2023年云賦能制造報(bào)告：運(yùn)營(yíng)和IT領(lǐng)導(dǎo)者將雄心壯志轉(zhuǎn)為優(yōu)勢(shì)（英文版）-IBM商業(yè)價(jià)值研究院

IBMInstituteforBusinessValue|ResearchInsights

Cloud-enabledmanufacturing

OperationsandITleaders

turnambitionintoadvantage

Incollaborationwith

HowIBMcanhelp

IBMcanhelpmanufacturersleveragehybridcloud,AI,andautomationtoachievenewlevelsofbusinessagility.Wehelpyousetyourdirectionbasedona

time-testedIndustry4.0referencearchitectureandindustrystandards,achievescalebyconsistently

deployingadvancedshop-floortechnologiesonanopenplatform,andunleashoptimumvalueby

selectingmanufacturingprocessusecasesto

addressimmediateneeds.Formoreinformation,

visit/industries/manufacturing

HowAWScanhelp

AWShelpsleadingmanufacturerstransformtheir

operationswiththemostadvancedsetofcloud

solutions,includingmachinelearning,IoT,robotics,andanalytics.AWSallowsyoutofocusyour

resourcesonoptimizingproduction,creatingnew

smartproducts,andimprovingoperational

efficienciesacrossthevaluechain,notontheinfrastructuretomakeithappen.Formore

information,visit

/manufacturing/

1

Key

takeaways

Advanceddigitaltechnologies

underpinnedbycloudcanpowermanufacturing

transformation.

Nearlyhalf(48%)ofsurveyed

manufacturersindicatetheycanharnessmorevaluefromcloud.

Companiesneedtopivotfromafocusoncostsavings

forisolatedcloudusecasestoanend-to-end,outcome-drivencloudstrategy.

Innovativemanufacturersareleveragingcloudtobuilda

foundationfordigitaldexterity.

Asubgroupoftopperformershaveimplementeda

data-drivenculture1.7timesmorethantheirclosestpeergroup,positioningthemtoembraceemergingtechnologiesthatdriveoperationaltransformation.

Cloud-enableddigitaltechnologiessuchasAIandIoTcatalyze

reinvention.

Leadingmanufacturersaremodernizingbothhowtheyworkandthetechtoolstheyusewhileinvestinginthedigitalskillsoftheirworkforcetoelevateperformanceandproduction.

2

Capturingcloud’spotential

AstheIndustry4.0eraevolves,manufacturingorganizationshavebeensteadilyembracingcloudcomputing,withmostreporting

significantimplementationprogressin2022.1

ButrecentinsightsfromtheIBMInstituteforBusinessValue(IBMIBV)andAmazonWebServices(AWS)suggestthatmanymanufacturingorganizationsmaynot

beoptimizingthevalue—andopportunity—ofcloudasthecornerstonefordigitaltransformation.Inourglobalsurveyofmanufacturers,onlyhalf(52%)oftheirITexecutivessaytheirorganizationsareharnessingcloud’sbenefits.

Whatisholdingthemback?Threereasonsstandoutinourresearch:

–Asurprisinglylownumberofmanufacturingworkloadshavebeenmigratedtothecloud,hinderingadvancedoperationalinitiativeswherecloudcanbeakeyenabler.

–Somemanufacturerslackintegratedtechnologystrategiesthatincludecloud,AI,IoT,andapplicationmodernizationformanufacturingactivities.

–Somerespondentshavefocusedstrictlyoncostsavingsversusadditionalbusinessoutcomes,suchasimprovingperformanceandincreasingvalueacrosscore

manufacturingoperations.

Thelessonformanufacturers?Merelyadoptingcloudforsimplelift-and-shift

workloadsorstandaloneusecasesisnotenough.Amoreoutcome-drivenapproach

canhelpthemrealizebenefitssuchasboostingproductivity,quality,machineavailability,andsustainability,aswellasacceleratingengineeringeffortsandproductlifecyclemanagement.

