【MDPI】2025工业4.0到工业5.0转型回顾探索技术与人机协同的交叉挑战与机遇研究报告

Review

AReviewoftheIndustry4.0to5.0Transition:ExploringtheIntersection,Challenges,andOpportunitiesofTechnologyandHuman–MachineCollaboration

MdTariqulIslam†,KameliaSepanloo†,SeonhoWoo†,SeungHoWoo†

c

andYoung-JunSon*

o

updates

巴checkfor

AcademicEditors:RatnaBabuChinnamandSaraMasoud

Received:3March2025

Revised:17March2025

Accepted:21March2025

Published:24March2025

Citation:Islam,M.T.;Sepanloo,K.;Woo,S.;Woo,S.H.;Son,Y.-J.AReviewoftheIndustry4.0to5.0Transition:

ExploringtheIntersection,Challenges,andOpportunitiesofTechnologyandHuman–MachineCollaboration.

Machines2025,13,267.

https://

/10.3390/machines13040267

Copyright:©2025bytheauthors.

LicenseeMDPI,Basel,Switzerland.

Thisarticleisanopenaccessarticle

distributedunderthetermsand

conditionsoftheCreativeCommonsAttribution(CCBY)license

(/

licenses/by/4.0/)

.

EdwardsonSchoolofIndustrialEngineering,PurdueUniversity,WestLafayette,IN47904,USA;

islam70@(M.T.I.);ksepanlo@(K.S.);woo75@(S.W.);

woo44@(S.H.W.)

*Correspondence:yjson@

†Theseauthorscontributedequallytothiswork.

Abstract:TheIndustrialRevolution(IR)involvesacenturies-longprocessofeconomicandsocietaltransformationdrivenbyindustrialandtechnologicalinnovation.Fromagrarian,craft-basedsocietiestomodernsystemspoweredbyArtificialIntelligence(AI),eachIRhasbroughtsignificantsocietaladvancementsyetraisedconcernsaboutfutureimplications.AswetransitionfromtheFourthIndustrialRevolution(IR4.0)totheemergentFifthIndustrialRevolution(IR5.0),similarquestionsariseregardinghumanemployment,technologicalcontrol,andadaptation.Duringalltheseshifts,arecurringthemeemergesaswefeartheunknownandbringaconcernthatmachinesmayreplacehumans’hardandsoftskills.Therefore,comprehensivepreparation,criticaldiscussion,andfuture-thinkingpoliciesarenecessarytosuccessfullynavigateanyindustrialrevolution.WhileIR4.0emphasizedcyber-physicalsystems,IoT(InternetofThings),andAI-drivenautomation,IR5.0aimstointegratethesetechnologies,keepinghuman,emotion,intelligence,andethicsatthecenter.Thispapercriticallyexaminesthistransitionbyhighlightingthetechnologicalfoundations,socioeconomicimplications,challenges,andopportunitiesinvolved.WeexploretheroleofAI,blockchain,edgecomputing,andimmersivetechnologiesinshapingIR5.0,alongwithworkforcereskillingstrategiestobridgethepotentialskillsgap.Learningfromhistoricpatternswillenableustonavigatethiseraofchangeandmitigateanyuncertaintiesinthefuture.

Keywords:artificialintelligence(AI);human–machinecollaboration;socioeconomicimplications;workforcereskilling;Industry4.0;Industry5.0

1.Introduction

TheIRisbetterunderstoodasaprocessofeconomictransformationratherthanafixedperiodinaparticularsetting[

1]

.ThisperspectiveacknowledgesthespatialandtemporalheterogeneityinadoptingIRacrossglobalcontexts.Forinstance,whileregionssuchastheUnitedStatesandWesternEuropebeganundergoingtheirSecondIndustrialRevolution(IR2.0)bythelate19thcentury,otherareas,particularlyinAsia,includingChina,India,andKorea,didnotcommencetheirFirstIndustrialRevolution(IR1.0)untilthe20thcentury.However,Japan,despitebeingalatecomertotheIR1.0,accelerateditsindustrialgrowthduringtheMeijiperiod,becomingasignificantplayerintheIR2.0bytheearly20thcenturyandlayingthefoundationforitslaterstatusasanAsianeconomicmiracle[

2]

.

