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》orkingSmarter:
HowManufacturersAre
UsingArti?cialIntelligence
KeyFindingsandInsightsfrom
Manufacturers
MAY2024
2
WorkingSmarter:
HowManufacturersAreUsingArti?cialIntelligence
May2024
KeyFindingsandInsightsfromManufacturers
NationalAssociationofManufacturers
3
>ALetterfromtheChair
Arti?cialintelligencehasdominatedtheheadlinesinrecentyears,andpeoplearetrulybeginningtograspthepossibilitiesandpowerofthistechnology.ThelaunchofChatGPTandothergenerativeAItoolshasmadethetechnologyevenmore
accessible,puttingitinthehandsofeverydayAmericans.
Manufacturershavebeenattheforefrontofdevelopingandimplementingintelligent
systemsandAItechnologies,includingmachinelearning,deeplearning,natural
languageprocessing,machinevision,digitaltwinsandrobotics.Thishaspositioned
manufacturersuniquelyasbothdevelopersanddeployersofAIinnovations,providinginvaluableinsightsintotheeffectiveandresponsibleuseofthesetechnologies.
AIcanbeaforcemultiplier—andaforceforgood.AtJohnson&Johnson,forexample,AIhasbeenused
effectivelyinanumberofareas,rangingfromthedrugdevelopmentprocesstorestockinghospitals.Ithelpsussortthroughmassiveamountsofdata,yieldinginsightsfortheimprovedhealthandwellnessofpeoplearound
theworld.Itaidsusincreatingtargetedtreatmentsandgettingthemtotherightpatientsattherighttime.Whenweconductclinicaltrials,AIhelpsusmoreef?cientlyestablishsafetyandeffectivenessguardrails,whileallowingustoconducttrialsatalargerscale.AIalsogivesusafarstrongermasteryoveroursupplychains.Overall,it
helpsourpeopledoabetterjoboflivinguptoourcommitmentofimprovinghealthcareoutcomesandmakingourtowns,countryandworldabetterplace.
AIfunctionsbestwithhumansasthecoredecision-makerswithinAI-enhancedprocesses.Theseoperators
mustbeknowledgeable,well-trainedandabletoutilizethetechnologysafelyandtoitsfullestpotential.Early
on,Johnson&JohnsondevelopedanethicalAIframework,aswellasadatascienceacademytoenhanceourteams’digitalacumenandequipthemwithAIengagementskills.AsmanufacturersupskillandtrainmoreteammemberstoworkwithAI,thetechnologywillempowerthoseworkerstobemoreinnovativeandproductive.
Asyou’llreadinthispaper,manufacturersofallsizeshavefoundsimilarwaystouseAItoamplifytheir
operationsandliveuptotheirowncommitments.WithAIsupportingus,manufacturerscandosomuchmoretoimprovethequalityoflifeforeveryone.
Giventheimportanceofthisgenerationaltechnology,policymakersmustdevelopsensible,carefullythought-outframeworksforvariousAIapplications—andtheyshouldleanonmanufacturers’yearsofexperiencetoengineerthoseframeworks.WeneedapolicyenvironmentthatsupportsinnovationandgrowthinmanufacturingAI,
becauseitwillbolsterU.S.competitivenessandleadershipinthiscriticalemerging?eld.
AllpossiblefuturesformodernmanufacturingintheU.S.involveAI.Thistechnologyisagame-changer,anditwillcontinueprovingitselftobeanessentialpartnerontheshop?oor.ThispaperofferspolicymakersawindowintothefutureofAIinmodernmanufacturing—andaroadmaptohelpusgetthere.
