMathieub,SandroWartzacka
aChairofEngineeringDesign,Friedrich-Alexander-UniversitätErlangen-Nürnberg,
Martensstrasse9,91058Erlangen,Germany.bLURPA,ENSCachan,Univ.Paris-Sud,UniversitéParis-Saclay,
94235Cachan,France.
Abstract:
Thedigitalizationofmanufacturingfuelstheapplicationofsophisticatedvirtualproductmodels,whicharereferredtoasdigitaltwins,throughoutallstagesofproductrealization.Particularly,morerealisticvirtualmodelsofmanufacturedproductsareessentialtobridgethegapbetweendesignandmanufacturingandtomirrortherealandvirtualworlds.Inthispaper,weproposeacomprehensivereferencemodelbasedonthe concept of SkinModel Shapes,which serves as a digital twinof thephysical product in design andmanufacturing. In this regard,model conceptualization, representation, and implementation as well asapplicationsalongtheproductlife-cycleareaddressed.
Keywords:
Design,Tolerancing,DigitalTwin.1.IntroductionIntoday'shighlycompetitivemarkets,theambitionsforshorteningthetimetomarketandforincreasingtheproductdevelopmentperformancefueltheapplicationofsophisticatedvirtualproductmodels,whichare frequentlyreferredtoasdigital twins.Enabledbythedigitalizationofmanufacturing,cyber-physicalproduction systems,model-based systemengineering, anda growingendeavour fordata gatheringandprocessing, thesemodelsare increasinglyenrichedwithproductionandoperationdata.Moreover, theyallowtheefficientpredictionoftheeffectsofproductandprocessdevelopmentaswellasoperatingandservicingdecisionsontheproductbehaviourwithouttheneedforcostlyandtime-expensivephysicalmock-ups[1-3].Particularlyindesign,suchrealisticproductmodelsareessentialtoallowtheearlyandefficientassessmentoftheconsequencesofdesigndecisionsonthequalityandfunctionofmechanicalproducts.However, current approaches to the implementation of digital twins lack of a conceptual basis, whichhinderstheapplicabilityofthedigitaltwinvisiontovariousactivitiesindesignandproductionengineering.Motivatedbythisneed,thispaperproposesacomprehensivereferencemodel,whichservesasadigitaltwin of the physical product in design and production engineering. In this regard, important modelproperties,suchasscalability,interoperability,expansibility,andfidelity,aswellasdifferentoperationsonthis referencemodel along the product life-cycle, such as composition, decomposition, conversion, andevaluation are addressed.Moreover, the application of this referencemodel to geometrical variationsmanagementishighlighted.Thepaper is structuredas follows. In thenext section, thevisionof thedigital twinand itsevolution isreviewed.After that, a comprehensive referencemodel for thedigital twin is introduced,which is thenappliedtogeometricalvariationsmanagement.Finally,aconclusionandanoutlookaregiven.
