IIC：工业物联网人工智能框架白皮书（EN）

IndustrialIoTArtificialIntelligenceFramework

2022-02-22

Authors

WaelWilliamDiab,AlexFerraro,BradKlenz,Shi-WanLin,EdyLiongosari,WadihElieTannous,BassamZarkout.

IndustrialIoTArtificialIntelligenceFramework

IIC:PUB:IIAIF:V0.10:ID:2022ii

CONTENTS

1IndustrialArtificialIntelligence 6

1.1IndustrialInternetofThings 6

1.2IndustrialArtificialIntelligence 6

1.3ArchitectureViewpoints 7

2BusinessViewpoint 8

2.1UncoverValuableInsightsFromDataIntensiveEnvironments 9

2.2EnableDigitalTransformation 9

2.3AgentforFuture-ProofingtheOrganization 11

2.4AIAdoptionReadiness 11

3UsageViewpoint 12

3.1IndustrialAIMarket 12

3.2UsageConsiderations 13

3.3Trustworthiness 15

3.3.1Security 16

3.3.2Privacy 19

3.3.3Confidentiality 20

3.3.4Explainability 21

3.3.5Controllability 21

3.4EthicalandSocietalConcerns 22

3.4.1Ethics 22

3.4.2Bias 23

3.4.3Safety 24

3.5ImpactonLaborForce 25

3.6RegionalandIndustry-SpecificConsiderations 27

3.7AIasaForceforGood 27

4FunctionalViewpoint 28

4.1ArchitectureObjectivesandConstraints 28

4.2DataConcerns 29

4.3LearningTechniques 30

4.4GeneralIndustrialAIFunctionalArchitecture 32

4.5SystemofSystemsIssues 34

4.6ApplicationHorizonofIndustrialAI 35

5ImplementationViewpoint 36

5.1ImplementationGuidance 36

5.2ImplementationConsiderations 37

5.2.1Scope 37

5.2.2ResponseTime 37

5.2.3Reliability 38

5.2.4BandwidthandLatency 38

5.2.5Capacity 39

5.2.6Security 39

5.2.7DataProperties 39

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5.2.8TemporalDataCorrelation 40

5.2.9Interoperability 40

5.2.10RunningSystemsInParallel 40

5.2.11DealingWithTechnicalDebt 41

5.2.12PortabilityandReusabilityofAISystems 41

6TheFutureoftheIndustrialAI 42

6.1Far-ReachingBenefitsofAIDespitetheRisks 42

6.2ConvergencewithOtherTransformativeTechnologies 42

6.3StandardsEcosystem 44

6.3.1Enablingintelligentinsights 45

6.3.2Ecosystemapproach 46

6.3.3ProgramofworkandroleinenablingDXacrossindustries 46

6.3.4Summary 48

6.4FinalThoughtsandTakeaways 48

AnnexAArtificialIntelligenceBackground 50

A.1BriefHistoryofAI 50

A.2WhyNow? 51

A.2.1CheapandPowerfulComputeInfrastructure 51

A.2.2AvailabilityofLargeAmountsofData 52

A.2.3ImprovementsinAlgorithms 52

AnnexBExemplaryUseCasesofAIinIndustry 52

B.1Manufacturing 53

B.2Healthcare 55

B.3Buildings 56

B.4TransportationandLogistics 57

B.5DetectingIIoTSystemThreatsUsingAI 57

AnnexCIICReferences 58

AnnexDAuthors&LegalNotice 59

FIGURES

Figure1-1.IndustrialInternetViewpoints.Source:IICIIRA 7

Figure2-1.IndustrialAIFrameworkBusinessViewpoint.Source:IIC 8

Figure2-2.DigitalTransformationJourney.Source:IIC 10

Figure3-1.IndustrialAIFrameworkUsageViewpointandItsStakeholders.Source:IIC 12

Figure3-2.TrustworthinessofIIoTSystems.Source:IIC 15

Figure3-3.SecurityFrameworkFunctionalBuildingBlocks.Source:IICIISF 17

Figure3-4.Skillshift:AutomationandtheFutureoftheWorkforce.Source:McKinsey 26

Figure4-1.IndustrialAIFrameworkFunctionalViewpointandItsStakeholders.Source:IIC 28

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Figure4-2.AI/MachineLearningModelProcess 29