KathrynWengel
ExecutiveVicePresidentandChiefTechnicalOperations&RiskOf?cer,Johnson&JohnsonChairoftheBoard,NationalAssociationofManufacturers
4
>KeyInsights
nArti?cialintelligencetoolsareusedwidelyacrosstheindustryandarekeytoadvancingmodernmanufacturing.
nManufacturersareconsumers,developersanddeployersofAIthroughouttheirproductionprocesses.
nThepotentialapplicationsforAIinmanufacturingareexpansiveandcanhelpindustryleadersimproveef?ciency,productdevelopment,safety,predictivemaintenanceandsupplychainlogistics.
nAIreferstoalargeumbrellaoftechnologiesthatincludemachinelearning,machinevisionanddeeplearning.Thesetoolsallowmanufacturerstomaketheirshop?oorssafer,improveworkexperienceandcreate
innovativeproductsthatsolveglobalchallenges.
nManufacturersareimplementingandtestingAIprogramsinawaythatkeepsworkersasthecentraldriversanddecision-makersforAIprocessesorproducts.
nToremainagloballeaderinadvancingAIandsupportingmanufacturinginnovation,theU.S.shouldtakea
cautiousapproachtoAIregulation,tailoranyregulationtospeci?cusecasesandrisks,right-sizecompliance
burdens,supportR&Dandnewworkforcepathwaysandensurethatregulatoryframeworksarealignedglobally.
5
>WhatIsAI?
“WeseeAIasakeystrategicenablerfor
oureffectiveness,to
dothingsbetter,fasterandmoreeconomically,whiledelivering
essentialproductstoourcustomers.”
–SreedharSistu,
VicePresident,AIOffers,SchneiderElectric
Innovationiswhatdrivesmanufacturing,andasaresult,
manufacturershavealwaysbeenattheforefrontofnewtechnologies,strivingtooperatemoreef?cientlyandeffectively.Nowmanufacturersareleadingintheadoptionanduseofarti?cialintelligence.AIisa
broadumbrellaterm,de?nedbytheNationalInstituteofStandards
andTechnologyasa“systemthatcan,foragivensetofobjectives,
generateoutputssuchaspredictions,recommendationsordecisionsin?uencingrealorvirtualenvironments.”1Thesesystemsusedataandhuman-builtalgorithmstosimulatehowhumansperceive,learnand
respondtoquestionsandprompts.AIsystemsareoftenconnectedtoothermachinesandrespondtothedigitalandphysicalworldtosupportprocessesthatcaneitherbeverysimpleorcomplex.2
Whilerecentadvancementsinlargelanguagemodelsandchatbots,suchasChatGPTandGoogleGemini,haveplacedaspotlighton
generativeAItechnology,theseapplicationsrepresentbutafraction
ofthetypesofAIcurrentlyinuse.Infact,manufacturershavebeendevelopinganddeployingintelligent
systemsandAItechnologyformanyyears,intheformofmachinelearninganddeeplearning,natural
languageprocessing,machinevision,digitaltwinsandrobotics,allfurtherexplainedinthefollowingpages.
Theseinnovationsareoftencategorizedunderthebannerof“advancedmanufacturing”or“Manufacturing
4.0.”AIintegrationintomanufacturingprocesseshascontributedalreadytosigni?cantlyimprovedoperationsandtothedevelopmentofnewproducts.3
AIrepresentsatremendousopportunityforthemanufacturingindustry.AItechnologiescanhelp
manufacturersimprovetheiroperationsbyupgradinghowtheyanalyzelargedatasets,identifyingknowledgegaps,providingsolutionsandenablingteamstodevelopnewef?ciencesatscale.WidespreadimplementationofAIacrosstheindustrycouldleadtomoreef?cientprocesses,increasedsustainability,moreinnovative
productsandsaferworkplaces.TheseinnovationswillbothgrowtheeconomyandbolsterU.S.global
leadershipinmanufacturing.GiventhevastpotentialofAI,policyapproachestoAIshouldfurtherthe
developmentofthesetechnologiesandsupporttheirresponsibleusebymanufacturersacrossawiderangeofapplications—strengtheninginnovationand,inturn,supportingU.S.competitivenessontheworldstage.
ThisreportreviewshowAIhasevolvedwithinmanufacturingandhowmanufacturersaredevelopingand
deployingAItechnologiestoinnovatewithintheirbusinessoperationsandacrosstheindustry.ManufacturersarealeadingvoiceontheopportunitiespresentedbyAIandhavemuchtoshareabouttheirexperiences.
ThisreportconcludeswithpolicyrecommendationsthatwouldbestequipthemanufacturingindustrytotakeadvantageoftheimmenseopportunitiesAItechnologyhastooffer.TheNAMsupportsapolicyenvironment
forAIthatencouragessafe,responsibledevelopmentwhilepromotingtheinnovativegrowthofthetechnology.
1NationalInstituteofStandardsandTechnology,Arti?cialIntelligenceRiskManagementFramework(AIRMF1.0)(Washington,D.C.:
DepartmentofCommerce,2023),1,
/nistpubs/ai/NIST.AI.100-1.pdf
.
2TomCulver,LeeGreenandJimRedden,“PeeringintotheFutureofIntelligentSystems,”Research-TechnologyManagement62,no.3(May2019):21-30,
/doi/abs/10.1080/08956308.2019.1587322
.
3HailiZhang,XiaotangZhangandMichaelSong,“DeployingAIforNewProductDevelopmentSuccess,”Research-TechnologyManagement64,no.5(August2021):50-57,
/doi/full/10.1080/08956308.2021.1942646
.
6
>HowDidWeGetHere?
AIinmanufacturingismadepossiblebytheconnectednatureofmachinesandtoolsinmanufacturing
operations.Widespreaddigitalintegration,usingconnectedsensorsandinstrumentstocollectdataacrossshop?oors,enablesmachinelearning,atypeofAIthatwasdevelopedasearlyasthe1980s.4Amachinelearning
systemanalyzesdataandrecognizespatternstotrainitselftomakedecisionsandperformtasksef?ciently.
Deeplearning,anextensionofmachinelearningthatevolvedthroughthe2010s,incorporatesmultiplelayersofreasoninganddataanalysistomimichowthehumanbrainworks.5MachinelearninganddeeplearningarethebasisformostoftheAItoolsmanufacturersuse.AsofOctober2023,74%ofsurveyedmanufacturershad
investedorwereplanningtoinvestinmachinelearning.6
Arti?cialintelligence:atechnologythatcan,foragivensetofobjectives,generateoutputssuchaspredictions,recommendationsor
decisionsthatemulatehumanbehavior
Machinelearning:amodelthatuses
advancedalgorithmstoanalyzedataandrecognizepatternstotrainitselftomakedecisionsandperformtasks
Deeplearning:asystemthatincorporates
multiplelayersofreasoninganddataanalysistomimichowthehumanbrainworks
GenerativeAI:atoolthatusesdeep
learningtocreatecontent,suchastext,imagesorcode,basedondetected
patternsinlargedatasets
4JimDavis,“PuttingIntelligenceBackintoAI,”ManufacturingLeadershipCouncil(Dec.8,2020),
/putting-intelligence-back-into-ai-17349/?stream=all-news-insights
;
MichaelPlatzandShantonWilcox,“AchievingImpactfromEnd-to-EndDigitalization,”ManufacturingLeadershipJournal(January2023),
/achieving-impact-from-end-to-end-digitization-31586/?stream=ml-journal
.
5“Whatisdeeplearning?,”IBM,accessedJan.30,2023,
/topics/deep-learning
.
6PenelopeBrown,“SURVEY:ManufacturersGoAll-InonAI,ManufacturingLeadershipCouncil(Oct.1,2023),
/survey-manufacturers-go-all-in-on-ai-35350/?stream=ml-journal
.
7
>HowDoManufacturersUseAI?
Manufacturersarecollectorsofknowledge.Theybringtogethertheskillsandideasofpeople,sometimesfromallaroundtheworld,tocreatenewproducts.Thesegoodscanbeassmallandsimpleasaboltoraslarge
andcomplexasanautomobile.Themodernshop?oorisinterconnectedandtechnologicallyadvanced.This
enablesmanufacturerstocollectdataabouttheiroperationsandenhancetheirproductionprocesses.Inshort,thetechnologicalinnovationsofmodernmanufacturingenablemachinestoamplifytheproductivepowerof
manufacturingworkers—andAIisthenextstepinthisinnovativejourney.