SuchvariationsinthepaceandtimingofindustrializationprovetheimportanceofviewingIRasaspectrumofchangesratherthandistinctevents.Multipleindustrialand

Machines2025,13,267

/10.3390/machines13040267

Machines2025,13,2672of34

technologicalbreakthroughswithinthisspectrumcanoverlapwithinspecificgeographicregions.DespitethedisparatetechnologicalleapsacrossvariousIRs,severalcommonfactorsserveaslitmustestsforidentifyinganewIR.Thesefactorsincludeelevatedlevelsofproductivity,bettertransportation,demandfornewsoftandhardskills,resourceaugmenta-tion,politicalstability,andtheavailabilityoffinancialcapitalforinvestment.Furthermore,theinterplayamongthesefactorscriticallydeterminesthepaceandsuccessofindustrialtransformationsindifferentregions.Forexample,thesynergybetweentechnologicalinnovationandthedevelopmentofhumancapitalcansignificantlyaccelerateeconomicgrowth,whileinadequateinfrastructureorpoliticalinstabilitycanhinderprogress,leadingtounevendevelopment.

TheprecisestartandenddatesofIRsremainsubjectsofdebateamonghistoriansasthesocialandeconomicchangesunfoldatvaryingpacesacrossdifferentregions.However,historicalanalysisrevealsfourmajorshiftsthathaveshapedourknowncivilization.IR1.0,orIndustry1.0,beganinthelate18thcenturywiththeintroductionofwaterandsteam-poweredmechanicalmanufacturingfacilities.Thiserasawthetransitionfrommanualproductionmethodstomachines,whichmarkedthebeginningofindustrialization.TheinventionofthesteamenginebyJamesWattin1769wasapivotalmoment,enablingthemechanizationofproductionprocessesandaneweraoftransportation[

3]

.Atfirst,thistransformationwasseenasacauseofpovertyandhardshipbecausemachinesreplacedhumanworkerswithoutproperprotectionsorregulations.Companiesandprofit-drivenorganizationsrespondedbyreducingworkinghoursandwages.However,thisshiftalsoledtomajorsocietalprogressbyimprovingworkplacecommunicationandincreasingproductionrates,pavingthewayforfutureindustrialadvancements.

TheIR2.0,orIndustry2.0,emergedinthelate19thtoearly20thcentury.Thisperiodwascharacterizedbythewidespreadadoptionofelectricityandthedevelopmentofassemblylinesinproduction[

4]

.Duringthistime,industriesbegantocapitalizeonnaturalandsyntheticresources(e.g.,rareearthelements,plastics,alloys,andchemicals),whichplayedapivotalroleinproducingmachineryandtools,pavingthewayfortheautomationoffactoryenvironments.Majoradvancesduringthisperiodincluded(1)theintroductionofsignalprocessinganditsapplicationintelephonecommunicationinthe1870s,(2)structuralimprovementsutilizingsteelforbuildingsthatresultedintheconstructionofthefirstskyscrapers,aswellas(3)innovationssuchasphonographsandmotionpicturesinthe1890s.Additionally,theintroductionofgeneratorsandrefrigeratorsgraduallyreplacedthewaterandsteam-poweredenginesoftheIR1.0,whichmarksasignificanttransitioninenergyutilizationandproductioncapabilities.

TheThirdIndustrialRevolution(IR3.0),orIndustry3.0,beganinthe1970sandisoftenreferredtoastheDigitalRevolution.Thiserawitnessedtheriseofelectronics,in-formationtechnology,andautomatedproduction.Thedevelopmentofprogrammablelogiccontrollers(PLCs)androboticssignificantlyenhancedautomationwithinmanufac-turingprocesses[

4,

5]

.Moreover,theintroductionofcomputersandtheinternetlaidthefoundationforthedigitaltransformationofindustriesandsetthestageforthesubsequentphaseofindustrialevolution.OnenotableconsequenceofthisIR3.0wasthecontractionoftheblue-collarjobmarket,drivenbywidespreadautomationandincreasedproductivity.However,thisreductionwasnotuniformandwasgeographicallylocalized.TheprimaryreasonwasthatWesternnationsbegantooutsourceproductiontorelativelylow-wagecountries,whichledtotheproliferationoflabor-intensivemanufacturingjobswithintheAsianeconomy.

