>Rethinkingthecoursetomanufacturing,sfuture2

Authors

PatrickVollmer

SeniorManagingDirector–GlobalIndustryGroupLeadIndustrials

EnnoDanke

ManagingDirector–IndustryX,ASGProduction&Operations,CapabilityandDelivery

organizationlead

MatthiasWahrendorff

SeniorPrincipal-Accenture

Research,GlobalIndustrialandTransport&LogisticsLead

StefanHattula

SeniorPrincipal–Accenture

Research,GlobalAutomotive&MobilityLead

JeffWheless

PrincipalDirector–Accenture

Research,GlobalIndustrialsandIndustryXLead

>Rethinkingthecoursetomanufacturing,sfuture3

Contents

Page4

Introduction:

Today’sopportunitytoshapethefutureofmanufacturing

Page12

What'sneedednow:

Automationto

unlockefficiencyandprecision

Page5

The2040vision:

hyper-automatedfactories

Page15

What'sneedednow:

AI-drivenoptimizationtoadvancefromassistancetoautonomy

Page8

What'sneedednow:

Workforcetransformationtopreserveandaugmentcriticalknowledge

Page18

What'sneedednow:

Digitalizationtosetthe

foundationforthefactoryofthefuture

Page23

Conclusion:

Frommanagingtoorchestrating

>Rethinkingthecoursetomanufacturing,sfuture4

Introduction

Today’sopportunitytoshapethefutureofmanufacturing

Whatwillthemostcompetitivefactorieslooklikein2040?Theanswerwon,tjustbedeterminedbycostefficiencyandqualitylevels;infact,highmarksonbotharetablestakes.Therealdifferentiatorswillbeflexibility,sustainability

andintelligence—qualitiesthatwillrestonafactory’sabilitytomovebeyondtraditionalautomationandembracetheseamlessconvergenceofadvancedrobotics,data,AIanddigitaltools.

Wecallthatstatehyper-automation.It’saviablegoal—infact,it’stheinevitablecompetitive

path,accordingtothe552factorymanagerswhorecentlyparticipatedinAccenture’sin-depth,globalsurvey(seebox,“OurMethodology,”fordetail).However,gettingtherewon’tbeeasy,asmostfactoriesfaceabatteryofchallenges,includingworkforceshortages,complexbrownfieldenvironmentsandslowadoptionofAI-drivenprocesses.

Tooutlinethebestpathforward,wedrewonoursurveyfindings,coupledwithourownclient

experience.Sincetheusualplanningperiodforfactoriesinoursurveyedindustriesisaboutfivetosevenyears,anythingbeyondthatisgenerallythoughtofasa“vision.”Takingthevisionof2040articulatedbyoursurveyrespondentsasourstartingpoint,wesetouttoclosethegapbetweenwhat’sintheirsightsinthenextfivetosevenyears,andwhat’sbeyondintermsofplanning

andactions.

Thisreportfollowsthatstructure.Thefirstmajorsectionarticulatesthe2040vision—what

thefactoryofthefuturecouldlooklike.Subsequently,itoutlinesguardrailsforthestepsthat

factorymanagersneedtotakeacrossfourareas:Workforce,Automation,AIoptimizationandDigitalization.Ineach,thekeyisbalancingnear-termeffortswiththefoundationalneedsfor

thefactoryofthefuture.

OurMethodology

Accenturesurveyed552experiencedfactorymanagers

andengaged15headsofproductionindetailedqualitativeinterviewsbetweenAugustandDecember2024.Those

takingpartinthesurveyandresearchrepresented

automotivemanufacturers,automotivesuppliers,

industrialmachinerymanufacturers,industrialequipmentmanufacturers,electricalequipmentmanufacturers,

heavyequipmentmanufacturers,commercialaerospacemanufacturersandcommercialaerospacesuppliers.Theresearchcoveredfactoriesranginginscalefrom100

workerstomorethan5,000,andfromlocationsintheUS,Europe,China,IndiaandJapan.

Wefocusedourresearchonfactorymanagersbecauseoftheirvantagepointandbecausetheyaretheultimate

arbitersofwhethertheirvisionofthefuturewillbecomeareality.Theseindividualsareresponsibleforinformingstrategiccorporatedecisionsandfortranslatingthose

decisionsintoreal-worldoperations.