In2023,theNAM’sManufacturingLeadershipCouncil,aglobalnetworkofexecutivesinthemanufacturing
industry,conductedsurveysonhowmanufacturersuseAIintheiroperationstoexploresomeofthewaysAIisalreadymakinganimpact.WhenaskedaboutwhytheywereinvestinginM4.0technologiesordigitally
integratedinnovationssuchasAI,respondentspointedtocostreduction,operationalawarenessandprocessoptimization,asshowninFigure1.7Thisincludesvisibilityintooperationsbycollectingandanalyzingdatatodevelopinsightintotheperformanceofamanufacturingprocess,andusingdigitaltechnologyanddatato
determineaprocess’sef?ciency,speed,equipmentutilization,materialsusage,waste,etc.,andmakingdecisionsonhowanyofthosefacetscouldbeimproved.
Figure1:WhatAretheMostImportantReasonsYourCompanyInvestsinTransformativeM4.0Technologies?(CheckTopThreeReasons)
72%
51%
41%
32%
22%
21%
19%
14%11%
11%
5%
0%10%20%30%40%50%60%70%80%
Reducecostsandimproveoperationalef?ciencyImproveoperationalvisibilityandresponsiveness ImproveprocessoptimizationandcontrolCompensateforlaborshortages
Improvequality
CreatesustainedcompetitiveadvantageImproveassetreliability
Improvespeedtomarket
ImprovecustomerexperienceMitigateimpactfromdemandswingsDon’tknow
Wherepossible,manufacturersdeveloptheirownAItoolstoaccomplishthesetasks.OtherspurchaseAI
productsfromtechnologycompanies.RegardlessofwhethermanufacturersdevelopAItechnologyordeployAItechnology—orboth—they?ndthatAIhelpseasetheburdenofrepetitivetasks,allowingmanufacturingworkerstodevotetheirenergyandtimetomorecomplicatedandforward-thinkingactivitiesandprojects.
7Ibid.
8
AsdisplayedinFigure2,respondentsnotedawiderangeofusesforAIintheiroperations,thetopthreeofwhichweremanufacturingandproduction,inventorymanagementandqualityoperations/R&D.8
ToimplementAI,manufacturersworktoidentifywhichAIsystemisbestsuitedtohelpthemtackletheir
challenges;howtoresponsiblyandtransparentlycollectthedatanecessarytotrainandruntheAImodel;andwheretoimplementAItotransformcurrentprocesses.Inthiscontext,modernmanufacturersviewdataasa
criticalinputthatcanbeleveragedandutilizedtodiscovernewef?ciencies.AIishelpingtotransformthatdataanddeploysolutionsatascalenotpossibleforhumansalone.
Figure2:WhichoftheFollowingCorporateFunctionsHaveBeguntheAdoptionofAI?(SelectAllThatApply)
ManufacturingandproductionInventorymanagementQualityoperations
R&DIT/OT
Equipmentmaintenance/installation Supplychain ProductdesignDistribution/logisticsSalesandmarketing
FinannceeHumanresourceess
CustomerserviceandsupportLegal
ProcurementSustainability
39%
33%
24%
24%
21%
17%
11%
11%
9%
7%
7%
6%
4%
3%
3%
3%
0%10%20%30%40%50%
Withthelargeamountsofdatacollectedontheshop?oorandthroughouttheiroperations,manufacturersuseAItodesignproductionprocesses,predictivemaintenanceprogramsandlogisticsdecision-makingmodels,
amongmanyotherexamples.ThesecompaniesarepushingtheboundariesofwhatAIsystemscando.ThisputsmanufacturersinauniquepositiontoguidethedevelopmentoftheAIpolicylandscape.
8DavidBrousell,JeffPumaandPaulTate,TheFutureofIndustrialAIinManufacturing(Washington,D.C.:ManufacturingLeadershipCouncil,
2023),
/wp-content/uploads/2023/06/The-Future-Of-AI-In-Manufacturing-MLC-2023.pdf
.