Organizationsaretacklingthenextphaseofcomplextechnology-poweredinitiatives—includingsupplychainorchestration,qualityanalysisandresolution,materialsand

productionoptimization,andpredictivemonitoringofassets.Andtheyarelearning

thattheserequireintegrationofdata,security,andexponentialtechnologies,withthecloudasthefoundationtomakeinnovationpossible—andpowerful.Infact,our

researchhasshownthatcombiningcloudcomputingwiththeseotherleversof

businesstransformationcangenerate13timesgreaterbenefitsthancloudalone.2

Withoutamorestrategic,value-drivenapproachtocloud,digitaltransformationinmanufacturingbecomesmorechallenging.Toexplorehowmanufacturing

organizationscanunleashmorevaluefromcloudandtheadvancedtechnologiesit

enables,weanalyzedsurveyresponsesfrombothmanufacturingandITexecutivesatmorethan1,100manufacturingcompaniesworldwidetoassesstheirorganizations’digitaltechnologymaturityanddatamaturity.Respondentsworkinautomotive,

electronics,downstreamoilandgas,chemicals,metals,andindustrialmachinery(see“Studyapproachandmethodology”onpage32).Ouranalysisresultedinfourarchetypes(seeFigure1):

–ConstrainedOperators:behindtheirpeersinbothdigitaltechnologyanddatamanagement

–DigitalEnthusiasts:committedtodigitaltransformationbutlaggingintheirdatapractices

–Data-focusedDeciders:investedindatamanagementbutlackingtechnologyenablement

–TransformationalOptimizers:leveragingdataandtechnologytodrivesuccess.

FIGURE1

Manufacturers’maturityinleveragingdataanddigitaltechnologiesisdefininghowtheyunlockcloud’sdeepervalue.

Highdatamaturity

DD

Data-focusedDeciders

27%ofrespondents

TO

TransformationalOptimizers

27%ofrespondents

Lowdigital

technologymaturity

CO

ConstrainedOperators

22%ofrespondents

DE

Digital

Enthusiasts

24%ofrespondents

Highdigitaltechnologymaturity

Lowdatamaturity

Source:IBMInstituteforBusinessValue

3

Wethenpinpointedfivetraitsthatdistinguish

TransformationalOptimizers,positioningthemtooutperformtheothergroupsinkeyperformancemetricsandachievecloud-drivenbenefits:

–Amoderncloudplatform

–Arobustdatafoundation

–Digitaltechnologyintegration

–Newwaysofworking

–Businessoutcomeslinkedtocloud.

Thisreportdivesdeeperintoeachoftheseattributes,describingthearchetypes’effortsineachareato

supporttheiroperationalpriorities.Anactionguideoffersathree-stepplanformovingforwardbasedonamanufacturer’smaturityindigitaltechnologiesanddatamanagement.

4

Whyhaveonlyhalfofmanufacturingorganizationsharvestedbusiness

outcomesfromcloud?

3in4ofapplication/

systemworkloadsformanufacturing-relatedoperationshavenot

beenmigratedtocloud

3in4oforganizationshavenotestablishedintegrated

technologystrategiesacrosscloud,AI,andapplication

modernizationfor

manufacturingactivities

3in5manufacturing

andITleaderssaytheir

organizationsdonotfocusonbusinessoutcomes

oftechnologyinitiatives

ITQ.Whatpercentageofyourapplications/systemsworkloadshavebeenmigratedfromthedatacenter(s)toyourcloudestate?ITQ.Describeyourorganization’stechnologystrategiesforthefollowingactivities.ManufacturingQandITQ.Towhatextentdoyouagreewiththefollowingstatements:ITandmanufacturingfocusonthebusinessoutcomesoftechnologyinitiatives;

percentagesshowresponsesof4and5ona5-pointscalewhere1=stronglydisagreeand5=stronglyagree.

