理特咨詢-2023年工業(yè)元宇宙報(bào)告（英）-2023

2023Place

chart

/

diagram

/

image

hereThe

IndustrialMetaverseMaking

theinvisible

visible

todrive

sustainable

growth“What

amI?The

data?

Theprocess

thatgeneratesit?

Therelationshipsbetweenthenumbers?”—GregEgan,science

fictionauthor,Permutation

CityThe

Industrial

MetaverseMaking

theinvisible

visible

to

drivesustainable

growthAuthorsDr.

Albert

Meige,

Director

ofBlue

Shift,

Arthur

D.

LittleRickEagar,

Partner

Emeritus,

Arthur

D.

LittleContri

butorsEngin

Beken,

Partner,

Arthur

D.

LittleMartin

Glaumann,

Partner,

Arthur

D.

LittleBernd

Schreiber,

Partner,

Arthur

D.

LittleArnaud

Siraudin,

Associate

Director,

Arthur

D.

LittleJaime

Capdevila,Consultant,

Arthur

D.

LittleOlivia

Dehlin,

Business

Analyst,

Arthur

D.

LittleArtist-in-residenceLeo

Blondel,

scientist3Executive

summaryPreamble681.

Whatis

thecontextfor

theIndustrial

Metaverse?122.

Whatdoes

Industrial

Metaversereally

mean?2232Interlude:Make

theinvisible

visible3.

Whereis

Industrial

Metaversetechnology

today?364.

Whatis

thepotential

valueof

theIndustrial

Metaverse

to

business?506068725.

What

shouldcompanies

do?Appendix#1:

Technology

readiness

levelsAppendix#2:Selectedcompany

prof

ilesAppendix#3:Industrial

Metaverseusecases805ExecutivesummaryInbusinessandpopular

media,

theMetaverse

hype

wave

isalreadyentering

its

disillusionment

phase,

supersededby

artificial

intel-ligence

(AI).

Yet

theIndustrial

Metaverse,

perhapsless

exciting

inthepopular

imagination,

hasnever

really

beenpartof

thehype.

Isthiswhere

thereal

value

of

theMetaverse

will

berealized?There

are

differing

views

aboutwhat

theIndustrial

Metaverse

is

versusthe

Metaverse

as

a

whole,

and

how

it

differs

from

existing

digital

twintechnologies

normally

considered

under

Industry

4.0.

In

this

Report,

weprovide

an

evidence-based

perspective,

assessingcurrent

technologystatus,

summarizingusecases

and

market

potential,

and

offeringrecommendations

for

companiesgoing

forward.Weconclude

that

theIndustrial

Metaverseisbestdefinedasa

“con-nected

whole-system

digital

twinwith

functionalities

to

interactwith

thereal

systeminits

environment,allowingdecisionmakersto

better

understand

thepastand

forecast

the

future.”

Assuch,

theIndustrial

Metaverseisa

further

evolution

of

discrete

digital

twintechnologies

thatalready

exist

today

(e.g.,

for

factoriesor

plants)butprogressively

extended

to

ultimately

representanend-to-end,real-worldindustrial

system,includingexternal

elementsoutsidethecompany

and

theenvironment

within

which

it

operates.

TheIndustrial

Metaverse

thusprovides

a

transformative

tool

to

elevatetheuseof

digital

simulation

technology

to

thelevel

of

strategicdecision-making.

Thisisimportant

for

dealingwith

theincreasingcomplexity

andacceleratedpaceof

development

company

leadersfaceandisespecially

valuable

for

developing

effective

sustainablegrowth

strategies.6While

achieving

a

full-scale,

connected,

end-to-end,

whole-systemdigital

twin

may

be

five

or

more

years

away

—

especially

due

to

devel-opment

gaps

in

connectivity,

computing

capacity,

and

scaled-up

AI

—intermediate

steps

are

possible

in

the

short

term,

and

many

IndustrialMetaverse

use

cases

already

exist.

Thesecan

be

grouped

into

four

cate-gories:(1)

optimization

(e.g.,

digital

twinsand

augmented

reality

[AR]

foroperations/maintenance

efficiency

and

productivity

improvements);(2)

training

(e.g.,

virtual/remote

training

tools);

(3)

technical

tools

(e.g.,design/construction/maintenance

digital

tools);

and

(4)

managementtools

(e.g.,

virtual

meeting/collaboration/interaction

tools).