9
Ef?ciency
Thecontinued,expandedimplementationofearlyAItechnologies,suchasmachinelearning,hasimproved
manufacturers’ef?ciency.Greateref?ciencyallowsmanufacturerstoallocateresourcesinamorecost-
effectivemanner,improveshop?oorprocesses,implementmoresustainablepracticesanddiscovernew
opportunitiesforgrowth.IninterviewsconductedbytheNAM,onechemicalproductioncompanystatedthattheapplicationofmachinelearningtodatacollectedfromchemicalreactorsenablesoperatorstomakebetterdecisionsabouthowtooperatethem.TheAImodelalertsoperatorswhenitisoptimaltomakechangesintheprocess,ratherthanmanuallykeepingtrackofallsensorsordependingonaspeci?coperationaltimetable.
Humanoperatorsarestillatthecenterofdecision-makingandoperations,butAIhashelpedimprovethereliabilityoftheirprocessesandthequality,deliveryandsafetyoftheirproducts.
“HitachiisfocusedonapplyingAI,machinelearningandrelatedtechnologiestowardaddressingreal-worldchallengesinindustrialandsocietaldomains.
Functionalareasincludemaintenanceandrepair,operationsoptimization,qualityassurance,safetymanagement,supplychainmanagementandautomationand
control,amongothers.Thegoalistheend-to-endoptimizationofkeyindustrialprocesses.”
–ChetanGupta,GMoftheAdvancedAIInnovationCenter,Hitachi,Ltd.andHeadoftheIndustrialAILabatHitachiAmerica
MachinevisionisamorerecentadvancementinAI,enablingindustrialequipmentto“see”bygatheringand
analyzingvisualdatainitsenvironmenttoformconclusions.Almost80%ofMLCsurveyrespondentshad
investedorplannedtoinvestinvisionsystems.9Onelogisticscompanyusesmachinevisiontosortpackages,dependingonAI-enabledrobotstorespondtoandmakedecisionsbasedonever-changingsituationsand
conditionsratherthansimplyrepeatingthesamepatterns.Manycompaniesarealsousingmachinevisionto
performqualitycontrol,quicklyreviewingpartsandmaterialsfordefectsthataremoredif?cultforhumansto
detect.Forsomemanufacturers,thishasbeenaparadigmshiftandhasallowedtheirmachinesandprocessestoworkmoreef?cientlyandrespondtonewsituationsandproblemsmorequickly.
AImodelscanalsoperformpredictiveanalyticsusingdatacollectedfromdigitallyenableddevices.Aresult
ofthisanalysiscanbepredictivemaintenance,oridentifyingpartsthatarenotperformingef?cientlysothat
theycanbereplacedbeforetheybreak.MorethanhalfofMLCsurveyrespondentsstatedthatpredictive
maintenanceisakeyAIapplicationintheiroperations.10Suchef?cienciescanpreventunplanneddowntimeforproductionaswellasenhancesustainabilitybyenablingmoreenergy-ef?cientprocesses,loweringwasteanddecreasingemissions.
9Brown,“SURVEY:ManufacturersGoAll-InonAI.”10Ibid.
10
Safety
“AIgivesustheabilitytocombinedigitalandphysicalteamsandtohelpourpeoplebyreducingrepetitivetasksandphysicalstresswhile
promotingsafety.”
–JoelStenson,SeniorVicePresidentofOperations
Technology,UPS
ManufacturersareinterestedinusingAItoimprovesafety
foremployeesandoperations.OneautomotivemanufacturerisusingAIandmachinevisiontomonitorintersectionsof
productionlanes,lettingworkersknowifaforkliftorother
machineryiscomingaroundthecorner,outsideofthe
peripheryoftheirvision.ThisuseofAIhelpstoprevent
humanmistakesandgreatlyimprovessafetyontheshop
?oor.Forindividualworkers,ergonomicassistance,likea
roboticexoskeletonthatcollectsandlearnsfromdataon
thewearer’smovementsandtheenvironment,canenhancehumanstrengthandpreventinjuries.Overtime,thesetoolshavethepotentialtoimproveworkersafety,makejobslessphysicallydemandingandreducehealthcarecosts,whicharekeyconcernsforemployers.
OthercompaniesuseconnecteddevicesandAImodelingtoimprovethecustomerexperience.Infact,47%ofsurveyedmanufacturersplantodeploymorecustomer-facingAItoolsinthenexttwoyears.11Oneautomotivecompanyhasalreadybeguncollectingdatafromtheirnewestvehiclemodelsandalertingcustomerswhen
theAIidenti?eschangesintheperformanceofthevehicle,allowinguserstopreventcostly,inconvenientandpotentiallydangerousproblemslater.