5

Traitsthattransformmanufacturing

Trait#1

Amodern

cloudplatform

Digitaltransformationisfacilitatedbyhybridcloud,whichcombinesandunifiespubliccloud,privatecloud,andon-premisesenvironmentstocreateasingle,flexible,

cost-optimalITinfrastructurethatenablesorganizationstoprocessdatawhereit

makesthemostsense.3Itenablesreal-timedatacollectedfromsensors,devices,

andmachinesonthefactoryfloortobeusedbyotherfactoryassets,aswellassharedacrossothercomponentsintheenterprisesoftwarestack,includingERPandother

businessmanagementsoftware.4

Similarly,cloudsupportstherequiredITworkloads,suchasoperationaltechnology(OT)-ITintegration,edgeanalytics,OTsecurity,andbothnewandtraditionalapplica-tions.Datafromdifferentmanufacturingoperationscanbecentralized,allowing

cross-factoryinsights,KPIcomparison,andoptimization.5Inadditiontobasiccloud

infrastructureadvantages,morethan60%ofexecutivesinoursurveysaythatadvancedcloudcapabilitiessuchascontainers,portability,andDevSecOpsareanimperativeforsuccess.

Butformanymanufacturers,theircurrentcloudarchitectureinsufficiently

supportsmostoftheirprimaryinitiatives,makingitdifficulttoorchestratethe

multipledigitaltechnologiesrequiredforimplementingthesepriorities(seeFigure2).

Forinstance,predictivemanagementofassetsmightrequirethecloud,IoT,AI,and5G.Manufacturingqualityrootcauseneedsthecloud,IoT,AI,computervision,

andedgecomputing.Withoutthecloudunderpinningtheothertechnologies,theseinitiativescouldstallorevenfail.

FIGURE2

Executivesreporttheircloudarchitectureisinadequateforsomeoftheirmostimportanttechnologyinitiatives.

Importanceofinitiative

Cloudarchitecturesupportive

Importanceofoperationaltechnologyinitiatives

versushavingasupportivecloudarchitectureinplace*

58%

Supplyorchestration

44%

Gap

57%

Manufacturingqualityrootcause

50%

Gap

Materialsoptimization

55%

49%

Gap

54%

Productionoptimization

52%

Supportive

Predictiveassetmonitoringand

performancemanagement51%

48%

Supportive

Manufacturingqualityresolution

51%

40%

Gap

Transportationoptimization

50%

46%

Supportive

*Agapisdefinedasapercentagepointdifferenceofmorethan5%.

ManufacturingQ.Howimportantarethefollowingoperationaltechnologyinitiativestoyourorganization?Percentagesshowresponsesof4and5

ona5-pointscalewhere1=notatallimportantand5=extremely

important.ITQ.Towhatextentdoesyourcloudarchitecturesupportyouroperationalinitiatives?Percentagesshowresponsesof4and5ona

5-pointscalewhere1=notatalland5=toaverylargeextent.

7

TransformationalOptimizershavemadethemostprogressinimplementingcloudtechnologiestosupportadvancedoperationalinitiatives(seeFigure3).Takesupply

orchestrationforexample—acriticalareagiventhataNationalAssociationof

Manufacturerssurveyfoundnearly80%ofmanufacturerscitedsupplychain

disruptionsastheirnumber-onebusinesschallenge.6TransformationalOptimizersreporttheircloudarchitecturesupportssupplyorchestration1.5timesmoreoftenthanpeers.Theyaregainingreal-timetrackingtomonitorandmanagetheflowofmaterialsandtrackworkinprogressandfinishedgoods.Withthisinsight,theycanpreventinventoryissuesbyinterveningwhenanissueoccurs.Manufacturing

executivesestimatethatoptimizedsupplyorchestrationcanyield37%lowersupplychaincosts.

Likewise,TransformationalOptimizersreporttheircloudarchitecturesupportsmanufacturingqualityrootcauseinitiatives1.4timesmoreoftenthanpeers.

Theabilitytoidentifyproblemsordefectsinmanufacturingprocessesandautomaterectificationtranslatestodeterminingthecauseofaproblemfasterandmitigating

recurringissues.Executivesestimatethisfocuscanreducethecostimpactofpoorqualityby57%.