Figure4-3.DataProcessingforAIModeling 30

Figure4-4.IndustrialAISystem 31

Figure4-5.IndustrialAIinIndustrialOperationEnvironment 32

Figure4-6.IndustrialAIHigh-LevelFunctionalComponents 33

Figure4-7.ExampleofaSystemofSystemsintheEVChargingSpace.Source:Artemis 34

Figure5-1.IndustrialAIFrameworkFunctionalViewpointandItsStakeholders.Source:IIC 36

Figure6-1.TrustworthinessofIIoTSystems.Source:ISO/IECJTC1/SC42 46

TABLES

Table3-1.KeyRolesofAIinIndustrialApplications 14

Table3-2.SecuringIndustrialAIAcrosstheIIoTSecurityFunctionBuildingBlocks 18

Table3-3.CorePrinciplesoftheAIEthicsFramework.Source:DepartmentofIndustry,Australia 23

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IndustrialArtificialIntelligence(AI)istheuseofAIinapplicationsinindustry

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andamajorcontributortovaluecreationinthefourthindustrialrevolution.AIisbeingembeddedinawiderangeofapplications,helpingorganizationsachievesignificantbenefitsandempoweringthemtotransformhowtheydelivervaluetothemarket.

Thisdocumentprovidesguidanceandassistanceinthedevelopment,training,documentation,communication,integration,deploymentandoperationofAI-enabledindustrialIoTsystems.ItisaimedatdecisionmakersfromITandoperationaltechnology(OT),businessandtechnicalfrommultipledisciplines,includingbusinessdecision-makers,productmanagers,systemengineers,usecasedesigners,systemarchitects,componentarchitects,developers,integratorsandsystemoperators.

ThedocumentisstructuredaroundthearchitectureviewpointsasframedinIIC’s

Industrial

InternetReferenceArchitecture,

namelybusiness,usage,functionalandimplementationviewpoints.Thedocumentdiscussesthebusiness,commercialandvaluecreationconsiderationsthatdrivetheadoptionofAI.ItalsoelaboratesontheconcernsthatarisefromtheusageofAI,theusecasesinindustry,andtheethical,privacy,bias,safety,laborimpactandsocietalconcernsrelatedtothem.Onthetechnicalside,thedocumentdescribesthearchitectural,functionalanddataconsiderationsrelatedtoAI,anddiscussesvariousimplementationconsiderations,suchasperformance,reliability,datapropertiesandsecurity.

TheadoptionofAIisexpectedtoaccelerateintheindustry.AItechnologywillcontinuetoevolve,giventhefast-increasingcomputepower,wideravailabilityofdatathatcanbeusedfortrainingandtheever-growingsophisticationofalgorithms.CurrentITstandardsandbestpracticesmustevolvetoaddresstheuniquecharacteristicsofAIitselfandspecificconsiderationsrelatedtosafety,reliabilityandresilienceofIIoTsystems.Inaddition,thegrowingmaturityoforganizationsaboutAIwillhelpthemappreciatethatitsbenefitsfaroutweighitsrisks.TheAIstandardsecosystemwillalsocontinuetoevolve,forexampletheongoingstandardsworkbyISO/IECJTC1/SC42thatprovidesguidancetoJTC1,IECandISOcommitteesdevelopingAIstandards.

Basedonthesetrends,thereshouldbelittledoubtthatAIwillcontinuetopushthestate-of-the-artofwhatistechnologicallyandfunctionallypossible,andthuswhatisexpectedtobethereasonablethingtodowillequallyevolve.Attitudestowardsthetechnologyandbusinessexpectationsaboutitsusewillalsocontinuetoevolve.

Inthefuture,wecanexpecttheuseofAItechnologiestobecomethenormratherthantheexception,andgiventhesocietalbenefitsofthistechnology,“notusingAI”mayeventuallybecometheirresponsiblethingtodo.

1Smartmanufacturing,robotics,predictivemaintenance,healthdiagnostics,andautonomousvehicles.

IndustrialIoTArtificialIntelligenceFramework

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1INDUSTRIALARTIFICIALINTELLIGENCE

ThissectionintroducestheIndustrialInternetofThings(IIoT)andtheapplicationofArtificialIntelligence(AI)inIIoTecosystems(IndustrialAI).ItfocusesontheconsiderationsthatmustbeaddressedduringtheAI’sfulllifecyclewithinanIIoTsystem,fromdesigntoimplementationandoperation.

1.1INDUSTRIALINTERNETOFTHINGS

TheIndustrialInternetofThingsintegratestheindustrialassetsandmachines—thethings—withenterpriseinformationsystems,businessprocessesandpeoplewhooperateorusethem.