TheIR4.0,orIndustry4.0,startedintheearly2000sandrepresentsaleapinman-ufacturingandindustrialpracticescharacterizedbytheintegrationofadvanceddigitaltechnologiesintoproductionprocesses.Industry4.0markedtheintegrationofcyber-

Machines2025,13,2673of34

physicalsystems,IoT,bigdataanalytics,cloudcomputing,andAI,leadingtotheemer-genceofsmartfactoriesthatoptimizeefficiency,automation,anddata-drivendecision-making[

6

–

8]

.IR4.0technologiesofferedsignificantopportunitieswhilesimultaneouslyposingconsiderablechallenges.Ontheonehand,organizationscouldleveragethesetechnologiestoimprovedecision-makingprocesses,enhanceproductivity,andreduceop-erationalcosts[

9,

10]

.Forinstance,theintegrationofsensortechnologiesenabledreal-timemonitoringandcontrolofmanufacturingprocesses,whichimprovedproductqualityandminimizedwaste[

9]

.DespitetheadvantagesofIndustry4.0,smallandmediumenterprises(SMEs)encounteredmajorchallenges,includinglimitedfinancialresources,workforceskillgaps,andresistancetotechnologicaladoption.Thehighcostsofimplementation,coupledwithalackofexpertise,createdbarrierstointegratingadvancedautomationandAI-drivendecision-making[

11

–

13]

.Nevertheless,theimpactofIndustry4.0extendedbeyondjustoperationalimprovements;italsohadbroaderimplicationsforsustainabilityandenvironmentalresponsibility.TheadoptionofIndustry4.0practicescontributedtosustainablemanufacturingbyoptimizingresourceuseandminimizingwaste[

14,

15]

.

BuildingonthefoundationsofIndustry4.0,Industry5.0isemergingasanewparadigmratherthanamereextension.Unlikepastindustrialrevolutionsthatunfoldedovercenturies,therapidpaceoftechnologicalbreakthroughstodayjustifiesrecognizingIR5.0asadistinctera.Fromthatpointofview,IR5.0buildsupontheIR4.0paradigmbyemphasizinghuman–machinecooperationasacentraltenet.Industry5.0buildsontheautomationanddigitizationofIndustry4.0byprioritizinghuman–machinecollaboration.Ratherthansolelyfocusingonefficiency,IR5.0emphasizestheintegrationofhumancogni-tiveabilities,adaptability,andethicalconsiderationsintoindustrialsystems,fosteringamorebalancedsynergybetweenhumansandtechnology[

16,

17]

.

SomekeycomponentsofIR5.0arethehuman-centricapproach,circulareconomy,andenhancedresilience.Thisparadigmfocusesonthewelfareofhumansandaugmentingusthroughtechnology[

18]

.Forexample,collaborativerobots(co-bots)aredesignedtoundertakerepetitiveandhazardoustasks,enablinghumanworkerstofocusonmoreinno-vativeandvalue-addedresponsibilities[

19]

.Thistechnologicalsupportincreasesworkers’occupationalsatisfactionandmotivatesthemtoenhancetheircreativeproblem-solvingabilities[

20]

.AnotherdefiningcharacteristicofIndustry5.0isitscommitmenttosustain-abilityandthecirculareconomy.Recognizingtheplanet’sfiniteresources,IR5.0prioritizesenergy-efficientproduction,wastereduction,andethicalindustrialpractices.EmergingtechnologiessuchasAI,IoT,andblockchainareincreasinglyadoptedtoenhanceresourceoptimization,cybersecurity,andenvironmentalresponsibilityinmanufacturing[

21,

22]

.Similarly,resilience,whichisthecapacityofsystemstomaintainconstantoperationsinthefaceofuncertaintyorcrisisevents,playsapivotalroleinIR5.0.Inthiscontext,resilienceisnotjustaboutrecoverybutalsoinvolvestheproactiveadaptationandevolutionofsystemstowithstanddisruptionsacrosstheindustry.Forexample,thewidespreaduseofAIindataacquisition,interpretation,andevaluationinIR5.0strengthenssupplychainnetworksbyimplementingadvancedtechnologiessuchaspredictivedisruptions,maintenance,an-ticipatingpotentialfailures,andminimizingdowntime,thusmakingthewholesupplychainmoreresilient.