TransformationalOptimizersarealsobetterpositionedforpredictivemanagementofassets—aprioritythatexecutivessaycanincreaseassetavailabilityby52%.

Usingdataandanalytics,predictivecapabilitieshelpfacilitateassetutilizationandavoidcostlydowntimeandrepairs.

8

FIGURE3

TransformationalOptimizersclaimamoremature

cloudarchitecturetosupportoperationaltechnologyinitiatives.

Percentthatsaytheircloudarchitecturesupportstheseoperationaltechnologyinitiatives

38%

TO

DE

CO

DD

36%43%60%

TO

DD

DE

CO

42%45%48%62%

TO

DD

CO

42%49%54%

51%

TO

DD

CO

DE

48%52%56%

47%

TO

DE

CO

DD

35%48%58%

TO

CO

DE

DD

26%34%45%50%

46%

TO

DD

CO

DE

47%52%

38%

Supplyorchestration

Manufacturingqualityrootcause

Materialsoptimization

Productionoptimization

Predictiveassetmonitoringandperformance

management

Manufacturingqualityresolution

Transportationoptimization

ConstrainedOperators

Digital

Enthusiasts

Data-focusedDeciders

TransformationalOptimizers

ITQ.Towhatextentdoesyourcloudarchitecturesupportyour

operationalinitiatives?Percentagesshowresponsesof4and5ona5-pointscalewhere1=notatalland5=toaverylargeextent.

Casestudies

Volkswagentransforms

manufacturingandlogistics7

IBMSystemsManufacturingscalesAIvaluebycombininghybridcloudwithedge

computing8

Totransformitsautomotivemanufacturingand

logisticsprocesses,theVolkswagenGroupbuilttheVolkswagenIndustrialCloudonAWS,whichuses

AWSIoTservicestoconnectdatafrommachines,

plants,andsystemsacrossmorethan120factory

sites.TheVolkswagenIndustrialCloudaimstoyielda30%increaseinproductivity,30%decreasein

factorycosts,andsaveover$1billioninsupplychaincosts.TheGroupisalsousingAWStoexpandbeyondmanufacturingintoride-sharingservices,connected

vehicles,andimmersive,virtualcar-shoppingexperiencestoshapethefutureofmobility.

RatherthanbuildanisolatedAIsolution,IBM

SystemsManufacturingcombinedhybridcloud

withedgecomputingtoscalethevalueofAIacrosstheglobalmanufacturingenterprise.Itdeployeda

first-of-its-kindAIvisualinspectionsystemonassemblylinesinplantsinCanada,Hungary,Mexico,andtheUS.

Thesolutionleveragescloudandedgecomputingtoeliminatebandwidthandlatencyissuesthatarise

fromrunningAIinferencinginadatacenter.TheAImodelsaredeployedtoedgedeviceswhereimagedataisprocessed,enablingthecompanytodetectanomaliesandactontheminrealtime.

AImodelsandedgedevicesaremanagedfroma

centrallocationthroughthecloud,anautomated

processthatreducessoftwaremaintenancecostsby20%.Comparedtoahumaninspector,AIautomationreducedinspectiontimesfrom10minutestoone

minuteinoneusecase.

10

Trait#2

Arobustdatafoundation

Manufacturershavemorethanenoughdatatofuelfar-reachingoperationalchanges,butapproximately90%ofthatdatastagnatesinisolatedsystems.9Cloudcomputingflipsthescript,enablingmanufacturerstocultivateaculturewherehigh-qualitydata

isdemocratizedandemployeesareskilledindigitaltechnologies.Datafrom

equipment,processes,andsystemsfeedsdeeperinsightsthatdrivecontinuousprocessimprovement.

TransformationalOptimizersdemonstratethegreatestdatamaturity,havingimplementedadata-drivenculture1.7timesmorethantheirclosestpeer—Data-focusedDeciders—and2.9timesmorethanConstrainedOperators.