2.TheVisionoftheDigitalTwinIthasbeenargued,that“thevisionofthedigitaltwinitselfreferstoacomprehensivephysicalandfunctionaldescriptionofacomponent,productorsystem,whichincludesmoreorlessallinformationwhichcouldbeusefulinall-thecurrentandsubsequent-lifecyclephases”[4].Inthefollowing,theevolutionofthisvisionisbriefly illustrated, recentdefinitionsof thedigital twinarediscussed,andseveralviewpointson itareaddressed.2.1.TheOriginandEvolutionoftheDigitalTwinPriortotheindustrialrevolution,physicalartefactswerepredominantlymanufacturedbyartisansresultinginuniqueinstancesofagiventemplate.However,withtheintroductionoftheconceptofinterchangeablepartsinthe18thcentury,thewayproductsweredesignedandmanufacturedrapidlychangedascompaniesbegantostriveforbuildingcopiesoftheirproducts inmassproduction.Recently,theparadigmofmasscustomizationaimsatcombiningthesetwoestablishedmanufacturingconceptstoachievelowunitcostsforcustomizedproducts.However, thoughsuchmanufacturingparadigmsallow the fabricationof largequantitiesof similar, i.e.customized,partsorproducts,thesemanufacturedinstancesaremereunrelatedcopies.Incontrasttothat,theideaofbuildingatwinreferstoproducingacopyofapartorproductandusingitforreasoningaboutotherinstancesofthesamepartorproduct-thusestablishingarelationbetweenmultiplecopies.ThisideaissaidtooriginatefromNASA’sApolloprogram,“whereatleasttwoidenticalspacevehicleswerebuilttoallowmirroringtheconditionsofthespacevehicleduringthemission”[5].However,overthepastdecades,advancementsincomputertechnologyenabledestablishingincreasinglysophisticated virtual models of physical artefacts as well as the fusion of such models for systemsengineering [6]. Thesemodels notonly serve for thedesign verification and validation [7], but are alsoincreasinglyusedasthemasterproductmodelcomprisingthemodel-baseddefinitionofrequiredproductcharacteristics[8].Moreover,theevolvementsin“microchip,sensorandITtechnologies”[9]pavedthewayfortheadventofsmartproducts,whichtrackandcommunicatetheiroperatingconditionsandthusallowto“feed”theirproductmodelswithdataabouttheirstatus,suchasenvironmentalconditionsandloads.sBesidethis,modernsensingroutines,whichgoevenbeyondgeometricalmeasurementandscanning,allowtheeasy,quick,andreliablecollectionoflargesetsofdatafromphysicalartefacts.Patternrecognition,datamining,deeplearning,reverseengineering,andotherdataanalysisapproachesmakeuseofthesedatasetsandunveildependenciesbetweenproduct,process,andoperationalcharacteristicsthatusedtobehidden.Thevastdevelopments in simulation technologyaswell as the increasingpossibilities forgatheringandexchangingdatafromproductsthusallowedforbuildingvirtualtwinsofphysicalproducts,whichfinallyledtothepresentunderstandingofthe“digitaltwin”vision.ProbablythefirstdefinitionofitwasgivenbyNASAintheirintegratedtechnologyroadmap(TechnologyArea11:Modeling,Simulation,InformationTechnology&ProcessingRoadmap; 2010),whichhasbeen slightly adapted in [10]: “ADigital Twin is an integratedmultiphysics,multiscale,probabilisticsimulationofanas-builtvehicleorsystemthatusesthebestavailablephysicalmodels,sensorupdates,fleethistory,etc.,tomirrorthelifeofitscorrespondingflyingtwin”(Fig.1).Withsomesimilaritytothis,Grievesdefinesthedigitaltwinas“asetofvirtualinformationconstructsthatfullydescribesapotentialoractualphysicalmanufacturedproductfromthemicroatomicleveltothemacrogeometricallevel”[11].
Fig.1.TheVisionoftheDigitalTwinthroughouttheProductLife-Cyclefollowing[11].