The

nextdevelopment

steps

will

include

extending

digital

simulations

beyonddiscrete

physical

assets

toward

multiple

connected

assets,

internalprocesses,

and

functions,

and

finally

extended

upstream

and

down-stream

activities

involving

the

entire

industrial

system.TheIndustrialMetaverseWe

estimate

thecurrentIndustrial

Metaverse

market

tobearoundUS$100-$150billion,witha

conservative2030

forecast

of

around$400billionbutwitha

potential

upsideof

more

than$1

trillion.

Thebenefits

tobusinessin

terms

of

productivity

couldbemultipledouble-digit

percentages.

The

growth

of

theIndustrial

Metaversewill

not

necessarily

dependonwidespread

adoption

of

theconsumerMetaversebecauseits

utility

and

value

for

businessdependmoreonthequality

of

complex

systemsimulationandlesson

featuressuchasimmersivity

andhuman-machineinterface

technology.Our

con-clusionis

that

theIndustrial

Metaversehaselements

of

both

evolu-tionandrevolution:

evolution

in

terms

of

thepotential

for

furtherstepwise

penetration

of

Industry

4.0

technologies,andrevolutionin

terms

of

how

theconvergence

of

these

technologies—

especiallyconnectivity,

AI,complex

systemssimulation,and

visualizationpow-ered

by

increasingcomputingcapacity

—

has

thepotential

to

trans-formbusinessproductivity.provides

atransformativetool

to

elevatetheuseof

digitalsimulationtechnology

to

thelevel

of

strategicdecision-making.Companiesneed

toconsider

their

strategy

for

theIndustrialMetaversein

thecontext

of

their

broader

digitalization

strategy,whilealsoconsideringimplementationbarriers.

We

recommend

thatcompaniesconsider

four

steps

to

reap

thebenefits:1.

Review

strategy.

Develop

a

clear

picture

of

the

digitalizationstrategy,

journey,

and

current

position.2.

Identify

opportunities.

Discover

value-adding

IndustrialMetaverse

opportunities

and

develop

a

roadmap.3.

Implement

pilot

projects.

Adopt

a

test-and-learn

approachand

manage

change

proactively.4.

Build

and

align

the

ecosystem.

Create

a

win-win

situationwith

ecosystem

partners.7PreambleWhenI

wasa

child,

10or

11

years

old,

I

remember

thinking

thatif

it

were

possible

to

“scan”

thepositions

andspeedsof

all

theatoms

andmolecules

that

make

upmybody

at

a

given

momentandputall

thisinformation

ina

computer

capable

of

simulatingall

thephysico-chemical

reactions

that

govern

theuniverse,

thenthisdigital

copy

would

not

bedistinguishable

from

theoriginal.There

would

thenbe

twoof

“me”—

theoriginal,

basedoncarbonchains,and

thedigital

copy,

whosesubstrate

would

besilicon.

Thecopy

would

beasconscious

as

theoriginal,

andit

would

be

just

asconvinced

of

beingme.8I

didn’tknowit

yet,butI

hada

materialistic

approach

to

conscious-ness.I

didn’tknowaboutHeisenberg’suncertainty

principle,

whichprohibitsknowingwith

infinite

precision

thepositionand

thespeedof

thesameparticle.

Thus,

theperfectscanwas

therefore

not

pos-sible.

Not

to

mention

thecomputingpower

required

torunsuchasimulationisstill

quite

far

frombeingavailable.

However,

withoutknowingit,I

hadconceptualizedwhat

theindustry

wouldonedaycall

“digital

twins.”Many

years

later,

my

friend

David

Louapre,

Scientific

Director

atUbisoftandcreator

of

thepopular

“Scienceétonnante”

YouTubechannel,recommended

thatI

read

thescience

fictionbookPermutation

City

by

Australianauthor

Greg

Egan,

releasedin1994.Immersingmyself

inPermutation

City,

thedigital

twinstory

of

mychildhoodsuddenly

cameback

tomelikea

Proust

digital

madeleine.Becauseindeed,oneof

thekey

elements

of

theplotisbasedonthe

fact

thatin

thenear

future,

around

2050,

itbecamepossible

toupload

one’sconsciousness

toa

computer.