CompanyexamplesthatarenotsourcedarebasedonAccentureclientexperience.

>Rethinkingthecoursetomanufacturing,sfuture5

The2040vision:

hyper-automatedfactories

Thetransformationofthemanufacturinglandscapebeganin

theeraofmechanizationmorethan200yearsago.Thedriver?

Technologicaladvances.Andinthatrespect,nothinghaschangedThroughmassproduction,automation(whichwenowseeaslimitedautomation),digitalizationandnowAI,technologyhasbeenthe

drivingforcebehindrevolutionarychange.

What’sdifferentnowisthatthespeedofchangehasaccelerated.

Now,evenascompaniesareadoptingAIandfiguringouthowto

deployittotheiradvantageintoday’sfactories,theymustthink

aheadtothenextrevolution,whichisalreadyinitsnascentstages

(seeFigure1).Thatmeansplanningforandaddressingallattendantconsiderations—includingtechnologyandtalentinvestments—

andthedigitalcore,thecriticaltechnologycapabilitythatdrives

continuousreinvention.Thisisessentialforsupportingtheirfactoriesoverthenextfiveyearswhilelayingthefoundationforthenext15.

The2040vision

Figure1:

Evenastoday’smanufacturingrevolutiontakesshape—enabledbyearlyforaysintogenAI—thenextwaveoffactorytechnologyadoptionisbeginning

HyperAutomation

AtifiilIntllig

Digitalization

Atmation

MssPdtion

Mhaition

AI

1784

1870

1969

10y

2030

2040

86y99y42y201119y

Source:Accenture

The2040vision

Rethinkingthecoursetomanufacturing,sfuture6

By2040,ifcompaniesdothis,theirfactorieswilllookstunninglydifferentthantheydonow.Theywillbeself-optimizingandAI-driven,seamlesslyintegratingrobotics,digitaltwinsandhumanoversightintoanintelligentandhyper-automatedproductionecosystem.Assuch,theywillbeabletodomuchmorethanexecuteprocessesatscale.Theywillalsoanticipatedisruptions,adaptdynamicallyandoptimizeproduction,withnear-completeautonomy,inrealtime(seeFigure2).

51%

45%

Figure2:

Keyelementsofa

hyper-automatedfactory

53%

Automated

guidedvehicles(AGV)1

Autonomous

operations(I5.0)1

Completelyautomatedwarehouses1

48%

Digitally

connectedcrews1

52%

49%

49%

GenAI-based

self-learningmachines1

47%

Digital

operationstwin1

Autonomous

mobilerobots(AMR)1

Smartandconnectedmanufacturingcells1

Note1:Percentageoffactorymanagerswhoratedtheseelementsasan“8,9,

or10”onascalefrom1to10,with1

meaning“veryunlikely”and10meaning“extremelylikely’tobeimplemented

by2040.N=552;thefullhypothesesformulationcanbefoundonPage26.Source:AccentureResearchanalysis

The2040vision

>Rethinkingthecoursetomanufacturing,sfuture7

Broadlyspeaking,theenablersofthehyper-automatedfactorysortintofour

areas:workforce,automation,AI-drivenoptimizationanddigitalization.Factorymanagersunderstandtheseenablerswell.Thechallengeisturningthat

understandingintoactionsthatservethemwellinthecurrentenvironment

andalsosupporttheirlonger-termvision,especiallygiventhatvolatilityand

uncertaintywillcertainlycompoundby2040.Doingthiswillrequirerethinking

howfactoriesoperate,howtechnologyisdeployed,andhowpeopleand

machinesworktogether.Itwillrequiretakingboldstepsnowtoreskillthe

workforce,scaleintelligentautomation,embedAIintodecision-making,andfullyembracedigitalizationasthebackboneofmodernmanufacturing.