Theseleadersareleveragingthecloudandothertechnologiestostrengthendatamanagementpractices(seeFigure4).Forexample,nearlytwo-thirds(63%)of

TransformationalOptimizershaveteamsofdataexpertswhoareskilledincloudservices,andtheyhavenearreal-timecapabilitiestoupdatedatarepositories.Thishelpsensurethatemployeescantapintothemostcurrentdataforinsightsthatpowerimprovedfactoryoperations.

11

FIGURE4

Cloudunderpinsstrongdatamanagementpracticesto

sharpenfactoryoperations.

43%

TO

DE

CO

DD

Teamsofdataexperts

arepro?cientwithcloudservices

Near-toreal-timeupdatestodata

repositories

APIsareusedfor

internaldata-sharingactivities

APIsareexposedtosharedatawithanecosystemofthirdparties

Sensitivedatahasbeenmigratedandencryptedincloud

45%

51%63%

TO

CO

DD

26%38%

52%

TO

DE

DD

CO

33%40%43%

51%

TO

DD

CO

DE

49%

31%36%40%

TO

CO

DE

DD

Percentthatareimplementingthesedatamanagementpractices

25%29%40%49%

ConstrainedOperators

Digital

Enthusiasts

Data-focusedDeciders

TransformationalOptimizers

ITQ.Towhatextentdoesyourmanufacturingorganizationusethefollowingdatamanagementpractices?Percentagesshowresponsesof4and5ona

5-pointscalewhere1=notatalland5=toaverylargeextent.

Casestudy

PanasonicConnect

conquerscomplexitywithshop-flooranalytics10

Tosupportchipmanufacturersadaptingtonewsemiconductorpackaging

trends,PanasonicConnecthasinfusedadvancedanalyticsintotwoprocesscontrolsolutionsthathaveemergedasthecompany’sfirstsmart-factoryofferings.

Thefirstsolutioncreatedanadvancedplasmadicer—aspecializedtoolformoreprecisecuttingandprocessingofsemiconductorwafers—byfully

automatingthe“recipe”generation,whichdeterminestheoptimal

combinationofdecisionsonvariablesthataffecttheprocess.Thissolutionreducedthedevelopmentcycletimebyasmuchas30%.

Thesecondsolutionoptimizedplasmacleanermachineperformance

throughsmarter,data-drivenmaintenancepractices.Thecombinationofreducedunnecessarymaintenance,proactivepartsordering,andfewermachineoutageshelpeddecreasemaintenancecostsformanufacturingcustomersby50%.

Data-drivenmaintenancepracticeshelpeddecreasemaintenancecostsfor

manufacturingcustomersby50%.

Trait#3

Digital

technologyintegration

Manufacturersrecognizetheimportanceofdigitaltechnologiestotheirinitiatives.

IoTsensorsmonitorplantproduction,energyconsumption,inventory,andasset

maintenance.Additivemanufacturing—alsoknownas3Dprinting—enablescreationofbespokepartsandsupportsagiledesignchanges.AIhelpsautomatemanufacturing

productionprocessesandimprovequalitycontrol,whilethegrowthofgenerativeAIopensthedoortoevenmoreadvancedAIusecases(seePerspective,“AnticipatingtheboostfromgenerativeAI”onpage17).

Thesetechnologies,whendeployedinconcert,propelinnovation.Thecloudenablesthatintegration.TransformationalOptimizersareintegratingthecloudwithenablingtechnologiestoagreaterextentthanpeersinallareasexceptAI,whereData-focusedDecidersarelikelycapitalizingontheircommitmenttodata(seeFigure5).

13

14

FIGURE5

Cloudplatformsenableintegrationofdigitaltechnologiestospurinnovation.

Percentthatareintegratingthesedigitaltechnologieswithcloudplatforms

53%

TO

DD

CO

DE

63%66%

55%

TO

DD

DE

CO

51%

57%

48%

39%

57%

DE

TO

DD

CO

59%

43%

49%

TO

DD

CO

DE

42%

46%

60%

56%

TO

DD

DE

CO

35%

45%

25%

40%

30%

TO

CO

DE

DD

32%

46%

38%

TO

DE

DD

26%

48%

45%

InternetofThings

Roboticprocessautomation

Additivemanufacturing(3D)

AI

Robots

Edgecomputing

5G

ConstrainedOperators

Digital

Enthusiasts

Data-focusedDeciders

TransformationalOptimizers

ITQ.Towhatextentdoyourcloudplatformsintegratewiththe

followingdigitaltechnologiesinyourmanufacturingorganization?Percentagesshowresponsesof4and5ona5-pointscalewhere

1=notatalland5=toaverylargeextent.