The

problemis

thatinorder

for

a

person’s

digital

twin

tobeable

to

interact

witha

personin

thereal

world,

their

simulationmustrun

fastenough—

thatis,enoughcomputingpower

mustbeavailable.

If

thecomputingpowerisinsufficient,

the

timeof

thesimulatedperson,although

remainingsubjectively

unchanged,passesmore

slowly

than

thereal

time.

Andif,

on

thecontrary,

thecomputingpower

isexcessive,

thesimulatedworld

unfolds

faster

than

thereal

world.It

thenbecomespossible

toforesee

the

future.There

wouldthenbetwoof

“me”—theoriginal,basedoncarbonchains,andthedigitalcopy,whosesubstrate

wouldbe

silicon.9These

are

exactly

theobjectives

thatweseek

to

achieve

with

theIndustrial

Metaverse.

TheIndustrial

Metaverseis

theextension

ofwhathasbeencalled“Industry

4.0”

for

at

leasta

decade.Itis

thedigital

twinof

a

complex

system

thatallows

you

to

project

yourselfthrough

timeandimmerse

yourself

inspace.Itmakes

itpossible

tonumerically

anticipate

the

futureconsequencesof

a

decisionor

aneventona

complex

system—

whatever

thissystem:a

machine,afactory,a

company,a

valuechain.Aswewill

seein

thisReport,

theIndustrial

Metaversehas

threemajor

advantages

over

Industry

4.0:1.

Modeling

and

simulation

of

complex

systems—

approachesthat

were

still

part

of

the

academic

world

10

years

ago

and

thatare

now

changing

the

game

in

the

industrial

world

—

make

itpossible

to

create

virtual

what-if

scenarios.

The

accessible

datais

no

longer

just

data

from

the

past

and

the

present,

but

is

nowalso

data

about

the

future.

It

becomes

possible

to

project

intime.2.

Thanks

to

AI

and

virtual

reality

(VR),

it

finally

becomes

possibleto

bring

out

meaning

and

visualize

the

industrial

system

thatmust

be

managed

and

thus

overcome

the

limits

of

the

humanbrain,

which

is

not

well

adapted

to

apprehend

a

complex

systemand

its

emergences

—

the

famous

butterfly

effect,

resultingfrom

a

decision

or

an

event.3.

Interoperability

and

interconnectionbetween

the

physicalindustrial

system,

its

digital

twin,

and

the

various

stakeholdersnow,

more

and

more,

make

it

possible

to

manage

it

optimally.10Thanks

to

the

IndustrialMetaverse,

it

has

become

pos-sible

to

make

the

invisible

vis-ible

to

drive

sustainable

growth.While

ensuring

economic

growth,we

believe

that

the

IndustrialMetaverse

will

be

part

of

thesolution

to

the

climate

challenge.And,actually,

itisinteresting

to

note

thatananagram

of

MétaversIndustriel

(Industrial

Metaverse)is:verduresmi

litantes/mi

litantgreeneryThisisquite

intriguingand,asalways,anagrams

moveinmysterious

ways.–

AlbertMeige,PhD11112131

What

is

thecontextfor

theIndustrialMetaverse?Industrial

Metaverse

isa

term

com-monly

applied

to

theset

of

Metaverseapplications

designed

for

businessusers.

Inour

previous

Report,

“TheMetaverse,

Beyond

Fantasy,”

welookedat

theMetaverse

asa

whole,

its

appli-cations,

underlying

technologies,

andimpact.In

thisReport,

we

focus

spe-cifically

onMetaverse

applications

forbusinessesandenterprises,

thereforeexcluding

applications

andexperi-ences

for

individual

consumers(e.g.,gaming,entertainment,

andsocialinteraction),

although

there

isanoverlap

where

consumersinteract

withbusinessesat

thecustomer

interface.14Today,theIndustrial

Metaverseasa

conceptisboth

commonlyunderstoodand,at

thesame

time,

variously

interpreted.Businessmanagersare

already

well-versedin

thepotential

of

digitalization,andmany

are

already

well

along

thedigital

transformation

journey.Digital

modelsof

physical

productsandassets,increased

connec-tivity,andnew

visualizationsare

very

muchpartof

this

journey.Sowhatdoes

theIndustrial

Metaverse

really

bringinaddition?

