Ericsson Technology Review: Industrial automation enabled by robotics, machine intelligence and 5G

ERICSSON
TECHNOLOGY
5GANDINDUSTRIAL
AUTOMATION
C H A R T I N G T H E F U T U R E O F I N N O V A T I O N | # 2 ∙ 2 0 1 8

✱ 5G AND INDUSTRIAL AUTOMATION
2 ERICSSON TECHNOLOGY REVIEW ✱ FEBRUARY 15, 2018
enabledby
ROBERTO SABELLA
(ERICSSON),
ANDREAS THUELIG
(ERICSSON),
MARIA CHIARA
CARROZZA
(SANT’ANNA SCHOOL
OF ADVANCED
STUDIES),
MASSIMO IPPOLITO
(COMAU)
The combination of robotics, machine
intelligence and 5G networks will provide a
wealth of opportunities for cooperation
between robots and humans that can improve
productivity and speed up the delivery of
services for citizens.
■Mostanalystsagreethatsmartmanufacturing
islikelytorepresentthebiggestportionofmarket
revenuesfortheInternetofThings(IoT)inthe
nearfuture.Smartmanufacturingisdependenton
industrialautomation,whichreliesheavilyonthe
useofrobotsandmachineintelligence.The
factoryofthefuturewillberealizedthroughthe
digitizationofthemanufacturingprocessand
plants,whichwillbeenabledby5Gnetworksand
alltheirbuildingblocks.Asaleaderin5G
infrastructure–includingcloudtechnologies,big
dataanalyticsandITcapabilities–Ericssonis
wellplacedtotakealeadingroleinthis
transformationandpartnerwithindustriesto
developsolutionsthataretailoredtofittheir
needs.OurfruitfulcollaborationwithComau,a
worldleaderinindustrialautomation,andthe
Sant’AnnaSchoolofAdvancedStudies,ahighly
regardedacademiccenterofexcellencein
robotics,isthefirststep.
UnderstandingIndustry4.0
TheGermangovernmentlaunchedtheIndustry
4.0initiativein2011tofosterthecompetitiveness
ofitsindustriesforthedecadestocome.Seven
yearslater,wecanseethatleadingindustriesare
The emergent “fourth industrial revolution” will have a profound impact on
both industry and society in the years ahead. Robotics, machine intelligence
and 5G networks in particular will play major roles in this revolution by enabling
ever higher levels of automation for production processes.
ROBOTICS, MACHINE INTELLIGENCE AND 5G
Industrial
automation

5G AND INDUSTRIAL AUTOMATION ✱
FEBRUARY 15, 2018 ✱ ERICSSON TECHNOLOGY REVIEW 3
implementingbreathtakinglyinnovativeconcepts
asaresult.Forexample,the2017Hannover
IndustryFairshowcasedseveralinnovationssuch
ascollaborativerobots,smartmaterials,adaptive
production,andself-learningsystems,whichwere
ontheirwayoutoflabsandontorealproduction
shopfloors.Germanindustryiscommittedto
makingIndustry4.0thenewbenchmarkin
productionefficiency,withplanstoinvestEUR40
billionannuallyuntil2020.
ThestrengthoftheIndustry4.0initiativeliesin
thefactthatithasbeenajointeffortofgovernment,
universitiesandindustriessincedayone.Together
theyfostergrowth,usingfewerresources,reducing
riskandboostingproductivityandflexibility.The
initiativehasdevelopedmanygroundbreaking
conceptsthathaveresultedinaquantumleapin
thenetworkingofhumans,machines,robotsand
products.Manufacturingleadersarecombining
informationtechnologyandoperationstechnology
tocreatevalueinentirelynewways.Thesecyber-
physicalproductionlinesarecutting-edgetoday,but
willbethestandardoftomorrow.Bytheendof2017,
Industry4.0hadgrownintoatrulyinternational
initiativewithcontributorsandusersallover
theglobe,changingthebasisofcompetitionin
productionautomationforgood.
Guaranteedreal-timecommunicationbetween
humans,robots,factorylogisticsandproducts
isafundamentalprerequisiteoftheIndustry4.0
concept.Real-timedatawillgeneratetransparency
andactionableinsights,whileedgeanalyticswill
helpreapmaximummachinevalueandoptimize
production.Alloftheaboveconceptsclearly
requirestandardizationand(data)security.With
itsstandardizednetworkingcapabilities,built-in
security,guaranteedgradesofservice,aswellas
distributedcloudandnetworkslicingconcepts,5G
isaperfecttoolforadvancedindustriesthatwantto
takeadvantageofdigitaltransformation.
Terms and abbreviations
IoT–InternetofThings|OEM–originalequipmentmanufacturer|PLC–programmablelogiccontroller|
PoC–proofofconcept