OnetechnologythatfusesthepowerofIoTandbothtraditionalandgenerativeAIforenormouspotentialbenefitstothemanufacturingindustryisdigitaltwins.Offeringavirtualrepresentationofasystemacrossitslifecycleandupdatedfromreal-timedata,digitaltwinsusesimulation,machinelearning,andreasoningtostrengthendecision-makinganddriveefficiency,innovation,andcompetitiveness.11Transformational

Optimizersareusingdigitaltwinsdramaticallymorethantheirpeers(seeFigure6).

FIGURE6

Leadingmanufacturersusedigitaltwinstocombinereal-timesimulationandcontrols.

Useofdigitaltwinsinmanufacturingoperations

38%

ProductionoptimizationQualitymanagementPredictivemaintenance

TransformationalOptimizers

56%62%60%

Data-focusedDeciders

47%

Digital

Enthusiasts

25%

38%

48%

ConstrainedOperators

23%

33%

49%

42%

ManufacturingQ.Towhatextenthasyourorganizationuseddigitaltwinsinthefollowingareasofyourmanufacturingoperations?

15

Percentagesshowresponsesof4and5ona5-pointscalewhere1=notatalland5=toaverylargeextent.

16

Similarly,TransformationalOptimizersreportheightenedsecurityreadinessthroughthecloud(seeFigure7).TheyrecognizethatthecombinationofAIandthecloudis

criticaltodefendingagainstcyberthreats.AsITandOTbecomemoreintertwined,

theOTnetworkandconnectedOTdevicesareincreasinglyexposedtosecurityrisks,whileremoteaccesstoOTnetworksbyoutsidevendorsfurtherexpandsvulnerabil-ities.Infact,IBMX-Force?reportedthatmanufacturingcontinuedtobethetop

attackedindustryin2022.12

FIGURE7

TransformationalOptimizersarebuildingcyberresiliencewithrobustsecuritypractices.

Adoptionofsecuritypractices

44%

AmatureOTorICSpatchmanagementprogramisinplace

RobustOT/industrial

controlsystem(ICS)assetinventoryisdeveloped

Incidentsaremanagedwithauni?edAIautomation

acrossenvironments

TransformationalOptimizers

63%62%58%

Data-focusedDeciders

39%

Digital

Enthusiasts

35%

43%

49%

Constrained

Operators

26%

29%

40%

47%

ITQ.Towhatextenthasyourmanufacturingorganization

adoptedthefollowingsecuritypractices?Percentagesshowresponsesof4and5ona5-pointscalewhere1=notatalland5=toaverylargeextent.

Perspective

Anticipatingtheboostfrom

generativeAIinmanufacturing

OurstudyrevealsthatmanufacturingexecutivesexpectgenerativeAItoimprovemanufacturingprocessesacrossarangeofareas(seefigure).

Foursignificantpillarsofimpactinclude:

Productionqualityandoptimization.GenerativeAIsystemscaningestalargeamountofproductiondataandproactivelydetectqualityissuesinproduction.

ThecombinationofIoTandgenerativeAIcanidentifyreal-timeanomaliesandoptimizeproduction

accordingly,ultimatelyimprovingoverallequipmenteffectiveness.

Sourcingandprocurement.Offthefactoryfloor,generativeAIcanassistwithvendordiscoveryandevaluation,pricing,supplychainriskassessment,andcontracts.

Predictivemaintenance.Withassetsensorscontinu-ouslymonitoringvariablessuchastemperature,flow,andpressure,generativeAImodelscanleveragethedatatorecognizethenormaloperationalbehaviorofequipmentandthenidentifydeviationstopredictandrectifyequipmentissues.