ResearchersandindustrypractitionersarediligentlyworkingtoensurethesuccessfulintegrationofthesekeycomponentsinthisneweraofIR5.0.Continuouseffortstopushtheboundariesofourcapabilitiesandknowledgeareessentialtoachievethis.Therefore,thispaperseekstoestablishacriticalassessmentforunderstandingthenaturalprogressionfromthemachine-driven,automatedenvironmentscharacteristicofIR4.0tothemorehuman-centricvisionofIR5.0,wherecollaborationbetweenhumansandmachinesbecomesparamount.Inthisreviewpaper,wediscussthebreakthroughsthatarevisiblyleading

Machines2025,13,2674of34

ustowardthisgoalaswellasthosethatremainrelativelyunknown.Thisdiscussionincludesinsightsfrommultidisciplinaryapplications(i.e.,science,engineering,ergonomics,psychology,andethics)andaddressesthetechnologiesthataregoingtoshapetheworldwewanttoinhabitoverthenextfewdecades.Inparticular,weaddresstheapplicationofIoT,bigdata,physics-informedmachinelearning,additivemanufacturing,robotics,andhuman–machineinteraction.Furthermore,wediscussadvancementsinAI,explainableAI,andcyber-physicalsystems,especiallyintermsofvulnerabilitiesandinformeddecision-making.ThroughouteachmajorIR,concernsregardingjobsecurityandthenecessityforupskillinghavebeenprominentissues,whichthisreviewpaperalsoaddresses.Wewilldiscussthetoolslikelytoemergeattheforefrontofthisrevolutionandexaminehowupskillingtheworkforceinutilizingthesetools(e.g.,extendedreality(XR),brain–computerinterfaces,generativeAI,human–computerinteraction,andblockchain)willbenefitfuturegrowthandadaptation.Byanalyzingpasttrendsandemergingtechnologicalshifts,thisstudyprovidescriticalinsightsintothechallengesandopportunitiesdefiningthetransitiontoIndustry5.0.

Theremainderofthispaperisstructuredasfollows.Section

2

discussesthemethodsusedtodeterminethescopeofthisresearch.Section

3

exploresthetechnologicalfounda-tionofIndustry4.0,detailingkeyadvancementssuchasIoT,bigdata,andcyber-physicalsystems.Section

4

discussestheemergenceofIndustry5.0,highlightingtheshifttowardhuman–machinecollaboration,sustainability,andresilience.Section

5

examinestheso-cioeconomicimplicationsofthistransition,includingworkforceupskillingandethicalconsiderations.Section

6

presentskeytoolsandtechniquesthatfacilitatethisshift,whileSection

7

outlinesreal-worldapplicationsandopportunitiesacrossvariousindustries.Finally,Section

8

addressesthechallengesandfuturedirectionsofIndustry5.0,concludingwithinsightsontheevolvingindustriallandscape.

2.Methods

Toidentifythescopeofthisreviewpaper,weconductedanextensivebibliometricnetworkanalysis.Initially,weretrievedover30,000documentsfromtheScopusdatabasewiththekeyword“IndustrialRevolution”,thenfilteredthemdowntoapproximately19,000documents,toincludeonlyarticles,conferencepapers,andbookchapters.Thetitle,abstract,keywords,andauthorinformationoftheseselecteddocumentswereexportedinRefWorks(RIS)format.Thecollectedbibliometricdatawerethensorted,analyzed,andvisualizedusingVOSviewersoftware1.6.20asshowninFigure

1

,whichisawidelyusedtoolforconstructingandvisualizingbibliometricnetworksforjournals,authors,andkeywords.Thebibliometricnetworkscanillustratedifferenttypesofrelationships,includingcitations,keywordsco-occurrence,co-citations,andco-authorships.Inthesenetworkvisualizations,eachitemisrepresentedbyitslabel,andthesizeofeachcirclereflectsthesignificanceorfrequencyofthekeywordorauthor.Thelargerthecircle,thegreatertheweightorfrequencyoftheitem.Eachcolorrepresentsaclusterofcloselyrelateditems,andthedistancebetweentwokeywordsapproximatelyindicatestheirrelatednessbasedonco-occurrence;thecloserthekeywordsaretoeachother,thestrongertheirconnection.Thekeywordco-occurrencevisualizationshownherefromtheselected19,000Scopus-indexeddocumentson“IndustrialRevolution”servedasaguidelinetooutlinethescopeofthispaper.Fromouranalysis,weidentifiedthreeprimaryclusterswithinthekeywordmap:onecenteredaroundIndustry4.0,anotherfocusedonAIandtheIoT,andthethirdemphasizingsustainabilityandhuman-centeredapproaches.

Machines2025,13,2675of34

Figure1.Bibliometrickeywordco-occurrencenetworkof“industrialrevolution”research.