Figure1showsthedevelopmentpaththatallows
industriestoevolvestep-by-steptowardthefull
Industry4.0transformationprocess[1].Itconsists
ofsixstageswitheachbuildingontheprevious
one.Eachstageincludesadescriptionofthe
necessarycapabilitiesandtheconsequentbenefit
forcompanies.Connectivityisthesecondstage,
immediatelyaftercomputerization,anditenables
theonesthatfollow.
Thetransformationofmanufacturing
Thetransformationofthemanufacturingindustry
[2]frommassproductiontomasscustomization
throughdigitizedfactoryoperationsisillustrated
inFigure2.Althoughtheindustrialrevolutionat
theendofthe18thcenturyledtotheadventof
mechanization,industrialproductionremainedat
anartisanalleveluntilthe20thcentury,whentrue
massproductionbeganwithautomotive
manufacturing.Assembly-lineproduction
becameaparadigmformassproductionandhad
far-reachingimpactsonsociety.Infact,whatis
called“Fordism”insocialsciencedescribesan
economicandsocialsystembasedon
industrialized,standardizedmassproductionand
massconsumption.Thekeyconceptisthe
manufacturingofstandardizedproductsinhuge
volumes,usingspecial-purposemachineryand,at
thattime,unskilledlabor.AlthoughFordismwasa
methodusedtoimproveproductivityinthe
Figure 1: The Industry 4.0 maturity index
1 2 3 4 5 6
What is happening?
“Seeing”
Computerization
Value
Connectivity
Digitalization Industry 4.0
Visibility Transparency Adaptability
Predictive
capacity
Why is it happening?
“Understanding”
What will happen?
“Being prepared”
How can an autonomous response be achieved?
“Self-optimizing”

automotiveindustry,theprincipleappliedtoany
kindofmanufacturingprocess.
Inrecentdecades,therehasbeenanincreasing
needforcustomizationtoallowmanufacturersto
differentiatefromcompetitorsandbroadentheir
productofferings.Inaway,theproductvariety
stimulatestheconsumermarket,providedthat
manufacturingcostsarekeptlowenoughtohave
sustainablemargins.Thefinalstepofthetrendis
“personalizedproduction.”BasedontheIndustry
4.0paradigmandleveragingonnewtechnologies
acrossthecompletevaluechainfromsuppliersto
customers,itispossibletosignificantlyincrease
theflexibilityoftheproductionline,andshorten
productionleadtimes.Thisleadstomoreaffordable
andscalablecustomization.
Thetrendfor“personal”productcustomization
isgrowing,alongwithapreferenceforonline
purchasing.Therefore,currentprocessesneedtobe
adaptedtobemoreflexibleandcustomizable,while
stillprotectinginitialinvestmentsintheproduction
line.Highspeedwirelessinfrastructuresuchas5G
networkscanfacilitatethemodification(required
bycustomizedproducts)ofOEMmachineswith
minimalimpact.
Thedigitizationoffactoryoperationsenabled
byIoTtechnologiespromisestomakethathappen.
Digitaltoolswillbeabletomonitorandcontrolall
toolsofproduction,collectingdatafromthousands
ofsensorstocreateadigitalimageoftheproduct
Figure 2: Evolution of the production paradigm toward Industry 4.0
Productvolumepermodel
Product variety
Mass
production
Mass
customization
Business
model
Craft
production
Personalized
production
1994
1850
1913
1955
1980
PUSH
PULL