8

Rethinkingthecoursetomanufacturing,sfuture

WHAT'SNEEDEDNOW:

Workforce transformationtopreserveandaugmentcriticalknowledge

Asignificantmajority(70%)ofthefactorymanagersthatAccenturesurveyedconsiderworkforce

transformationasthemostcriticalfactorforsuccess.They’reright.Thetalentpoolformanufacturersisrapidlyshrinking.Experiencedworkersareapproachingandenteringretirement.Anddemographicchanges,alongwithyoungertalentshowinglessandlessinclinationtopursuecareersin

manufacturing,arelimitingthesupplyofnewworkers.IntheUSalone,forinstance,analystsestimatethatby2033,therewillbeamanufacturingskillsgapequivalentto3.8millionjobs.1

Nowonderthenthatfactorymanagersrateknowledgemanagement,embeddingdataanalyticsintodailyworkflowsandenablingdata-drivendecision-makingastheirtopfocusareas.

TheseactivitiesarealreadykeytoAI-drivenchange,andtheywillalsobecriticaltorealizingthe

2040vision.Yetexecutingonthemisprovingextremelychallenging.Oneissue?Thecostoftraining.Almosthalf(49%)ofoursurveyrespondentsconsidertheinvestmentintrainingasamajorhurdle.

Yetinvestingintrainingpeopleistheonlywaytorealizethefullbenefitsofthetechnology.

Workforcetransformationtopreserveandaugmentcriticalknowledge

Anotherissue?Employeeengagement.Accenture’sglobal2024

studyonchangefound,70%ofemployeesdon’tfeelengaged

inorganizationalchange.2Inpart,that’sbecausetheylackan

understandingofhowtheirworkcontributestothefuture.Butitalsocorrelatestothefearthatinhelpingthecompanyimplementnew

technologies,theyareworkingthemselvesoutofajob.Despitethe

loomingskillsgap,almosthalf(46%)ofoursurveyrespondentssaidworkersworrythatasautomationexpands,theirassemblylineroleswillbecomeobsolete.Figure3showsfactorymanagers’topprioritiesforsuccessinthenear-term(fiveyearsout),andtheirtopbarriers.It’scriticalthatcompaniesaddressthebarriersnow,notonlyforthenear-termbutalsoforthe2040vision.Factorieswillneedahighlyskilledworkforce,albeitskilleddifferently.

So,companiesneedtoidentifyandcommunicatefutureemploymentopportunitiesnow,andprovidepathwaystothoseopportunities.

Moreover,theywillneedtosetupanewmodelfortalentdevelopmentthatsupportscontinuous,real-timetraining.Mostofthefactory

workforceofthefuturewillmoveawayfromworkinginproduction

towardsworkingforproduction,whichmeanstheywillmovefrom

manuallabortoprocessoversight,decision-makingandoptimization.Theseindividualsmustalsoengageinacyclewherebytheyboth

learnfromandwithAIandteachAI,asthenatureoftheworkevolves.TheywillneedtobecomfortablecollaboratingwithAI,operating

autonomoussystemsandoverseeingcomplexautomationprocesses.

Figure3:

Factorymanagers’near-termprioritiesandlimitationsregardingworkforcetransformation

Top5prioritizedworkforcetransformationmeasures1

74%

73%

72%

72%

ProductionknowledgemanagementDataanalyticsindaytodayworkDatadrivendecisionmaking

71%

FosteringacultureofcontinuouslearningDigitalcompetenciestraining

Top5limitationsofworkforcetransformationmeasures2

49%

46%

38%

SignificantinvestmentintrainingFearsofjoblosses

Resistancetoadaptingtoexpandedroles

34%

Attractingnewtalent

32%

Workersareoverburdenedbydigitalliteracydemands

Note1:Percentageoffactorymanagerswhorated“8,9or10”onascalefrom1to10,with(1)standingfor“notatallimportant”and(10)for“extremelyimportant”.N=552

Note2:Percentageoffactorymanagerswhoselectedaspecificlimitation

Source:AccentureResearchanalysis

>Rethinkingthecoursetomanufacturing,sfuture9

Workforcetransformationtopreserveandaugmentcriticalknowledge

>Rethinkingthecoursetomanufacturing,sfuture10

Takeproductionoperations.Thejobsofthefuturewilllikelyincludehyper-automation

systemintegratorsanddigitalprocessorchestrators.Peoplewillneedtooverseede-

centralized,AI-drivenproductionnetworks,optimizereal-timeprocesses,andtroubleshootintegrationissues.Anotheremergingposition:TheAI-supportedroboticsengineer.This

personwilldesignandmaintainAI-drivenroboticmachinesandassemblylines.