Withtheseconnectionstotheindustrialassetsandmachines,moderntechnologiesenabletheapplicationofAItomachineandoperationalprocessdatatogaininsightsintotheoperations,optimizethemintelligentlytoboostproductivity,increasequality,reduceenergyandmaterialconsumption,increaseflexibilityandultimatelycreatenewbusinessvalue.Allthismustbedonewhilemaintainingcommitmentstosafety,reliability,resilience,securityanddataprivacyasthetrustworthinessofthesystemsandconservationoftheenvironmentassocialvalues.

IIoTisanaturalextensionoftheindustrialandinternetrevolutions.IIoTisamajorforcedrivingeconomicgrowth,nowandforthecomingdecades,atagreaterpacethanpriorrevolutions.AsoutlinedbytheWorldEconomicForum,

2

“Thefirstindustrialrevolutionusedwaterandsteampowertomechanizeproduction.Thesecondusedelectricpowertocreatemassproduction.Thethirdusedelectronicsandinformationtechnologytoautomateproduction.Now,afourthindustrialrevolutionisbuildingonwhathasprecededit,blurringthelinesbetweenthephysical,digitalandbiologicalspheres.”

ToacceleratethisdigitalrevolutiontheIndustryIoTConsortium(IIC)isadvancingthetechnologyofIIoTacrossadiversesetofapplicationdomains.

1.2INDUSTRIALARTIFICIALINTELLIGENCE

IndustrialartificialintelligenceistheapplicationofAItoIoTapplicationsinindustry,inareaslikesmartmanufacturing,robotics,predictivemaintenance,diagnosisofinfectiousdiseasewithmachinelearningandautonomousvehicles.

TheuseofAIispervasiveintheenterprise,helpingorganizationsachievesignificantbenefitsintermsofbetterinsight,fasterdecisionsandmoreeffectiveoperations.Inparticular,AIplaysakeyroleindrivingtheIT/OTconvergencewithagrowingrangeofpracticalapplicationsinindustry,forexampleautomatingroutinelabortasks,drivingautonomousvehicles,

2WorldEconomicForum(2016):

TheFourthIndustrialRevolution:WhatitMeans,HowtoRespond.

https://bit.ly/3CRmjzz.

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understandingspeechandperformingmedicaldiagnostics.IndustrialAIisamajorcontributortovaluecreationinthefourthindustrialrevolution.

1.3ARCHITECTUREVIEWPOINTS

ThisIndustrialAIFrameworkusesthearchitectureviewpointsoftheIIoT,viewpointsforshort,asdefinedintheIICIndustrialInternetReferenceArchitecture

3

(IIRA):

•BusinessViewpoint,

•UsageViewpoint,

•FunctionalViewpointand

•ImplementationViewpoint.

ThisreferencearchitecturedocumentleveragestheISO/IEC/IEEE42010:2011

4

methodologytoidentifytheseviewpoints.Wehighlightfourimportanttermsfromthisstandardastheyareusedthroughoutthisdocument.

Stakeholdersareindividuals,teams,ororganizationsthathaveaninterestinasystem.Systemconcernsareinterestsinasystemrelevanttooneormoreofitsstakeholders.Architectureviewsareworkproductsexpressingthearchitectureofasystemfromtheperspectiveofspecificsystemconcerns.Architectureviewpointsareworkproductsthatestablishtheconventionsfortheconstruction,interpretationanduseofarchitectureviewstoframespecificconcerns

Thearchitectureviewpointsidentifyrelevantstakeholdersandtheirconcernsandarticulateshowtheseconcernsareaddressed.Astakeholdermayhavemorethanonetypeofconcern,forexampleanexecutivemayhavebusinessconcernsaswellasconcernsaboutimplementation;asystemarchitectmayhaveusageconcernsaswellasfunctionalandimplementationconcerns.

Figure1-1.IndustrialInternetViewpoints.Source:IICIIRA.

TheviewpointsprovidedifferentperspectivesofthecomplexIIoTsystemandtakentogether(seeFigure1-1)expressthesystem’sarchitecture.

3IIC:

IndustrialInternetReferenceArchitecture.

RefertoAnnexCfordetails.

4

/standard/50508.html

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Thebusinessviewpointattendstotheconcernsoftheidentificationofstakeholdersandtheirbusinessvision,valuesandobjectivesinestablishinganIIoTsysteminitsbusinessandregulatorycontext.ItfurtheridentifieshowtheIIoTsystemachievesthestatedobjectivesthroughitsmappingtofundamentalsystemcapabilities.