2.2.ViewpointsontheDigitalTwinBasedonthesedefinitions,itcanbefound,thatthereexistdifferentviewpointsonthevisionofthedigitaltwin.Inthiscontext,ithasbeenargued,that“fromasimulationpointofviewthedigitaltwinapproachisthenextwaveinmodelling,simulationandoptimizationtechnology”[5].However,thedigitaltwinisnotonecompletemodelofthephysicalproduct,butasetof linkedoperationdataartefactsandsimulationmodels,whichareofsuitablegranularityfortheirintendedpurposeandevolvethroughouttheproductlife-cycle[4].Thus,thedigitaltwinnotonlyservesrepresentationpurposesbutisalsoapplicableformakingpredictionsabouttheexpectedproductbehaviour[4],whilethegranularityofthesimulationmodelsfitstotheirpurposeandevolvesfromearlydesignstages,wheresimpleproductmodelsareusedtodecideaboutproductconcepts,todetaildesign,wheresophisticatedsimulationmodelssupportthedimensioninganddesignofpartsandsubassemblies.Asaresult,fromaproductlife-cyclemanagementpointofview,thereisastrongneedtointegratealllife-cycledataartefacts intoacomprehensivemanagementsystem,whichcanbeusedbyvariousactors forqueryingdata,suchasthrough-lifeperformance information,andmakingpredictionsaboutthephysicalproductfromthedigitaltwinfordesignoptimizationandmanufacturingsystemimprovement[5].2.3.CurrentIndustrialUnderstandingandApplicationsDifferentunderstandingsof the“digital twin”canbeobserved in industrialpractice,particularlybyPLMsoftwarevendors.Inthisregard,ithasbeenargued,thatPTCisfocusingonestablishingalinkbetweenthevirtualproductmodelandthephysicalparttoincreasethemanufacturingflexibilityandcompetitiveness,while Dassault Systèmes targets the product design performance by creating a platform that enablesdesignerstovirtuallybuildandinteractwithcomplexsystems.Moreover,thedigitaltwinunderstandingofGeneralElectricfocusesonforecastingthehealthandperformanceoftheirproductsoverlifetime,whereasSIEMENS strives for improved efficiency and quality in manufacturing by exploiting the possibilities oftoday’smanufacturingdigitalizationinthecontextofIndustry4.0.TESLAaimsatdevelopingadigitaltwinforeverybuiltcar,henceenablingsynchronousdatatransmissionbetweenthecarandthefactory,whileothercompaniesincreasinglyusecomplexproductmodelstoboosttheimmersioninvirtualandaugmentedrealityapplications.
PhysicalDom
ain
VirtualDom
ainDesign
Manu-
facturing
Use
2.4.SynthesisandDiscussionAsithasbeenhighlighted,thevisionofthedigitaltwinevolvedduringthelastdecadesanddescribesthevisionofabi-directionalrelationbetweenaphysicalartefactandthesetofitsvirtualmodels.Inthiscontext,the virtual “twinning”, i.e. the establishment of such relations between physical parts and their virtualmodels, enables the efficient execution of product design, manufacturing, servicing, and various otheractivities throughout theproduct life-cycle. Particularly in design, suchdigital twins allow the check forconformanceoftheproductspecificationswiththedesignintentandcustomerrequirements.However, as it has been reported in scientific literature and in practice, current limitations to theimplementationofthevisionofthedigitaltwinareinsufficientpossibilitiesforsynchronizationbetweenthephysicalandthedigitalworldtoestablishclosedloops,themissingofhigh-fidelitymodelsforsimulationandvirtualtestingatmultiplescales,thelackinguncertaintyquantificationforsuchmodels,thedifficultiesinthepredictionofcomplexsystems,aswellasthechallengesforgatheringandprocessinglargedatasets.Indeed, these challenges can only be mastered based on a sound conceptual framework and acomprehensivereferencemodelforthedigitaltwin.3.AReferenceModelfortheDigitalTwinTheneedforrealisticvirtualproductmodelsfordesignandmanufacturingactivitiesisubiquitous.However,current approaches to the implementation of digital twins lack of a conceptual basis. This hinders theapplicabilityoftheimplementationstovariousactivitiesindesignandproductionengineeringandhencehandicaps the efforts for building integrated digital twins of physical artefacts. Motivated by thisshortcoming,weproposeareferencemodelforthedigitaltwin,whichcanbeconsideredasatemplatefortheimplementationofdigitaltwinsforspecificapplicationswhileensuringimportantmodelproperties,suchasmodelscalability,interoperability,expansibility,andfidelity.3.1.BackgroundTheconceptualbackgroundofthereferencemodelisborrowedfromclassicalsolidmodellingandrecentdevelopments in ISO standards for Geometrical Product Specifications (GPS), which offer a widelyacknowledged framework for the modelling, specification, and verification of product geometry. Solidmodellinghas introduced theabstraction-representation schema to conceptualize the idealizedphysicalproduct,andtoimplementitoncomputerswithasuitablerepresentation.ISOGPSstandardsevolvedfromindustrialbest-practicesandexamplestomorerigorousconceptsandalanguagewithconsistentsyntaxandsemanticswiththeaimoftransferringthemintotheageofdigitalization.TheseconceptualizationeffortshaveledtothedevelopmentoftheGeoSpelling“language”[12]whichisbasedonsoundconceptstoallowthe unambiguous definition of geometrical specifications and to mirror specification and verificationoperationsonthegroundsofadualityprinciple.OneofthesebasicconceptsistheSkinModel,whichisanabstractmodelof thephysical interfacebetweenaworkpieceand itsenvironment [13].TheSkinmodelpermitsamentalmodeland thoughtexperiments todevelopa theoretical inspectionprocedure,henceconnecting the specificationworld to thephysicalworld. Furthermore, severalmirroredoperations anduncertainties(ambiguities,methoduncertainty,implementationuncertainty)weredefined[14].