Meanwhile,inqualitycontrolandassurance,jobswilllikelyincludequalityintelligence

specialists,whouseAI-drivenanalytics,InternetofThings(IoT)-sensorsandreal-time

monitoringtoensureproductintegrity,compliance,andprocessoptimization.Figure4

showsavarietyofjobsandresponsibilitiesasweenvisionthemnowacrosstheseareasaswellasmaintenance,repairandoverhaul.

Alsoneeded:arangeoflogisticsandsupplychain,andstrategicmanagementandIT

integrationroles,callingforskillsincludingstrategicplanning,AIoptimization,blockchain,real-timedataanalytics,networkcoordination,cybersecurityanddigitaltransformation.Andtheseroles,too,willevolve.

Onecompanyexhibitingthekindoffuturefocusneededtoachievethe2040vision?UK-basedautomakerJLR,holdingcompanyofJaguarLandRover.JLRhascommittedtoinvesting$25millionannuallytohelpemployeesinproductionrolesgainthenewtechnologyskillsandcapabilitiesthey’llneedtopivottonewrolesinthefuture.3

Nowisapivotaltimetothinkdifferentlyaboutthefutureofworkandtheworkforce.

Workforcetransformationtopreserveandaugmentcriticalknowledge

Figure4:

Asamplesetofjobprofilesandkeyskillsneededinthehyper-automatedfactory

ProductionOperations

QualityControl&Assurance

Logistics&SupplyChain

Maintenance,Repair,Overhaul

Management&ITIntegration

Category

Futurejobprofiles

DigitalLogisticsSpecialists:

Manageautonomouswarehousing,AI-drivensupplychains,and

blockchain-optimizeddistribution.

SmartMaintenanceSpecialists:

Usereal-timeIoTdataandpredictivediagnosticstomanagesystemhealthandpreventissues.

Cyber-PhysicalSystemsSpecialist:Developspredictivemaintenance

systemsforindustrialautomation.

QualityIntelligenceSpecialists:

UseAl-drivenanalytics,loTsensors,andreal-timemonitoringtoensureproductintegrity,compliance,andprocessoptimization.

Cyber-PhysicalSystemsSpecialist:Integratessensornetworks,digital

twins,andAl-baseddecision-makingtoautomatequalitycontrolacrossproductionlines.

AutonomousQualityControlInspector:

ManagesAI-poweredmachinevisionsystemsthatdetectmicroscopic

DigitalTransformationExecutives:Drivehyper-automation,IT

integration,cybersecurity,andcontinuousinnovation.

FactoryCybersecuritySpecialist:Securesfactorydatanetworksandimplementscybersecurityfor

Hyper-automationSystem

Integrators&DigitalProcessOrchestrators:

Overseedecentralized,AI-drivenproductionnetworks,optimizereal-timeperformance,and

troubleshootintegrationissues.

AutonomousLogisticsCoordinator:Optimizesself-drivingfactory

logisticsandwarehouseautomation.

AI-poweredRoboticsEngineer:

DesignsandmaintainsAI-driven

roboticmachinesandassemblylines.

automationinfrastructure.

AugmentedReality(AR)MaintenanceTechnician:

Conductsvirtualtroubleshootingandmachinelearning-based

maintenance.

HolographicInterfaceDesigner:

Createsholographicdashboardsforproductionmonitoringanddevelopsreal-timeinteractivefactorycontrolsystems.

Real-timeProductionOptimizationEngineer:

Responsibleforcontinuously

monitoringandimproving

automatedproductionprocessestomaximizeefficiency,minimizewaste,andenhanceOverallEquipment

Effectiveness(OEE).

Cyber-PhysicalSystemsSpecialist:Integratesandmanagessmart

factoryIoTanddigitaltwins.

defectsinproductsatultra-highspeeds.

PredictiveQualityAnalyst:

Developsandimplementspredictiveanalyticsmodelstoforecastpotentialfailuresbeforetheyoccur,preventingdefectiveoutputs.

Human-RobotCollaborationManager:

Developsprotocolsforhumanandmachineco-workingenvironments.