How

sig-nificantis

thecreation

of

animmersive

virtual

environment

torun-ninga

typical

business?IsIndustrial

Metaverse

really

revolutionary,or

isitin

fact

more

evolutionary?In

thisReport,weexamine

thebackgroundandcontext

of

theIndus-trial

Metaverse,definewhatitmeans,setouta

conceptual

architec-ture,

explore

its

key

technological

buildingblocks,assessits

valuetobusinessbothnowandin

the

future,andproposehowbusinessesshouldgoaboutexploiting

its

potential.

The

Reportisbasedonin-houseresearch,

client

experience,andcontributions

frominterviews

with

experts

acrossindustry

andacademia.Industry

4.0&

theIndustrialMetaverse

todayTheIndustrial

Metaverseis

frequently

citedas

thenextphaseofevolution

after

Industry

4.0,

moving

from

cyber-physical

systems

toa

fully

virtualizedworld

(see

Figure1

).Fig1—

TheIndustrial

Metaverseisoftenseenas

thenextphaseof

evolutionafter

Industry4.0IndustrialMetaverseVirtualizationIndustry4.0Cyber-physicalsystemsIndustry3.0AutomationIndustry2.0Mass

productionIndustry1.0Mechanization18th/19th

century?19th/20th

century?1960s

onward2010s

onwardToday

onwardSource:

ArthurD.

Little15The

term“Industry

4.0”

(or

theFourthIndustrial

Revolution)

waspopularizedarounda

decadeagoandrefers

to

thedeploymentof

a

wide

range

of

technologies

with

thepotential

to

transformindustry

throughnewcognitive

tools,

connectivity,

virtual

modeling(includingdigital

twins),

collaboration

tools,andnew

techniques

formanufacturingandsupply

chain,includingadvanced

roboticsandblockchain

(see

Figure2).Of

these

various

technologies,someare

especially

relevant

for

theIndustrial

Metaverse.

Theseinclude

AI,connectivity

technologies,virtualizationandsimulation

technologies,andcollaboration/interaction

tools

(see

Chapter

3

for

further

exploration

of

keytechnological

buildingblocks).Industry

4.0

technologies

already

provide

significant

benefits

tothosecompanies

thathave

successfully

deployed

them

tohelptransform

their

businesses.For

example,

according

todata

fromcaseexamplesin

ArthurD.

Little’s

(ADL’s)

Operational

ExcellenceDatabase,

thesebenefits

are

often

double-digitinscale:-15%-30%

reductions

in

operational

capital

deployed-10%-30%

reductions

in

supply

chain

costs-30%

increased

utilization

of

production

capacity-10%-40%

reductions

in

maintenance

costsFig2—Industry4.0buildingblocksCOGNITIVECONNECTEDVIRTUALHUMAN-CENTEREDVALUE-ADDBigdata/advanced

analyticsConnectedthingsAugmentedreality(AR)Collectiveintelligence/crowdsourcingBlockchainCognitive,self-learningsystems/botsCollaborative,

smartmachines

&robotsCyber-physicalsystems/virtualizednetworksVirtual

workplace/workplace

4.0Additive

manufacturing/3DprintingAutonomoustransportsystemsSmartenergysystemsVirtual

modeling/simulationE-learning/massive

openonlinecourse(MooC)Integratedecosystems/decentral

(mobile)valueaddTechnologies

relevanttoIndustrialMetaverseSource:

ArthurD.

Little;Operational

ExcellenceDatabase,202016However,

overall

progressinachievingIndustry

4.0

maturity

still

hasa

long

way

to

go.

For

example,a

2020survey

of

70Germancompa-nies

by

Acatech

thatmeasured

progressagainsta

six-stageIndustry4.0

maturity

scaleshowed

that

the

vast

majority

of

firms(80%)werestill

in

thesecondstage

(connectivity),

with

only

a

minority

(4%)having

progressed

toward

thenext

stage

of

creating

digital

twins(visibility).