Theusageviewpointaddressestheconcernsofexpectedsystemusage,typicallyrepresentedassequencesofactivitiesinvolvinghumanorlogical(e.g.systemorsystemcomponents)usersthatdeliveritsintendedfunctionality,ultimatelyachievingitsfundamentalsystemcapabilities.

ThefunctionalviewpointfocusesonthefunctionalcomponentsinanIIoTsystem,theirstructureandinterrelation,theinterfacesandinteractionsbetweenthem,andtherelationandinteractionsofthesystemwithexternalelementsintheenvironment,tosupporttheusagesandactivitiesoftheoverallsystem.

Theimplementationviewpointdealswiththetechnologiesneededtoimplementfunctionalcomponents(functionalviewpoint),theircommunicationschemesandtheirlifecycleprocedures.Theseelementsarecoordinatedbyactivities(usageviewpoint)andsupportiveofthesystemcapabilities(businessviewpoint).

ForAItechnology,thearchitectureviewpointscanhelpcurrentandaspiringprovidersandoperatorsofAI-enabledIIoTsystemstoidentifyandgaugethevaluethatAItechnologycanbringtothesystem’sdesignandoperation.TheviewpointsfacilitateasystematicwaytoidentifyindustrialAIsystemconcernsandtheirstakeholdersandbringsimilarorrelatedconcernstogethersotheycanbeanalyzedandaddressedeffectively.Thedeliberationoftheconcernsisoftenperformedwithineachoftheviewpointstowhichtheybelong,buttheyshouldnotberesolvedinisolationtothoseinotherviewpoints.

2BUSINESSVIEWPOINT

Thebusinessviewpointattendstotheconcernsofstakeholdersincludingbusinessdecisionmakers,forexampleexecutiveofficers,boardofdirectors,generalmanagers,aswellastechnicalmanagersandplantmanagers.Theviewpointencompassestheirbusinessvision,valuesandobjectivesinestablishinganAI-enabledIIoTsysteminitsbusinessandregulatorycontexts.

BusinessViewpointofIndustrialAI

MaximizevalueandimprovetheROI

•Uncovervaluableinsightsfromdataintensiveenvironments

•Enabledigitaltransformaon

•Actasagentforthefuture-proofingoftheorganizaon

Figure2-1.IndustrialAIFrameworkBusinessViewpoint.Source:IIC.

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organizationanditsecosystemthroughadirectimprovementoftheROI.Forexample,AIcan

As

Figure2-1

shows,theprimaryconsiderationofthisviewpointistomaximizevaluetothe

moreeffectivelyprovideinsightssuchasincreasingproductionthroughput,avoidingorreducing

operatingcosts,deliveringhighermargins,enablingnewcapabilities,minimizingmistakes,

reducinginventory,improvingsafety,makingbetterandfasterdecisionsandimprovingthe

qualityofproducts.

TheapplicationofAIcanalsomaximizevalueindirectlyasaresultofimprovingsocietalaspects.Forexample,AIcanincreasetheaccuracyofdiseasediagnosis,helpexpertspredictnaturaldisastersbetter,improveeducationthroughone-on-onetutoringofstudents,promoteagradualevolutioninthejobfieldandreduceon-the-jobhazardsbyenablingautomatedsystemsandrobotstodohazardoustasks.Theseindirect(andnotsoindirect)benefitscanalsoleadtoimprovementsoftheorganization’sROI.

2.1UNCOVERVALUABLEINSIGHTSFROMDATAINTENSIVEENVIRONMENTS

IIoTsystemswithconnecteddevices,people,andenvironmentsgeneratesignificantamountsofdatawithcomplexrelationshipsacrosstheorganization’ssilosandecosystems.

Thisoverwhelmingamountofdataexhibitsthetypicalcharacteristicsofbigdatasuchasvolume,variety,velocity,veracityandvalue(orlackthereof).“Value”canbeelusive,buttheorganizationcanuseAItoanalyzeanduncovervaluableinsightfromthisdata.ThiscanhelptheorganizationidentifywaystoimprovetheROI,makeeffectivedecisionsanduncoverhiddenrisksthattheorganizationmaybefacing:financial,operational,governance-related,etc.

AIenablesvaluecaptureacrossanincreasinglydiversearrayofusecasesandindustries.OneresearchbriefingestimatesthatAIapplicationshavethepotentialtocreatebetween$3.5trillionand$5.8trillioninvalueannuallyacrossninebusinessfunctionsin19industries.