3.2.ModelAbstractionandRepresentationThe idea behind the comprehensive reference model is to extend and transfer the above conceptualframeworkandtoconveythescientificfundamentalsofthegeometricalproductspecificationlanguagetothevisionofthedigitaltwin.Thenoveltyofthisreferencemodelistheparticularfocusonthe“twinning”betweenthephysicalandthevirtualrealm.Inthisregard,weproposetoendowthedigitaltwinwithanabstractmodelthatcomprisesallcharacteristicsandfullydescribesthephysicaltwinataconceptuallevelthroughout the whole product life-cycle. Based on this abstract model thoughts experiments can beperformed,which allows to capture andunderstand aswell as to clearly describe thephysical twin, itsbehaviouranditsenvironmentatanabstractlevel.TheexperiencesfromGPSstandardizationandrecentresearcheffortsontolerancingledtotheinsightthatonlythedifferentiationbetweentherealworkpiece,itsabstractandconceptualmodel(SkinModel),andthevirtualrepresentationofthisabstractmodelallowsforaclearunderstandingaswellasaforward-lookinglanguageforgeometricalvariationsmanagement.Consequently,theconceptofSkinModelShapeshasbeendeveloped for the virtual representation of the SkinModel based on discrete geometry representationschemes[15].Withsimilaritytothis,weproposeadifferentiationbetweentheabstractionofthedigitaltwinanditsrepresentation(Fig.2).Inthiscontext,themodelrepresentationmaydependontheparticularapplicationandcaninvolvevariousrepresentationandmodellingparadigms.
Fig.2.PhysicalTwinandReferenceModelfortheDigitalTwin(RepresentationandAbstraction).
Thedifferentiationbetweenaconceptualmodelanditsvirtualrepresentationforthedigitaltwinallowsachievingimportantmodelproperties(Table1),suchasmodelscalability,interoperability,expansibility,andfidelity.Inthisregard,theabstractmodeldescriptionenablesthedefinitionofmodeloperationsatdifferentscales,whilemodels for different interfaced parts and subassemblies of a product can be conceptuallyqueriedanddigitalproductmodelscanbeexpandedtosystemmodels.
PhysicalTwin DigitalTwin(Representation) (Abstraction)
Table1PropertiesoftheReferenceModelfortheDigitalTwin.
Scalab
ility Abilitytoprovideaninsightatdifferent
scales(fromfinedetailstolargesystems).
Interope
rability Abilitytoconvert,tocombine,andto
establishequivalencebetweendifferentmodelrepresentations.
Expa
nsibility Abilitytointegrate,toadd,ortoreplace
models.
Fide
lity
Abilitytodescribetheclosenesstothephysicalproduct.