ThemostdominantresearchclusterweobservedisIndustry4.0,acentralthemeconnectingmultipledomainssuchassmartmanufacturing,supplychains,digitalization,educationandtraining,andaugmentedreality.CloselylinkedtothisistheclusterfocusingonAIandIoT,whichincludesmachinelearning,deeplearning,blockchain,cybersecu-rity,andcyber-physicalsystems,whichhighlightstheroleofAI-drivenautomationinindustrialtransformations.AnemergingpresenceofIndustry5.0,positionedbetweenthesetwomajorclusters,suggestsagradualshiftfrompureautomationtowardsmorecollaborativeinteractionsbetweenhumansandAIsystems.Thethirdmajorclusterem-phasizessustainabilityandsocietalimpacts,placinghumansatthecore.Thisclusterincludescriticaltopicssuchassustainabledevelopment,climatechange,circulareconomy,andeconomicgrowth.Thisreflectstheincreasingemphasisonbalancingtechnologicalprogresswithenvironmentalandsocialresponsibility.Thevisualizationalsohighlightshistoricalandeconomicdimensionsofindustrialrevolutionsthroughkeywordshistory,economics,energy,agriculture,andthatindicatesthecurrentresearchextendsbeyondpurelytechnologicalaspects.

Similarly,wegeneratedabibliometricauthornetwork(Figure

2

)whichhighlightstheprominentresearchercollaborationsandthematicgroupingsintheindustrialrevolutionliterature.Here,severaldistinct,interconnectedclusterswereidentifiedandrepresentedbyaspecificcolor.Asshowninthelarge,denselyconnectedredcluster,whichidentifiesacoregroupofhighlyinfluentialauthorswhofrequentlycollaboratewithintheirrobustcollaborativenetwork.Smallerclustersofvariouscolors(suchasblue,green,andpurple)reflectadditionalresearchergroups,likelyindicatingregionalorthematicspecializations(e.g.,agriculture,energy,history,biasness,economics).Additionally,thepresenceofsmallerorisolatedclusterssuggestsemergingresearchtopicsorspecializedareasthatarecurrentlyperipheralbutmayrepresentpromisingdirectionsforfutureresearch.

Machines2025,13,2676of34

Figure2.Bibliometricauthorcollaborationnetworkin“industrialrevolution”research.

3.TechnologicalFoundationofIR4.0

ThetechnologicalfoundationofIR4.0isprimarilybasedontheconvergenceofIoT,digitaltwinofindustrialprocesses,cloudcomputing,roboticsystems,andadvancedana-lytics.However,allthesetechnologiesdidnotappearovernight.Rather,theygraduallymaturedfordecadesandreachedapointwhereseamlessintegrationbecamefeasibleatscale.Forinstance,sensortechnologieshaveexistedforyears,buttheirminiaturizationandplummetingcostsnowenablereal-time,accuratedatacollectionacrossindustries.Similarly,theonce-theoreticalconceptsofdigitaltwinsandXR(ExtendedReality)havebecomeincreasinglyappliedandfundamentallyalteredhowproductsaredesigned,tested,produced,andconsumed.Thisshiftfromisolatedtechnologicalbreakthroughstointer-connected,data-richecosystemslaidthefoundationforthecurrenttimeinwhicheverymachine,process,andworkerisdigitallyawareofandcapableoftheirimprovement.

3.1.IoT

IoTisoneofthekeycomponentsofIR4.0,whichrepresentstheinterconnectednessofthedevicenetworktoexchangeandtransmitdata[

23]

.Inanindustrialenvironment,IoTallowsinteractionbetweendevices,sensors,equipment,andsystems,alsocalledtheIndustrialInternetofThings(IIoT).IoTprovidesreal-timeinsights,stimulatesautomationofdecision-making,andhelpstoinnovatemanufacturingorsupplychainprocesses[

24]

.OneofthemostpopularIoTcontributionstoIR4.0isreal-timemonitoringoftheprocess.Sensorsequippedinmachinescollectmultiplestreamsofdata,suchastemperature,vibra-tion,pressure,andhumidity,toensurethesystemoperateswithindesignatedthresholds.Nowadays,companiesworldwideutilizeIoTsmartdevicestomonitorequipmentperfor-mance,predictthenecessityofmaintenance,andperformdiversefunctionalitiestoreduceoperationidletimeandincreaseproductivity[

23]

.