ProductDevelopmentandDesign
Researchershavefoundthatproductdevelopmentcanbene?tfromusingAImodelstolearnfromaccumulateddataandthathigherAIusageinthedevelopmentprocessincreasessuccess.12ManufacturersinmanydifferentindustrysubsectorsareutilizingAItodevelopnewproducts.AsupplierofautomotivepartshascreatedanAI
toolthatprocesseswheelgeometrydata,allowingthecompanytomorequicklydevelopwheeldesignsthatperformbetterandareproducedmoreef?ciently.AIallowsthiscompanytobringproductstomarketfaster,
respondtodesignchangesmorequicklyandbetterapplytheknowledgeoftheirengineeringteam,unlockingcontinuousinnovationandlearning.
OnepharmaceuticalcompanysharedthatitisusingAImodelstoidentifynewwaystodevelopmoleculesand
advanceindividualizedtreatmentsfordisease.ThiscompanyisdevelopingtheirownAImodelsto?ndmorepreciseendpointsfortreatments,whichmakeclinicaltrialssafer,moreeffectiveandwithagreatermarginforsuccess.
Training
Manufacturerswanttokeeptheworkofpeople,notcomputers,atthecenteroftheiroperations.TheingenuityofworkersisakeycomponentinanyAIprocessesorproducts.WhenitcomestoAIinmanufacturing—workersarethedriversanddecision-makers,andAIworkstomaketheirjobseasierandmoreef?cient.ManycompanieshavefoundthattheirbestAIoutcomesresultfromenrichingemployees’experienceatwork,thusimproving
theiroutput.AItechnologyisoftenusedtocomplementandaugmenttheworkofhumans,likeaco-pilot.
Thisapproachenhancesworkeref?ciencywhilestillprioritizinghumanexperienceandingenuity—ultimately
11Ibid.
12Zhang,ZhangandSong,“DeployingAIforNewProductDevelopmentSuccess.”
11
increasingtrustandcon?denceinAIsystems.13Themosteffective
AImodelsarehuman-centered,allowingthemtolearnandunlearn,
continuouslyimprovingtomeettheneedsoftheirhumanoperators.14
Manufacturersareupskillingtheirworkforceactivelytomeetthe
opportunitiesofAI.Manycompanies,fromlogisticstopharmaceuticals,aresettinguptrainingprogramstohelpemployeesdeveloptheir
con?denceandcompetencyintheuseofAIsystems.Thesetraining
programsincludeafocusonsafetyandcontrol,tolimitriskstoworkersandtoprotectcompanies’intellectualpropertyinthefaceofthe
increasedcybersecurityrisksthatcomefromaninterconnectedshop?oor.
Recruitmentofnewemployeeshasalsochanged.Oneautomotive
suppliernotedthattheyhaveincreasedtheirhiringofthedatascientistsnecessarytobuildandimplementAIsystems.
ThemosteffectiveAI
modelsarehuman-
centered,allowingthemtolearnandunlearn,
continuouslyimprovingtomeettheneedsof
theirhumanoperators.
Attheendofworkers’careers,companiescanuseAIsystemstomanageknowledgeaskeypersonnelenter
retirement.Asof2019,nearlyone-quarterofthemanufacturingworkforcewasover55,15andoneelectri?cationandemergingtechnologycompanyisusingAI-utilizingsystemsforknowledgemanagementandtotrainnew
employeesontheskillsoflegacyworkers.TheyarealsousingAImodelstoidentifyfuturechallengesand
predictwhichskillswillbeneeded,identifyinghowmanyemployeeswillneedtobetrainedinthesenewskills.