3.3.OperationsontheReferenceModelBesidetheSkinModel,thedualityprincipleisanchoredintheISOGPSstandards.Itallowsthedifferentiationbetween a specification operator, which covers a set of operations that are used to define certaingeometricalspecificationsontheSkinModel,andtheverificationoperator,whichmirrorsthespecificationoperatorandcomprisestheoperationsthatarerequiredtoverifythespecificationsontherealpart.Thoughtheverificationoperatormirrorsthespecificationoperator,therewillalwaysremainuncertaintieswhethertheverificationoperationsfullycomplywiththespecificationoperator.Thisdualityprincipleaswellastheconceptofuncertaintiesisalsoconveyedtothereferencemodelforthedigital twin. In this regard, theapplicationof adigital twin todifferent scenariosand tasks indesignorproductionengineeringdictatestoapplycertainoperationsonthedigitaltwin.Theseoperationsdependonthe specific application and are backed by physical counterparts (such e.g. manufacturing or assemblyoperations).Theabstractionofthedigitaltwinallowsdescribingtheseoperationsonanabstractlevel,whiletheir virtual “representation” is performed employing specific simulationmodels. Due to the nature ofsimulation models, obviously, uncertainties will remain between the abstract description of a certainoperationanditsrepresentation.Weproposeheretoclassifythesetofoperationsinfourbroadcategories,namelyconversion,composition,decomposition,andevaluation.Moreover, the “twinning” between the physical world and the virtual world can be considered asobservationandpredictionphasesataconceptuallevel(Fig.3).Whiletheinformationtransferfromthephysicaltothedigitaltwinisrelatedtotheobservationandsensingofthephysicaltwin,theinformationtransferfromthedigitaltothephysicaltwinoriginatesfromscientificassumptions,simulationandvirtual
testing models, with proper handling of uncertainty, used to predict certain characteristics and thebehaviourofthephysicaltwin.
Fig.3.DifferentOperationsonthePhysicalandtheDigitalTwinthroughouttheProductLife-Cycle.4.ADigitalTwinforGeometricalVariationsManagementTheaimofgeometricalvariationsmanagementistoensurethattherequiredgeometricalcharacteristicsoftheproductaremetdespitethepresenceofgeometricalpartdeviations.Theimplementationofadigitaltwin for geometrical variations management hence requires the consideration of all different viewsthroughouttheproductlife-cyclethatrelatetothespecification,generation,verification,andpropagationofgeometricaldeviations.Foreachoftheseviewsandapplications,specificoperationsonthedigitaltwinaredefinedandmirroredbycorrespondingvirtualrepresentations.Forthispurpose,thesetofoperationsdefinedinGPS[16]areexploitedandmappedtothosethatoperateonthereferencemodel.The concept of SkinModel Shapes as a paradigm shift in computer-aided tolerancing and geometricalvariations management [17] serves as a first approach to connect these views and operations in acomprehensivemodelthatincorporatesmanufacturingprocessplanningandinspectionprocessplanning(Fig.4).Thus,animportantsteptowardsthe“twinning”betweenthephysicalworldandavirtualmodelfora digital twin in geometrical variationsmanagement has been taken,which serves as a soundbasis forongoingresearch.