Nocompanieshadprogressed

toward

thelast

three1maturity

stages,

which

involved

modeling

complex

interactions,

sim-ulating

future-oriented

what-if

scenarios,

or

creating

self-governingsystems.

As

we

will

show

later

in

this

Report,

these

functions

are

keypartsof

what

theIndustrial

Metaverse

promises

to

deliver.Itiswell-known

thatmakingprogressonimplementation

of

digitalandIndustry

4.0

technologiesischallenging

for

any

large

company.Thisisbecauseit

typically

involves

fundamental

transformation

oftheway

thebusinessoperates;

itisnotpossible

to

simply

“bolt

on”thesenew

technologies

to

existingassets,businessprocesses,andways

of

working.

Typical

challengesinclude:Makingprogress

on

-High

initial

investment,

especially

in

data

gathering

andmanagementimplementationof-Limitations

imposed

by

legacy

IT

systemsdigital

andIndustry4.0

technologies

ischallengingfor

anylargecompany.-A

reluctance

to

embrace

the

extent

of

the

required

businesstransformation-Difficulties

in

realizing

the

targeted

business

returns

from

digitalinvestments

within

short-enough

timescalesThe

Acatech

study

alsohighlightedcommonbarriers

towardIndustry

4.0

progress,including:-A

lack

of

common

standards-Fragile

information

system

integration-A

reluctance

to

engage

in

interdepartmental

cooperation-Inadequate

employee

involvement

in

change

processesIf

weaccept

that

theIndustrial

Metaverseisa

further

stage

ofevolution

beyondIndustry

4.0,

thenit

follows

thatitssuccessfulimplementation

at

scalewill

alsorequire

overcoming

thesecommonbarriers

towardIndustry

4.0

implementation.1Schuh,Günther,

etal.“Using

theIndustrie4.0Maturity

IndexinIndustry:CurrentChallenges,CaseStudiesand

Trends.”Acatech,GermanNational

Academy

of

ScienceandEngineering,2020.17Why

thechangingbusiness

landscapeisleadingto

unmet

needsItisuseful

toconsider

how

thebusinesslandscapehas

transformedsince

theearly

days

of

Industry

4.0.

Today,

aswell

as

theconstantneed

to

further

improve

productivity,oneof

thebiggestchallengesfacingbusinessleadersishow

to

achieve

sustainable

net-zeroimpactgrowth.Contributing

to

thischallengeare

three

key

factors,asillustratedinFigure3:complexity,

acceleration,andcognition.ComplexityIndustrial

systems

are

increasingly

becomingcomplex

systems

thatare

subject

to

emergent

propertiesmaking

themmuchharder

tomanage.

A

complex

systemisa

system

havinga

largenumber

of:-Elements

(or

parts)-Relations

(connections

between

the

parts)-Nested

systems

(systems

within

the

system)Examples

of

complex

systemsincludecities,

theclimate,andlivingorganisms.

Complex

systems

differ

from

complicated

systems.Complicated

systemsrunessentially

likeclockwork,ina

predictablemanner.

They

may

have

many

elements,sub-elements,andinter-actions,but

thestructure

remains

stable

over

timeand

they

lendthemselves

to

problem

solvingusingstructured

analysis

throughdecomposition

of

theelements.

Up

to

now,

mostbusinessmanage-ment

approaches

havebeenbasedon

theidea

thata

company’sassets,processes,andorganizationcanbeapproximated

to

behave,at

leastinlargepart,likea

complicated

system.Fig3—

Thechallenges

toindustrial

organizationsComplexityAccelerationCognitionThe

complexity

of

industrialsystems

has

mushroomed……

andthe

pace

of

change

forbusinessisaccelerating

……

which

challenges

thecapacity

of

the

unaidedhuman

brain

…SUSTAINABLEGROWTH…

to

tacklecriticalcomplex

systemic

problems,

such

as

maintaininggrowth

with

net-zero

cradle-to-gravesustainability

impact.Source:

ArthurD.

Little18AccelerationHowever,

increasingly

thisapproximationisbecomingunrealistic.

For

example,consider

therecentchangesin:-Thepaceof

change

for

businessiscontinuing

to

accel-erate,causing

theseunpredictable

emergent

effectstooccur

faster

and

faster.