beingrealized,usuallyreferredtoasa“digital
shadow.”Onceadigitalshadowhasbeencreated
foraphysicalproductandbearsitsspecificDNA,
itispossibletomanufacturethatproductmore
efficientlyandwithahigherdegreeofqualityin
thedigitizedproductionfacility.Inthisway,itis
possibletooptimizethemanufacturingprocess,
detectqualityissuesearlytopreventdefectsatthe
endoftheproductionlineandmakecontinuous
improvements.Itisalsopossibletocarryout
predictiveandpreventivemaintenance.
Thecombinationofwirelesssensorsandhigh-
capacitycommunicationnetworkssuchas4Gand
5Gplaysakeyroleinthiscontext,byenablingdata
collectionfromshop-floorlevel(productionlines)
anddatatransfertocloudsystemsforcontinuous
monitoringandcontrol.
Virtualcontrollersthatcombinecontrol,data
loggingandalarmsintoacloudplatformalsohelp
theprocessofdigitizationandsavecosts,panel
spaceandmaintenanceactivitiescomparedto
traditionalsystems.Theycancontrolawidevariety
ofproductiontoolsandarealsoasolutionfor
remotelylocatedmachinesandportablesystems
thatcanrunstandalone.
Keyautomationtrends
Makinggoodproductsisimportantforthe
successofamanufacturer,butitisnotenoughto
beprofitableandtosustainbusiness.Production
costsmustbelowenoughforasuitablemargin.
Thiscanbeachievedbyincreasinglyimproving
theefficiencyofamanufacturingsystem.
Automationisvitalforthat.Manufacturing
systemsrequireheavyinvestmentsandmustbe
designedsothattheyremainprofitableforthe
longterm.Ifmanufacturersaretoremain
competitiveinanever-changingmarketplace,
theymustcontinuouslyimprovebothproducts
andtheproductionsystems.Virtual
commissioningisthereforenecessaryto
continuouslyupgradeaproductionsystemwith
reasonableincrementalinvestments.This
requiresavirtual(computer-based)environment
thatcansimulateamanufacturingplant.
Virtualcommissioninginvolvesavirtualplant
andarealcontroller.Thesimulatedplantmodel
hastobefullydefinedatthelevelofsensorsand
actuators.Amajorbenefitofthisisthatitreplaces
theneedforrealcommissioningwithrealplants
andcontrollers,whichisveryexpensiveandtime
consuming.Instead,virtualcommissioningallows
fortheidentificationofpossibledesigndefectsand
operationalmistakesbeforeinvestmentsaremadein
physicalplantinfrastructure.Thedigitizationofthe
manufacturingplantallowsitsdesignerstoenhance
theefficiencyoftheproductionprocess,increase
theautomationdensityandoptimizethehandlingof
materialsnecessarytorealizetheproducts.
Digitizationallowstheintroductionofthe
“justinsequence”concept,wherecomponents
andpartsarriveataproductionlineaccordingto
schedule,rightintimeforassembly.Inaddition,
itcanenableatrulyleanenterprise,allowingfora
muchricherunderstandingofthecustomerdemand
andtheimmediatesharingofthedemanddata
throughoutcomplexsupplychainsandnetworks.
Smartfactoriescanproduceatafasterratewithless
waste.Industry4.0enablesamuchquickerflowof
customizedproducts.Ithasthepotentialtoradically
reduceinventoriesthroughoutthesupplychain.
Finally,itisimportanttohighlightthe“zero-
defect”concept.Insomecases,relevantpercentages
ofproductioncanendupasscrapbecauseof
manufacturingdefects.A“zero-defect”process
requiresautomaticmonitoringoftheentire
manufacturingprocess,fromthequalityofraw
materialsenteringtheproductionlinetovariances
intoolsandprocessesduringeachproduction
run.Asaclosed-loopsystem,controllersare
immediatelyalertedtoanydefects,andchanges
canbemadeimmediatelytoeliminatethesource
oftheproblem.Theapproachhasthepotentialto
dramaticallyreducescrapbydetectingproduction
errorsinstantly,eliminatingthepropagationof
defectsalongtheprocessstages.Themanufacturing
systemcouldincludeknowledge-basedloops,
providinginformationandfeedbacktootherlevels
ofthemanufacturingchain,tominimizefailuresvia
continuousoptimizationoftheproductionprocess