BionicEnhancementSpecialist:

DevelopsAI-poweredexosuitsforenhancedworkercapabilities.

AI-drivenProductionPlanner:

Ensureseamlesscoordinationof

manufacturingprocessesusing

AI-drivenproductionschedulingandreal-timeoptimization.

KeySkills&Drivers

?AI-basedprocessoptimization

?Roboticsintegration

?Real-timemonitoring

?Systemstroubleshooting

?Advancedanalytics

?IoTsensorintegration

?Predictivequalitycontrol

?Auditmanagement

?PredictiveMROanalytics

?IoTdiagnostics

?Remotemonitoring

?Automationtroubleshooting

?Autonomouslogistics

?AIoptimization

?Blockchain

?Real-timedataanalytics

?Networkcoordination

?Strategicleadership

?ITintegration

?Cybersecurity

?Digitaltransformation

?Innovationmanagement

Source:AccentureResearchAnalysis

>Rethinkingthecoursetomanufacturing,sfuture11

12

Rethinkingthecoursetomanufacturing,sfuture

WHAT'SNEEDEDNOW:

Automationtounlockefficiencyandprecision

Asignificantmajority(63%)offactorymanagersareprioritizingautomationinthemid-

term,whichisnotsurprisinggiventheimmediateopportunitiesthatautomationoffersto

improveefficiencyandreducecosts.However,onlyabout60%ofthefactorymanagersare

alsoprioritizingkeyinnovationssuchasautonomousguidedvehicles(AGVs),transforming

intralogisticsandmaterialhandlingandautonomousmobilerobots(AMRs),whichtheywill

needtofulfilltheir2040vision.Indeed,despitetheir2040vision,just38%aretargetingthe

hyper-automatedfactoryastheirpreferredconceptwhenbuildingnewunits.Thevastmajorityareprioritizinglessergoals,suchasautomatedwarehouses,synchronizedinrealtimewith

manufacturingprocesses.Alltogether,thisdatarevealsasignificantconflictbetweentoday’sprioritiesand2040’scompetitiveneeds.

Figure5illustratesthisconflict.Fromlefttoright,itshowstraditionalfactories,whatfactorymanagerscanachievebyfocusingonnear-termgains,andtwotypesofhyper-automated

factories:brownfieldandgreenfield.Thehigherthedegreeofadvancement,thebetterthe

factorywillbeabletosecureresilient,sustainable,andprofitablemanufacturinginthefuture.Thegraphicusespluses(+)torepresentperformancelevels,frombasic(+)toexcellent(++++),withexcellentrepresentingfuture-readiness.

Figure5:Automationtounlockefficiencyandprecision

Thehyper-automationadvantage

KPI

Traditionalfactory

Optimized

human-integratedfactory

Hyper-automatedbrownfieldfactory

Hyper-automatedgreenfieldfactory

Description

Aproductionmodelrelying

primarilyonhumanlaborwith

minimalintegrationof

automatedsystems.Operationsaremanuallydriven,with

workersperformingtasks.

Ahybridapproachwhere

automationisintegratedinto

workflowstocomplementhuman

roles.Automationhandlesmost

repetitivetasks,whilehumansfocusonoversightandcomplex

decision-making.

AnexistingfactoryupgradedwithAIandhumanoidrobots.

Automationisintroducedinto

pre-existinginfrastructures,

enablingamixoflegacysystemsandmoderntechnologies.

Afacility/linebuiltspecificallyfor

hyperautomation,leveraging

advancedAIsystems.Thedesign

incorporatesDesignforManufacturingprinciples,withallprocessesoptimizedforautonomousoperations.

Automationlevel

10%-30%

50%-70%

upto100%

upto100%

Flexibility

++++

++

+++

++++

Productivity

+

++

+++

++++

Quality

+

++

+++

++++

Costefficiency

+

++

++++

++++

Investment

$

$$

$$$

$$$$

Source:AccentureResearch

It’stimeforcompaniestoalignvisionwithaction,beginningbyscopingoutinmoredetailtheirjourneytothefactoryofthefuture..Tothatend,wehaveidentifiedfivekeymodelsonwhichahyper-automatedfactorymightbebased:

Themassfactory:Fullyautomatedandfullydigitizedproductionlines,whichcreatehighlystandardizedproductsinmasswithlittleorno

variation.