Three

factors

are

driving

thisacceleration:Elements.

In

the

last

two

years

alone,

the

volume

ofenterprise

data

has

risen

by

over

40%

to

more

than2

petabytes.2-Relations.

As

a

proxy

for

relations,

the

numberof

Internet

of

Things

(IoT)

connections

grew

bynearly

20%

in

2022

versus

2021,

reaching

14.41.

Knowledge

and

enabling

technologies

arebeing

developed

and

adopted

at

an

increasinglyrapid

rate,

with

a

greater

number

of

exponentialtechnologies

driving

transformational

change.billion.

Partner

ecosystem

networks

have

greatly3increased

in

size

and

complexity

in

the

last

decade.Demonstrating

this,

the

proportion

of

a

typical

carmanufactured

by

third-party

suppliers

increased2.

The

lifecycle

of

companies

and

products

isshortening.For

example,

the

average

lifespanof

S&P

500

companies

has

fallen

from

around35

years

in

the

1970s

to

around

20

years

today.Product

lifespans

in

many

sectors

are

reducing,with

increasing

rates

of

disruption

by

new

entrantsand

faster

market

penetration

times.from

56%

in

1985

to

about

82%

in

2015,that

is

still

largely

the

case

today.4a

proportion-Nested

systems.

The

number

of

nested

“l(fā)ayers”

inindustrial

system

architectures

has

increased.

Inaerospace,

for

example,

the

number

of

specificationelements

in

the

latest

passenger

jet

designs

is

morethan

10x

that

of

its

predecessors.3.

Supply

chains

are

increasingly

subject

to

changeand

disruption.

Ever

more

complex

supply

chainsand

partner

ecosystems

are

being

impacted

byglobal

and

rapid

disruptions

such

as

climate

change,pandemics,

war

in

Europe,

and

other

geopoliticalinstabilities.

Additionally,

sustainability

trendssuch

as

bio-sourcing

are

leading

to

more

suppliervariability.What

thismeansis

that

theindustrial

system

of

anylarge

company

—

plants,processes,

people,

finance,customers,

supply

chain,partners,shareholders,andtheir

environment—

increasingly

has

tobe

treatedasacomplexsystem

for

managementpurposes.Complex

systems

are

inherently

difficult

tomanagedueto

three

specific

properties:This

accelerationmeans

thatcompaniesneed

tobeableto

respond

tochangingcircumstances

more

rapidly

andmake

strategicdecisions

faster.1.

Emergence.New,

unexpected

properties

emergefrom

the

interactions

between

the

parts.2.

Non-linearity.

Feedback

loops

between

the

partsmay

lead

to

exponential

behaviors.3.

Resilience.

A

small

issue

within

part

of

the

systemdoes

not

necessarily

lead

to

its

failure.These

propertiesmean

that

thebehaviors

of

a

com-plex

system

are

very

hard

to

predict,

introducinga

highdegree

of

uncertainty

into

theimpactof

managementdecisions.Managersrelyingonsimplifiedmodelsoftheir

systems

tohelpmakedecisions

find

that

thosemodelsare

often

inadequate.Indeed,

failure

toade-quately

recognize

inherentuncertaintiesisoneof

themainreasons

why

newIT

systems

often

fail

to

delivertheexpected

benefits.234Taylor,

Petroc.“Volume

of

EnterpriseData

Worldwide2020–2022,by

Location.”Statista,23May

2022.IoT

Analytics.“IoT2022:ConnectedDevicesGrowing18%

to14.4BillionGlobally.”

IoT

for

All,1

September

2022.Kallstrom,Henry.“Suppliers’Power

IsIncreasingin

the

AutomobileIndustry.”Yahoo!News,6

February

2015.19CognitionThe

limitations

of

humancognitionmean

thatmakinggooddeci-sions

within

these

faster-moving,

unpredictable

systemsisdifficult.Thehumanbrainisnotdesigned

todeal

well

with

complexsystems—

humans

tend

to

think

ina

Cartesian

way,

breaking

problems

intosmaller

parts,which

oversimplifies

complexity.In

thesesituations,humans

tend

tobeespecially

susceptible

to

cognitivebiases—relyingoninformation

thatmatches

previousideasandbeliefsystems—

which

often

leads

to

i