5

nn

Anotherstudyestimatesthatby2030,AIwillprovidea26%boostinGDP,equivalenttoa$15.7trillion

6

contributiontotheeconomy.ThemostimportantvaluedriverforAIisnotthetechnologyitselfbut“theproximityofwhereitisappliedtoprofits.”

7

2.2ENABLEDIGITALTRANSFORMATION

TheapplicationofAItechnologycanhelptransformtheenterpriseintoasmartdigitalenterpriseandenablethecreationofnewandtransformativetypesofbusinesses.AIcanalsoactasa

5McKinsey:

NotesfromtheAIFrontier:ApplicationsandvalueofAIdeeplearning.https://mck.co/3k4qlMe.

6PwC:

Sizingtheprize,PwC’sGlobalAIStudy,ExploitingtheAIRevolution.https://pwc.to/384ugU5.

7Forbes:

PasttheAIHype:WhenisAIActuallyProfitable.

https://bit.ly/3g9Lu6V.

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s

catalystfordigitaltransformation(DX)initiatives

8

thatcangeneratemorevaluefortheorganizationthanproductdesignIP.

9

Digitaltransformationisajourney(see

Figure2-2)

fromthe“mountingchallenges”facingtheorganizationtothe“betterandtransformationaloutcomes”thatcanaddressthesechallenges.Thejourneyisunderpinnedbybusiness,technologyandtrustworthinessfactors.

AchievingsuccessintheDXjourneyrequirestheactiveengagementofthestakeholderswhowillinvariablybringdifferentperspectivesanddivergingexpectationsaboutwhatDXmeansforthem:strategy,program,process,project(s)ortechnologies.

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MounngChallengesandDrivers

Strategy?

Program?

TransformativeProcess?

Project(s)?

Technologies?

Be弋er

Outcomes

BusinessFactors

TechnologyFactors

TrustworthinessFactors

DigitalTransformaon[inIndustry]

Figure2-2.DigitalTransformationJourney.Source:IIC.

AIplaysasignificantroleindisruptingtheorganizationandempoweringitsdigitaltransformationjourney.WhilesomeapplicationsofAIarenicheandselective,mostaredisruptiveandtransformativeinnature.

Backin2019,IDCpredictedthatby202175%ofDXinitiativeswillleverageAIservices.Thispredictionhasheldtrue.AIisallowingorganizationstobecomemoreinnovative,moreflexible,moreefficientandmoreadaptive.Inanindustrialcontext,itisenablingmachinestoensurethatmachinesoperateproperlyandoptimally,measuringandoptimizingproductivityofprocessesandprovidingpredictivemaintenancerecommendations.

AI-basedIIoTsystemsarealsoopeningupopportunitiestocommercialandpublicentitiestore-assess,optimizeandre-deploytheirworkforcefortheemergingdigitalworkplace.

8IIC(September2020):

DigitalTransformationinIndustry

whitepaper.

9

DigitalTransformation,SurviveandThriveinanEraofMassExtinction,Chapter3.

ThomasSiebel.

https://amzn.to/2W25j9d.

10IICJournalofInnovation(November2021):

TheDigitalTransformationJourneyintheEnterpriseandits

Leadership.

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2.3AGENTFORFUTURE-PROOFINGTHEORGANIZATION

AnAI-powereddigitalenterpriseisasmartdigitalenterprisethathasthecapacitytolookforward

anduseAIasanearlywarningsystemaboutissuesthathavenotbeenthoughtaboutsuchasbusinessthreatsandmissedbusinessopportunities.Thisisequivalenttofindingoutaboutwhat“youdonotknowwhatyoudonotknow”.Thiscantaketheorganizationtoadifferentlevel.

ThecapacityofAItoactasanagentforsucha“futureproofing”roleisespeciallyvaluablefororganizationswhereconvergingITandOTsystemsrequirethatfunctionsthatexecuteinIIoTsystemsbeintegratedwithfunctionsthatexecuteinbusinesssystems.Thisinvolvesacomplexmergeofkeysystemcharacteristics,bestpracticesandorganizationalcultures.AItechnologyisuniquelysuitedtospansuchintegratedIT/OTenvironmentsanduncoverthreatsandopportunitiesthatarenotpossibleforhumanstodiscern.

Inadditiontoitsprofoundimpactonorganizations,AImayultimatelyredefinethestrategicvalue

ofITfororganizations,raisingthestakesfortheneedforAIgovernance.