Fig.4.DigitalTwinforGeometricalVariationsManagement
Observation
Prediction
PhysicalTwin
PhysicalOperations- Conversion- Composition- Decomposition- Evaluation
DigitalTwin
Operations- Conversion- Composition- Decomposition- Evaluation
TWINNING
Manufacturing Assembly InspectionDesign …
GenerationofSkinModelShapes
AssemblySimulationfor
SkinModelShapes
MeasurementofSkinModel
Shapes
FunctionalCharacteristicsand
ToleranceSpecifications
Partition FiltrationExtraction
Decomposition
Collection Construction
Composition
Association
Conversion Evaluation
Evaluation
Operations
5.ConclusionandOutlookTheabilityforassessingtheconsequencesofproduct,process,andservicingdecisionsemployingvirtualmodelsisanimportantcompetitivefactorformodernmanufacturingcompanies.Thevisionofthedigitaltwinreferstoanentangledrelationbetweenaphysicalartefactandthesetofsuchvirtualmodels.Inthispaper,thehistoryandevolvementofthevisionofthedigitaltwinaswellasitscurrentunderstandingandapplicationshavebeenportrayed.Besidethis,currentlimitationstotheimplementationofdigitaltwinshavebeendiscussedandacomprehensivereferencemodelforthedigitaltwinindesignandproductionengineering has been highlighted. Particularly, this reference model enables the clear differentiationbetween a conceptualmodel and its virtual representation for the digital twin. The application of thisreferencemodeltogeometricalvariationsmanagementhasalsobeensketched.Thebenefitofthispaperforresearchaswellasindustrialapplicationsistheprovisionofafirsttheoreticalandconceptualframeworkforthedigitaltwin,which istobeenrichedbythedesignandproductionengineeringcommunity inthefuture and which may lead to a scientific discussion about the vision of the digital twin and itsimplementationthroughouttheproductlife-cycle.References[1] LeuMC,ElMaraghyH,NeeA,OngSK,LanzettaM,PutzM,ZhuW,BernardA(2013)CADmodelbasedvirtualassemblysimulation,planningandtraining.CIRPAnn.62(2):799-822.[2] Roy R, Stark R, Tracht K, Takata S, Mori M (2016) Continuous maintenance and the future –Foundationsandtechnologicalchallenges.CIRPAnn.65(2):667-688.[3] AltintasY,KerstingP,BiermannD,BudakE,DenkenaB,LazogluI(2014)Virtualprocesssystemsforpartmachiningoperations.CIRPAnn.63(2):585-605.[4] BoschertS,RosenR(2016)DigitalTwin–TheSimulationAspect.InHehenbergerP,BradleyD(eds.):Mechatronic Futures: Challenges and Solutions for Mechatronic Systems and their Designers, SpringerInternationalPublishing,2016,59-74.[5] RosenR,vonWichertG, LoG,BettenhausenKD (2015)AboutThe ImportanceofAutonomyandDigitalTwinsfortheFutureofManufacturing,IFAC-PapersOnLine48(3):567-572.[6] Lu SC-Y, Li D, Cheng J,Wu CL (1997) AModel Fusion Approach to Support Negotiations duringComplexEngineeringSystemDesign.CIRPAnn.46(1):89-92.[7] MaropoulosP,CeglarekD(2010)Designverificationandvalidationinproduct lifecycle.CIRPAnn.59(2):740-759.[8] QuintanaV,RivestL,PellerinR,VenneF,KheddouciF(2010)WillModel-basedDefinitionreplaceengineering drawings throughout the product lifecycle? A global perspective from aerospace industry.Comput.Ind.61(5):497-508.[9] AbramoviciM, Göbel JC, Dang HB (2016) Semantic datamanagement for the development andcontinuousreconfigurationofsmartproductsandsystems.CIRPAnn.65(1):185-188.[10] Glaessgen EH, Stargel DS (2012) The Digital Twin Paradigm for Future NASA and U.S. Air ForceVehicles.Proceedingsof the53rdAIAAStructures,StructuralDynamicsandMaterialsConference,2012,Paperno.1818.[11] GrievesM,VickersJ(2017)DigitalTwin:MitigatingUnpredictable,UndesirableEmergentBehaviorinComplexSystems.InKahlenF-J,FlumerfeltS,AlvesA(eds.):TransdisciplinaryPerspectivesonComplexSystems:NewFindingsandApproaches,SpringerInternationalPublishing,2017,85-113.[12] MathieuL,BalluA(2003)GEOSPELLING:acommonlanguageforGeometricalProductSpecificationandVerificationtoexpressmethoduncertainty. InWilhelmR(ed):Proc.ofthe8thCIRPInt.SeminaronComputerAidedTolerancing.70-79.
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