SupplyChain
ManufacturersareusingAImodelstopredict,preventormitigatedisruptionsintheirsupplychainsandmake
moreinformeddecisionsabouttheirlogisticsplans.Thesetoolsallowtheindustrytobemoreresilienttorisk,
preventproductionstoppagesorshortagesandeffectivelydeliverproductstocustomers.ThisisagrowingareaofAIimplementation,with21%ofsurveyedmanufacturersalreadyusingAIintheirsupplychainmanagement
and60%planningtodeployitinthenext12–24months.16
13JimEuchner,“Littleai,BigAI—GoodAI,BadAI,”Research-TechnologyManagement62,no.3(May2019):10-12,
/doi/full/10.1080/08956308.2019.1587280
.
14Davis,“PuttingIntelligenceBackintoAI.”
15TheManufacturingInstituteandAlfredP.SloanFoundation,TheAgingoftheManufacturingWorkforce(Washington,D.C.,July2019),
/research/the-aging-of-the-manufacturing-workforce/
.
16Brown,“SURVEY:ManufacturersGoAll-InonAI.”
12
Inapplication,AItoolsinthesupplychaincanhelpcompaniesmakethemostoftheirinventories.One
technologyandcomputingcompanybuiltandintegratedanAIprogramthatusedmachinelearningtoassessthecommonpartsacrossdifferentareasoftheiroperations,identifyingwhenandwherepartscouldbeshiftedfromoneareatoanotherasneeded.Becausesparepartshadbeenscrappedpreviouslyifunused,using
machinelearningtoassesshundredsofpartsandgreatlyreducedpotentialwaste—anunfeasibletaskforahumanteam—hassavedthiscompanymillionsofdollarsinreplacementandsourcingcosts.ThecompanyhopestoexpandthisprojecttoincludefurtheradvancementsinAItechnology,includingdeeplearningandgraphneuralnetworks.
Intheaerospacesector,AI,speci?callymachinelearning,hasevolvedtodeliversolutionsintheareasofautonomy,suchasobstacleavoidanceandautomaticvehicletaxiing,aswellasoptimizationofcargoinairplanesthatare
connecteddigitally,andmanyotherareas.Theseadvancements,leveragingdeeplearning,continueprovidingsolutionstotechnologygapsthatwouldotherwisebehardtoachievewithtraditionalapproaches.
Morewidely,usingmodelsthattakeglobalandnationaltrendsanddisruptionsintoaccount,manufacturerscanmakeswiftchangestotheirsupplychaindecisions.Thisallowsthemtobemoreresilienttounexpectedchanges,withmodelsabletoidentifynewshippingpatterns,alteredsupplierchoicesorinventoryshocks.
>HowAreManufacturersTestingAISystems?
AsmanufacturersexpandtheuseofAItechnology,theyare?ndingmorerobustwaystoguaranteethatthesetechnologiesaresafeandreliablefortheiremployeesandcustomerstouse.ManycompaniesareapproachingAIthroughthesamekindofprovenrisk-managementframeworksthattheyusefortheirITandcybersecurity
programs.Companiesarealsodevelopingtheirowninternalgovernanceprograms.
Manufacturersareusingtestinggroups,bringingtogetherAI,ITandoperationsprofessionals,toidentifywhere
algorithmsmightbeinaccurateandtovalidatethattheirsystemsmeethighthresholdsofsuccess.WhentestingnewAIsystems,oneshippingandlogisticscompanyfoundthatinternalfacilitysafetyteamsandtheirthird-partytestingorganizationsbothneededtodevelopanewknowledgebaseandupskilltogether.
Inthiswayandothers,manufacturersarebuildingtheirowngovernanceprogramsfordataandAIsystems,
maintainingdataprivacyandconductinginternaltestingbeforenewprogramsaredeployed.Thisistrue
especiallyforheavilyregulatedindustries,suchasautomotive,pharmaceuticalsandaerospace,thatalready
mustmeetmanyofthesafetybenchmarksapplicabletothedevelopmentandtestingofsafeAIsystems.Manyareworkingdirectlywiththegovernmentalreadytodevelopcerti?cationsforcriticaltechnologiesthatdonot
disrupttheirdeploymentofAI.
>WhatShouldWeDoNow?
ManufacturersarecommittedtotheresponsibledevelopmentanddeploymentofAI.AIhasbecomecritical
tomodernmanufacturing,andAItechnologiesandcapabilitiesar
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