2.4AIADOPTIONREADINESS

MostAI-focusedpublicationsfocusonthedesignanddevelopmentconsiderationsoftheAImodelsthemselves.Thissectionfocusesonthereadinessandmaturityrequirements

11

neededtomakeAImodelsworkforenterprises(industrialorotherwise),howtodefinerequirementsforAIapplications,howtoimproveAImodelscontinuouslyintermsofapplicationanddomain-specificcorrectness,accuracy,fairnessforthoseapplicationsinthesocialsettingsandhowtocustomizegeneral-purposemodelstospecificusecases.

Ingeneral,toachievematurityinAIenvironments,thereshouldbeanemphasison:

•automation:offeringnewpossibilitiesforbothclientsandstakeholders,

•informationsharing:offeringpredictionsandinsightstodecision-makersandplanners,

•discovery:offeringabaselineformoreeffectivenessandefficiencyand

•transformation:offeringanintelligencedrivenenterprise.GartnerfurtherbreaksdownAImaturityintofivelevels:

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•Level1,Awareness:EarlyAIinterestwithriskofoverhyping,

•Level2,Active:AIexperimentation,mostlyindatasciencecontext,

•Level3,Operational:AIinproduction,creatingvalue,

•Level4,Systemic:AIispervasivelyusedfordigitalprocessandchaintransformationand

•Level5,Transformational:AIispartofbusinessDNA.

GartnersuggeststhatorganizationsaspiringtouseAIeffectivelyshouldaimtobeatmaturitylevel3orhigher(machinelearninginitsfunctions,havingMLengineerstomaintainmodelsand

11IBM:CharacterizingMachineLearningProcess:AMaturityFramework.

https://bit.ly/3k1zbun.

12Gartner:

AIMaturityModelG00466009(2020).

https://gtnr.it/3ssF5IH.

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createnewdatapipelinesandaninfrastructurethatsupportsAI-enabledprocesses).ThoseplanningtouseindustrialAItoenabledigitaltransformationshouldaimforatleastlevel4,withanIIoTsysteminfrastructurethatsupportsAI-enabledprocessesandAItrainedstaffinthefield.

IIoTsystemshavelonglifecycles(decadesforexample).ThisislongerthanthetimeanAItechnologyneedstoreachtherequiredlevelsofreadinessandmaturitytobeappliedwithinanIIoTsysteminaneffectivemanner.

ThedecisiontouseaparticularAItechnologyinanIIoTsystemshouldbebasedbothonshort-termreadinessandmaturity,andonmediumandlong-termconsiderations.Insomecases,themediumandlong-termconsiderationsmaybethedecidingfactorsinfavorofusingAI,withappropriatemitigationmeasurestakentocaterfortheinitialperiodoflackofreadinessandmaturity.

3USAGEVIEWPOINT

Theprimaryconsiderationoftheusageviewpointistoaddresstheconcernsofstakeholdersincludingbusinessdecisionmakers,technicalmanagers,architectsandplantmanagersabouttheexpectedusageofAItechnologywithinanIIoTsystem.Thisisrepresentedassequencesofactivitiesinvolvinghumanorlogicalusersthatdelivertheintendedfunctionalityandultimatelyachievethefundamentalsystemcapabilities,asshownin

Figure3-1.

UsageViewpointofIndustrialAI

ConsiderationsaboutexpectedsystemusageofAItechnology

•IndustrialAImarketandapplicaons

•Usageconsideraons

•Trustworthiness,maturity,ethical,andsocietalconcerns

•Policies,impactonlabor,AIforgood

Figure3-1.IndustrialAIFrameworkUsageViewpointandItsStakeholders.Source:IIC.

ThissectionencompassestheusageofAItechnologyandthatofAI-enabledIIoTsystems.ItprovidesanoverviewoftheAImarketandprovidesexamplesofusecasesinindustryinwhichAIaddeduniquecapabilitiestotheoverallsolution.ItalsodiscussesAI-relatedtopicssuchastrustworthiness,ethics,explainabilityandsocietalconsiderationsaboutAIusageinindustry.

3.1INDUSTRIALAIMARKET

AIhasbeenadoptedintocountlessapplicationsinindustrywithawiderangeofapplicationssuchaspredictivemaintenance,qualityinspectionandassurance,supplychainoptimization,equipmentcondition-basedmonitoringandmanufacturingprocessoptimization.RefertoAnnexBforexemplaryusecasesofAIinindustry.

In2019,theIoTAnalyticsfirmpredictedthat“Bytheendoftheyear,theGlobalIndustrialAImarketisestimatedatjustunder$15Bandexpectedtogrowat31%annuallytobecomea$72.5Bmarketby2025.”

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G