Themodularfactory:Fixedproductionlineequippedwithindependent,interchangeableAMRmodulesthatseamlesslyadapttoefficiently

manufacturepartiallytailoredproductswithmaximumthroughput.

Thematrixfactory:Productiontakesplaceinflexible,independentcells,allowingmultipleproductionpathsinsteadofafixedsequence,which

reducesbottlenecksandenablesproductionofcustomizedproductswithoutneedingtoredesignthefactory.

Themachine-to-productfactory:Highlyrelevantmodelforlarge

dimensionalproducts—here,specializedAMRsandhumanoidrobotsconvergetoworkontheassemblyofasingleproductonsite.

Theworkshopfactory:Produceshighlycustomizedproductsinsmallbatchesorevenlot-sizeone;characterizedbyflexible,workshop-styleproductionprocessesacceleratedthroughadvancedautomationandhumanoidrobots.

>Rethinkingthecoursetomanufacturing,sfuture13

Automationtounlockefficiencyandprecision

>Rethinkingthecoursetomanufacturing,sfuture14

Ultimately,thenatureandvariabilityofproductsandtheextentofcustomizationwilldrive

acompany’schoiceofmodel.Inanycasethough,selectingtherightpathmeansfirst

determiningwhethertransformingexistingfacilities(brownfieldapproach)orinvestinginnewfactories(greenfieldapproach)willofferthemosteconomicallyviableapproach.Andinall

cases,whileafactoryfloorcouldbefullyautomated,peoplewillcontinuetoplaycriticalroles(justnowemerging)inorchestrating,overseeing,supportingandmaintainingitsoperations.

Consider:Itwilllikelyprovemorecost-effectivetoupgradeandretrofitestablished

infrastructureswithwell-maintainedfacilitiesusingAIandhumanoidrobots,ratherthanbuildingentirelynewproductionlinesfromscratch.Infact,earlyadoptersintheautomotiveindustryarealreadytestinghumanoidrobots’potential,withpositiveresults.SeveralautomotiveOEMsin

Chinahaveachievednear-100%automationintheirbodyshopsusinghumanoidrobots.NIO4has300robots—operatedbyonlyadozenworkers—andisabletoproduce20vehiclesper

hour.Xpeng5Motorshas264intelligentindustrialrobotsworkingfullyautonomouslyacrossitsstamping,welding,painting,assemblyandbattery-packproductionworkshops.

MeanwhileBMW6deployedahumanoidrobotcalled“Figure02”atitsSpartanburgplant,

afterwhichthecompanyreporteda400%boostinefficiency.AndSchaeffler7hasinvestedinAgilityRoboticsandseesthepotentialtodeployitsDigithumanoidrobotsacrossitsglobalmanufacturingnetworkof100plantsby2030toautomatetasksphysicallydemanding,

repetitiveorhazardous.(Figure6illustratesthegrowingcapabilitiesofhumanoidrobots.)

Challengessuchasspeed,cost,andintegrationcomplexityremain,andcurrently,fewerthanhalfofoursurveyrespondents(43%)overall,seehumanoidrobotsbecomingacost-efficientstandardinassembly.However,amongrespondentsinlargefactories,thatfigurejumpsto

58%.Andit’sinterestingtonotethattheseviewsvarygeographically,with63%managersin

India,65%inChinaand72%inJapanconsideringhumanoidrobotsvaluableformanufacturingassemblylines,comparedto35%inUSand21%inEurope.Ultimately,humanoidrobotshavesignificantpotentialtobecomeastapleofmainstreammanufacturing.

Figure6:

Humanoidrobots’growingcapabilities

AIControl&Perception

Training&Validation

High

DexterityTasks

Realand

SyntheticData

Integration

Hardware(DexterityofHand+Sensors)

Source:Accenture

15

Rethinkingthecoursetomanufacturing,sfuture

WHAT'SNEEDEDNOW:

AI-drivenoptimizationto advancefrom assistancetoautonomy

Asizeablenumber(62%)offactorymanagersconsiderAIasakeyen