Inaddition,IoTcontributestoprocessoptimizationbysupportingremoteaccessanddistinguishingprocessbottlenecks,rootcauses,andpotentialimprovementareas.Withinsupplychainmanagementframework,IoTprovidesvisibilityamongsupplychainentities

Machines2025,13,2677of34

bygeneratingsmartlogisticsolutionsfrommaterialtoproductdelivery.ProductionfloorIoTdevicessuchasRadioFrequencyIdentification(RFID)[

25

],UltrawideBand(UWB)[

26

],GlobalPositioningSystem(GPS),visionsystems,conditionmonitoringsensors,proximitysensors,pressuresensors,temperaturesensors,actuatorshelptotracktheworkinprogressstatus,locateobjects,identifybottlenecks,manageinventoryandmaintainsafetyandsecurity.However,despitehavingadvancementsandwidespreadusecasesinIoT,therearemajorchallengessuchasdatasecurity,interoperability,andexpansion[

27]

.Researchiscurrentlybeingconductedtoensurebetterencryption,standardizedprotocols,andedgecomputingtoovercomethosechallenges.

InadditiontoIoTtechnologiesthatenabledeviceinterconnectivityandreal-timeman-agementofindustrialsystems,human–machineinteraction(HMI)isincreasinglyessentialinindustrialenvironments.HMIactsasacriticalcomponentwithintheIIoTframework,particularlyenhancingreal-timeprocessmonitoringandbridgingthegapbetweenhumanoperatorsandautomatedsystems.IndustrialenvironmentsfrequentlyutilizeHMIsforintuitiveandefficientoperatorcontrol,oftenintegratingthemseamlesslywithSupervisoryControlandDataAcquisition(SCADA)systems.SCADAsystemsfacilitatecentralizeddatacollection,processvisualization,andremotecontrolovermultipleoperations.Additionally,GraphicalUserInterfaces(GUIs)improveusabilitybyprovidinginteractivedashboardsthatdisplayreal-timedata,alerts,andprocessinginsightswhichenablesquickerandbetter-informeddecision-makingbyusers.

3.2.BigData

Nowadays,itisquitecommonthatthousandsoftinysensorsonaproductionfloorgeneratesuchvastamountsofdatathattraditionalstorageandanalysismethodscannotcope.Modernmanufacturingencountersbothitschallengesandgreatestopportunitiesinthisdomain.CliveHumbystated,“Dataisthenewoil”,althoughsomearguedataareevenmorevaluable[

28]

.Bytransformingrawstreamsoflogs,readings,andperformancemetricsintoactionableinsights,theutilizationofbigdatahasbecomeatruegamechangerforIR4.0.Theamountofdatageneratedworldwidehasexploded,anditspromisetodriveproductivitygrowthisvisibleineverysector[

29]

.

Theintegrationofbigdataanalyticsapproachesandframeworksallowspredictiveanalysis,throughwhichorganizationscanpredictanomaliesproactively.SomepopulartoolsatpresentareApacheHadoopecosystem,ApacheSpark,Timeseriesdatabases,AzureIoTanalytics,NoSQLdatabases,andcommunicationprotocolslikeMessageQueu-ingTelemetryTransport(MQTT),whichfacilitateslightweightmessagingandstreaming.Smartmachineslinkedtocentralizedsystemscandynamicallytransmitdatathatcanbeanalyzedandintegratedtoforecastpotentialfailures[

30]

.Thedeployedalgorithmsanalyzebothhistoricalandcurrentdatastreamstoidentifypotentialpatternsofanomalies.Thisapproachisextensivelyusedincreditcardfrauddetection,demandforecasting,inventorymanagement,intrusiondetection,cybersecurity,andmanufacturing.Consequently,theseinterconnectedIoTdevicesconsistentlygeneratediversedataandsupportqualityman-agementprocessesthroughreal-timeonlineanomalydetection,thusensuringseamlessproductionwithenhancedqualityproducts[

31]

.

3.3.DigitalTwinofIndustrialProcesses

Theconceptofdigitaltwinswasonceconsideredsciencefiction,butitisnowareal-itywithmanyreal-worldapplications.Digitaltwinsessentiallygeneratevirtualreplicasreflectingphysicalentities,processes,andsystems.Thisdigitalreplicaisinterconnectedwithphysicalsystemsinreal-timethroughsensorsanddatasetstoperformsimulation,analysis,andoptimizationtasksoftheprocessbyutilizingCyber-PhysicalSystems(CPS)

Machines2025,13,267