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外文翻译--越智能制造新一代柔性智能数控机 英文版.pdf

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外文翻译--越智能制造新一代柔性智能数控机 英文版.pdf

tionandselfhealingwillbepresentedwithgreatfeaturesaswellaschallengesrelatedtozeroofintelligentbenefitsTheMachiningprocessmonitoringandcontrolisacoreconceptonwhichtobuildupthenewgenerationofflexibleselfoptimisingintelligentNCmachines.Inprocessmeasurementandprocessingoftheinformationprovidedbydedicatedsensorsinstalledinthemachine,enablesautonomousdecisionmakingbasedontheonlinediagnosisofthecorrectmachine,workpiece,toolandmachiningprocesscondition,leadingtoanincreasedmachinereliabilitytowardszerodefects,togetherwithhigherproductivityandefficiency.Indeed,themainsensingandprocessingtechniquesintheliterature3–5focuson0094114X/seefrontmatterC2112008ElsevierLtd.Allrightsreserved.Correspondingauthor.Tel.441612003804.Emailaddresss.mekidmanchester.ac.ukS.Mekid.MechanismandMachineTheory442009466–476ContentslistsavailableatScienceDirectMechanismandMachineTheorydoi10.1016/j.mechmachtheory.2008.03.006underverytightconditions1,2.Themachinetoolindustryisrespondingtoanumberofrequirements,e.g.e_commerce,justintimeproductionandmostimportantlyzerodefectcomponent.Thisisfacilitatedbyintegratingnewmaterials,designconcepts,andcontrolmechanismswhichenablemachinetoolsoperatingathighspeedwithaccuraciesbelowthan5lm.Howevertheintegrationofhumanexperienceinmanufacturingtowardsflexibleandselfoptimisingmachinesiswidelymissing.Thiscanbeachievedbyenhancingexistingcomputingtechnologiesandintegratingthemwithhumanknowledgeofdesign,automation,machiningandservicingintoemanufacturing.Thenextgenerationwillbedescribedasnewintelligentreconfigurablemanufacturingsystemswhichrealisesadynamicfusionofhumanandmachineintelligence,manufacturingknowledgeandstateoftheartdesigntechniques.Thismayleadtolowcostselfoptimisingintegratedmachines.Itwillencompassfaulttolerantadvancedpredictivemaintenancefacilitiesforproducinghighqualityerrorfreeworkpiecesusingconventionalandadvancedmanufacturingprocesses.1.IntroductionComplexcomponentmachinedwithlengerequiredforthenewgenerationuctsandprocessesofferssubstantialhigherqualityandbetterreliability.variousaspectsofthenextgenerationofintelligentmachinetoolcentres.C2112008ElsevierLtd.Allrightsreserved.defectsisatopperformanceinmassproductionanditbecomesanewchalmachinetools.Increasingtheprecisionandaccuracyofmachines,prodtoawiderangeofapplicationsfromultraprecisiontomassproductionwithrecentdevelopmentofultraprecisionmachinesisreachingnanometreprecisionBeyondintelligentmanufacturingAnewgenerationofflexibleintelligentNCmachinesS.Mekida,,P.Pruschekb,J.HernandezcaTheUniversityofManchester,SchoolofMechanical,AerospaceandCivilEngineering,ManchesterM601QD,UKbInstituteforControlEngineeringofMachineToolsandManufacturingUnits,UniversityofStuttgart,GermanycIDEKOTechnologicalCentre,ArriagaKalea,220870Elgoibar–Gipuzkoa,SpainarticleinfoArticlehistoryReceived30November2006Receivedinrevisedform3March2008Accepted4March2008Availableonline29April2008abstractNewchallengesforintelligentreconfigurablemanufacturingsystemsareontheagendaforthenextgenerationofmachinetoolcentres.Zerodefectworkpiecesandjustintimeproductionaresomeoftheobjectivestobereachedforbetterqualityandhighperformanceproduction.Sustainabilityrequiresaholisticapproachtocovernotonlyflexibleintelligentmanufacturebutalsoproductandservicesactivities.Newroutesphilosophyofpossiblemachinearchitecturewithcharacteristicssuchashybridprocesseswithinprocessinspecjournalhomepagewww.elsevier.com/locate/mechmtOntheotherhand,specialattentionhastobepaidtothelatterprocesscontrolstrategiesACO.CharacteristicexamplesS.Mekidetal./MechanismandMachineTheory442009466–476467canbefoundat15–19.Themainfunctionalityprovidedbysuchcontrolsystemsisthepostprocessselfoptimisationofprocessparametersetupi.e.feeds,depthsofcut,etc.,withtheobjectiveofsetuptimeminimisation,processknowledgemanagementandprocessoptimisation,towardsflexiblejustintimeproduction.Withtheinprocessmonitoringofprocessperformanceandthepostprocessmeasurementoftheresultingpartquality,aknowledgebasedprocessmodelisusedtodeterminethenewoptimisedsetofcuttingparameters,enablingautonomousselfoptimisation.Inthesameway,asaprevioussteptooptimisation,ACOsystemsarealsoappliedtoselectthefirstprocesssetupfornewpartqualityandprocessrequirements.Therefore,ifaflexibleintelligentNCmachinetoolistobedeveloped,processknowledgebasedmodelsareacomponentofprimaryimportancetobeintegratedunderthemachinetoolcontrolarchitecture.Inadditiontotheadaptationofcontrolparametersaccordingtoprocessconditions,controlparametershavealsotobeoptimalduringhandlingincludingchangingoperationsofworkpiecesandtoolsandpositioningoperationsastheseoperationsaccounttypicallyformorethan50oftheoveralloperatingtime.Earliermethodsforparameteroptimisationconcentratedonthereductionofpositioningandsettlingtimesofthefeedaxisbytuningonlyafewbasiccontrolparameterse.g.gainofthepositioncontrolloopandgainandresettimeofthevelocitycontrolloop.Withincreasedcomputationalpower,optimisationmethodsasdescribedin20cannowbereinvestigatedfortheusewithawiderparametersetincludingtheparametersforaccelerationandjerklimitswhicharedirectlyinfluencingthevibrationsofanaxis.Ifthecharacteristicsofacontrolledaxisareknownbymeansofthevibrationbehaviour,anadequategenerationoftheprogrammedtrajectoriescanyieldafurtheroptimisation.Methodsforinputshaping49canbeusedtodesigntrajectoriesthatdonotexciteresonantfrequenciesofagivensystem.Hence,settlingtimesandthuspositioningtimescanbefurtherreduced.Concerningparameteroptimisationthroughselflearningparticularly,theinterestofthesocalledmachinelearningapproaches21willbeintroducedasthemainresearchtrendinprocessmonitoringandcontrolstrategiestowardstheintelligentmanufacturingsystem.2.ExpectedcharacteristicsofthenextgenerationTheexpectedcharacteristicsofthenextgenerationofmachinecentresaredescribedasfollowsaIntegrationdevelopmentofanintegratedmachinetoolbeingcapableofperformingbothconventionalandnonconventionalprocessesinoneplatform.bBidirectionaldataflowdefinitionofabidirectionalprocesschainforunifieddatacommunicationexchangebetweenCAD,CAM,CNCandDrivesystems.cProcesscontrolloopdevelopmentandCNCintegrationofrobustandreliablerealtimestrategiesfortheinprocesstool,part,andprocessconditionmonitoringandcontrol.dPredictivemaintenancespecificationofaloadandsituationdependentconditionmonitoringformachinecomponentsasabasisforselfreliantmachineoperation.Thiswillbefollowedbytheformulationofaselforganisingpredictivemaintenanceschedulethatisbasedonselfandremotediagnosticsandcoversbothshortandlongtermaspects.eAutonomousoptimisationdevelopmentofaselfconfiguringselfoptimisingcontrolsystemforautonomousmanufacturing,basedontheinprocessmonitoring,characterisationandmanagementofprocessknowledge.Tofacilitatesuchcharacteristics,thefollowingtopicswillbenecessarytobeimplementedaTodevelopanintegratedintelligentmachinecentrededicatedtoemanufacturing.bToinvestigateanddevelopfast,stableandstiffreconfigurablemachineswithhybridmachiningprocessestoprepareanewplatformforfuturemachinetools.cToinvestigateimplementationoftotalerrorcompensationandinsituinspectionfacility.monitoringstrategiesforpartconditionmonitoringsurfaceroughness,surfaceintegrityanddimensionalaccuracy,toolconditionmonitoringthesocalledTCMforwearandbreakagedetection,processconditionmonitoringchatteronsetandcollisiondetectionandmachinecomponentconditionmonitoringforpredictivemaintenancepurposesrotarycomponentsandpartssubjecttofrictionsuchasguideways.Sincedirectandinprocessmeasurementisnotgenerallypossibleduetotheaggressiveenvironmentinthecuttingzonesurroundings,themainresearcheffortoverthelastdecadesforpartandtoolmonitoringhasbeenfocusedonindirectmeasurementtechniquesprocessconditionbased,inwhichcuttingprocesscharacteristicsi.e.cuttingforcesandpower,vibrations,cuttingtemperature,acousticemission,etc.aremeasuredinordertoindirectlyinferthepartandtoolcondition6,7.SensitivityofferedbyCNCinternalservosignalsfromopenarchitecturecontrollersisunderstudyaswell8,9,sincetheyenablethedevelopmentofmonitoringandcontrolstrategieswithouttheneedofinstallingadditionalsensorsinthemachine.Inthesameway,basedonthedataprovidedbyinprocessmonitoring,autonomousselfoptimisationcanbeperformedwiththeintegrationofprocesscontrolstrategiesintothemachinetoolcontrolarchitecture.Machiningprocesscontrolstrategiesareclassifiedintotwomaingroups5,namelyadaptivecontrolconstraintACCandadaptivecontroloptimisationACO.IntheformerACCcontrolstrategies,aprocessvariablei.e.cuttingforceiskeptconstantandundercontrolthroughtherealtimeinprocessregulationofacuttingprocessparameteri.e.cuttingfeed,withtheaimofincreasingprocessproductivityandrepeatability.MainresearcheffortsonACCstrategiesfocusoncuttingforcecontrol10–12andchattervibrationsuppression13,14.drawbacktodealwith.468S.Mekidetal./MechanismandMachineTheory442009466–476Indeed,flexiblemonitoringsystemsarerequiredundertheactualmarketrequirementsandthus,reliableprocessdiagnosisisnecessaryunderdifferentcuttingconditions.Nowadays,acommonproblematicsharedbyconventionalprocessmonitoringapproachesforpartandtoolconditionmonitoringisthelackofreliabilityunderchangingcuttingconditionshencelimitingtheflexibilityofsuchautomationsystems3.AsacharacteristicexampleofthisproblematicforprocessconditionbasedtoolconditionmonitoringTCM,theprocessconditionisnotonlyinfluencedbychangesintoolcondition,butitisalsodirectlyaffectedbycuttingconditions.Furthermore,underdifferentcuttingconditions,differentwearmechanismscanbeactivatedonthetool,eachonehavingitsparticularimpactonprocessandpartcondition.Therefore,whensettingupprocessmonitoringsystemsfornewcuttingconditions,previoustrialsforprocesssignaldatabaseretrievalarerequired4.Thesearecombinedtogetherwithskilledoperatorswiththenecessaryprocessknowledgeinordertointerpretchangesinprocessbehaviouri.e.forces,vibrations,etc.andsetupsuiteddetectionlimits.Additionally,flexibleprocessmonitoringequipmentsoftenrequiresadditionalsensorsthatcanfailandresultinunforeseendowntime.Asaresult,whenhighflexibilityisrequired,monitoringsystemsareusuallyswitchedoffinindustry,anddirectpostprocessmeasurementisperformed,withthecorrespondingreliabilitylackinthemachinedpartquality.Dealingwithsuchaproblematic,modelbasedprocessmonitoringandsensorfusionapproachesarepointedoutasthealternativeinordertogetreliableprocessconditiondiagnosis,withaclearresearcheffortoverlastyearsformachiningprocessessuchasturning22–24,grinding4,25,26andmilling27.Ontheotherhand,theintegrationofhumanexperienceinmanufacturingiswidelymissingconcerningmachiningprocessoptimisation.Setuptimereductioniscriticalwhenflexiblejustintimeproductionisrequired.Nowadays,setuptimemainlydependsonprocessknowledgeconcentratedinskilledoperators,andthereisalackofsystematicmanagement,retrieval,sharingandoptimisationofthatkeyknowledge.Furthermore,characterisationofprocessknowledgeanddevelopmentofmodelsforautonomousprocessoptimisationarerequiredifsetuptimesaretobedrasticallyreduced.dTodevelopandproducenewmethodologiesandconceptsofautonomousmanufacturing,selfsupervisionandselfdiagnostic/tuning/healing.eTodevelopandintegraterealtimeprocesscontrollersintoopenCNCanddrivesystemarchitecture,takingthemachinefromanaxiscontrolledsystemtoamachiningprocesscontrolledselfreliantsystem,basedontheonlineinformationprovidedbyrobustandreliablesensingtechniquesfortool,part,andmachiningprocessconditionmonitoring.fTodevelopandincorporateanextendibleandknowledgebasedCAMsystemcapableofrecognisingcomplexfeatures,performingselflearningbasedoninprocessmonitoreddataprovidedbymachinecontrolloops,andautonomouslydeterminingtheoptimumtools/setsforgivenrequirementsofpartquality,machineproductivityandprocessefficiency.Followingtheemanufacturingapproach,inasecondstep,CAMsystemscapableofsharingselfoptimisedprocessknowledgebetweennetworkedmachinesaretobedeveloped.Aninterdisciplinaryapproachofmachinetoolbuildersinordertoachievetheseobjectivesbecomesnecessaryandincludescontrolmanufacturers,researchinstitutionsandpotentialendusers.Suchadevelopmentwillrealiseanumberofbreakthroughsinthefuture,e.g.aDelayfreecumzerodowntimeproductiontheproposedemanufacturingapproachwillseetheuseofelectronicservicesbasedonavailabledatafrommachinedprocesses,sensorsignals,andhumanexperiencethatisintegratedinazerodelaytimesystemtoenablemachineswithnearzerodowntimeandproductionthatmeetsuserrequirementswithzerodelaytime.bSelfreliantproductionmachineswillbeenabledtooperatewidelyautonomously.cOptimalproductionselfconfigurationandselfoptimisationwilleliminateproductionerrorsdowntothelimitationsoftheinprocessmeasurementdevices.3.ConceptsofintelligentandflexiblemachinesInFig.2,theauthorsproposeanewintegratedconceptforthenextgenerationofmachinetoolcentres.Basedontheknowledgeacquiredandthefeaturesextracted,theperformanceofcontrolsystemswillbeextendedtowardsselfcontrolledmanufacturingwiththeobjectivesofcosteffective,highquality,faulttolerantandmoreflexiblesystemswithbetterprocesscapability.NewintelligentcontrolsystemshavetobedevelopedandintegratedwithopenarchitecturecontrollerssuchasOpenCNCC210orOSACAbasedCNCs.Inordertoallowanautomatederrorfreeproductionwithnearzerodowntime,openinterfaces,learningcapabilities,selftuningandselfadjustingmechanismsaswellassophisticatedmodelbasedpredictioninstrumentshavetobeimplementedattheselayers.Qualityinspectioncouldoperateinsituwithenvironmentalconditionstakenintoaccount.Forthefirsttime,theconceptofselfhealingwithemaintenancecouldbeoperational.3.1.IndustrialrequirementsformachiningprocessmonitoringandcontrolAmongthefuturerequirementsthathavetobefocusedon,aretheaspectsofthejustintimeproductionandzerodefectcomponents,togetherwithcontinuouslyhigherpartqualityandprocessproductivity.Automationlevelprovidedbymachiningprocessmonitoringandcontrolsystemscontributestothoserequirements.However,takingintoaccountthatthereisagrowingneedforproductionofsmalllotsizesinthemarket,flexibilitylackinsuchautomationsystemsisthemainS.Mekidetal./MechanismandMachineTheory442009466–476469Concerningthisprocessknowledgerelatedproblematic,intelligentmanufacturingsystemsIMSarethekeyongoingresearchconcepts.ThemainobjectiveoftheIMSconceptsisthedevelopmentofanautonomousmachinetoolcontrolsystemabletoperformselftuningandselflearning,providedbytheonlinemonitoringandretrievalofcuttingprocessrelatedknowledgei.e.forces,partquality,machiningtime,toollifeeconometrics,predictivemaintenance,etc.,towardsflexibleandselfoptimisingmachinetools.WiththesuccessfulincorporationofIMSsintomachinetoolcontrolintegratedCAMsystems,setuptimesfornewpartsandprocessoptimisationneedswillbeminimised,enablingjustintimeproduction,independentfrommachineoperatorskills.3.2.NewpossibilitiesinknowledgebasedsocietyThecoreconceptofdevelopingaflexiblemachineoperatedbyacontrollerthatperformsprocessadaptationonthebasisofabidirectionaldataexchangebetweenallpartsoftheprocesschainwillyieldacompletelynewwayofmanufacturing,Fig.1.Bidirectionalprocesschain.

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