Productdesignanddevelopment.Anarrayof

alternativesforproducts,parts,components,and/ormaterialscanbecreatedbygenerativeAImodels.

Usingvariablesspecifiedbyengineerssuchascost

andoperationalcriteria,generativeAIalgorithmscanhelpcreateentirelynew,innovativedesigns.

OperationswhereexecutivesexpectgenerativeAItohaveanimpact

1 2 3

4

Identi?cation,design,anddevelopmentofproducts/parts/

5

ManufacturingQ.WheredoyouseegenerativeAIimpacting

yourmanufacturingoperations?Percentagesshow

responsesof4and5ona5-pointscalewhere1=verylowand5=veryhigh.

Casestudies

DoosanDigitalInnovationprotectsinvestmentin

digitaltransformation13

SRAMdrivesinnovationwithnext-generation

manufacturing14

DoosanDigitalInnovation(DDI)embracedtheideathataneffective,comprehensivecybersecurity

programshouldbethefoundationofdigitaltransfor-mation.Tothatend,thecompanyidentifiedand

mappedappropriaterolesandresponsibilitiesofitsstaffworkingwithinthesecurityinfrastructure.DDIalsoconsolidateditsregionalsecurityoperation

centers(SOCs)toaunified,globalSOCthatdelivers24x7monitoringandprotection.

TocontroltheoperationsoftheglobalSOC,DDI

updateditscoresecurityinfrastructure.Theteam

enhancedthecompany’sproactivesecurityincidentandeventmanagementefforts,deployingtechnol-ogiestooverseeendpointdetectionandresponse

anddeliveringAI-basedautomationthatfurther

streamlinesthreatresponses.Asaresult,thecompanyacceleratedthreatreactions,cuttingapproximately85%fromresponsetimes.

Toimprovethecyclingexperience,SRAM,abicyclecomponentmanufacturer,hasembracedtheuseof

newmaterialsandadvancedmanufacturing

techniques.WorkingwithAWSanditspartner

Autodesk,SRAMisleveraginggenerativedesign,whichisaformofAIthatusescloudcomputingtospeedtimetodesignandtimetomarketwhile

optimizingperformance.

Usinggenerativedesigntools,SRAMcannow

generatemultipleconceptsatthebeginningoftheprojectandthenevaluateeachtochoosetheonesmostpromisingtobeproducedusingadditive

manufacturing(3Dprinting).Thisapproachenabledthemtoproduceapartthatwastwiceasstrongand20%lighterinlesstimewithfewerresources.

19

Trait#4

Newwaysofworking

TransformationalOptimizershaveradicallychangedhowtheirorganizationsworkby:

–Investingindigitalanddataskills

–Trainingtheiremployeesindigitaltechnologies

–RedefiningtherelationshipbetweenmanufacturingandIT

–Establishinganoperatingmodelfortheircloudoperations.

Theyoutperformtheirpeersineachareaandgaintheaddedbenefitofmakingtraditionallymundanefactoriesmoreappealingtotechworkers.

Nurturingdigitalandtechnologyskills

Whileeacharchetypeisactivelyinvestingintechnologyskills,Transformational

Optimizersareaheadinallareas(seeFigure8).Theysensetheurgencyofhaving

employeeswhocanputintelligentautomation,data,anddigitaltechnologiestowork.

Threeinfivesaytheyaretrainingtheiremployeeswithdigitaltechnologiesand

intelligentmachines/devices,comparedtolessthanhalfoftheotherarchetypes.

FIGURE8

Manufacturingorganizationsareinvestingintheirworkforcestoclosethedigitalskillsgap.

Percentthatareinvestingintheseskillstosupportdigitalinitiatives

TO

DE

DD

45%

61%65%

TO

DE

DD

47%

55%

61%

TO

DE

DD

CO

30%39%42%53%

42%

TO

DE

CO

DD

43%

33%

48%

TO

CO

DE

DD

30%34%

39%44%

Cloudsecurity

Clouddeploymentandmigration

Roboticp