andthemanufacturingsystem.
Thefactoryofthefuturecouldconsistofflexible
productionislands,abletorealizedifferenttypesof
buildingblocks,withouttherigidityofconveyors
andwithtrulystandardrobotizedworkingstations.
Asaresult,agileshuttlingrobotsareneededto
transferassembledblocksfromoneproduction
islandtoanotherwithouttheneedforphysical
orvirtualrails.
Digitalfactoryelementsandtheroleof5G
Thevirtualplantconceptmakesitpossibleto
carryoutglobalsystemdesign,simulation,
verificationandphysicalmappingatamuchlower
costthanwhatispossiblewithaphysicalplant.To
doso,however,thevirtualplantrequiresnew
kindsofrobotswiththeabilitytoincreasethe
flexibilityoftheglobalproductionsystem.These
robotsneedtobemultipurposeandintelligent
enoughtoadapt,communicateandinteractwith
eachotherandwithhumans,basedonaremote
controlthatcangloballymanageacompletesetof
robotsystems.
High-qualitywirelessconnectivityisessential
tothevirtualplantconcept.Wiredconnectivity,
withitscomplexcabling,wouldnotbefeasiblein
thistypeofever-changingenvironmentduetothe
factthatcableupgradingentailshighoperational
expenditure.Thewirelessconnectivitymust
connectallphysicalelementsofaproductionplant
withmachine(computing)elementsthatareable
tocollectandprocesshugeamountsofdataand/or
withacloudthatisresponsibleforthoseoperations.
Communicationsamongalltheseelementsmust
workinachallengingenvironmentcharacterizedby
electromagneticinterferences,anddistributedover
alargeareathatcouldspanseveralbuildings.While
LTEconnectivityisrobustandcapableenoughto
copewiththatenvironmenttoday,stringentlatency
requirementswillsoondemand5Gconnectivity.
Onceahugeamountofdatahasbeencollected
throughthewirelessconnectivity,itisnecessaryto
usenewmethodstohandle,processandtransform
itintoaformatthatcanbeusedbyhumansor
machinesorboth,andtotapintothepotentialof
cloudcomputing.
Bigdataandanalyticssystemsaretherefore
essentialinthedigitalfactory.Eventually,acyber-
physicalsystemwillbeneededtohandlethe
complexproductionprocess,consistingofIT
systemsbuiltaroundmachines,storagesystemsand
supplies.Alltheaboveleadstofurtherefficiencies
inthefactory,byallowingpreventiveandpredictive
maintenancethatreducesthetimetheplantisoff-
service,minimizingproductiondelaysandavoiding
faults.Oneinterestingeffectoftheefficiency
boostisthereducedenergyconsumption.Process
reengineeringissomethingthatwillbedoneata
lowercostthantoday.
Thechallengeofconnectingrobots
ApreviousarticleinEricssonTechnologyReview
[3]explainedthebenefitofcloudroboticsfor
variousareasofindustry(manufacturing,
agricultureandtransportation)indifferent
logisticscontextssuchasharborsandhospitals.
Therisinglevelofintelligenceinrobotsallows
themtoadapttochangingconditions,whichis
positivefordevelopmentbutsignificantly
increasestheircomplexity.Connectingrobotsand
placingthiscomplexity(intelligence)inacloud
willmakeitpossibleforaffordable,minimal-
infrastructuresmartrobotsystemswithunlimited
computingcapacitytoevolve.Aspartnersinthe
“5GforItaly”program,Ericsson,theSant’Anna
SchoolofAdvancedStudies,Comauand
ZucchettiCentroSistemihavebeencarryingout
researchtogetherintheseareasforthepastthree
years.
Thecurrentindustrialcontrolsystems
architecturehasprovidedastable,secure,and
robustplatformforthepast25years.Butthese
legacysystemsarereachingendoflifeinmany
industrialapplicationssuchasrobotizedcells,and
ongoingmaintenance,andupdatesarebecoming
complicatedandexpensive.Inaddition,legacy
equipmentwasnotbuilttoensureeffectivedata
accesswithinthesesystems,whichseverelylimits
theirpotentialforremotemonitoringandcontrol.
High-speedcommunicationnetworks,wireless

infrastructureandcloudcomputingtechnologies
makeitpossibletoenrichrobotizedplantswithnew
relevantcapabilities,whilereducingcoststhrough
cloudtechnologies.Asaresult,itispossibletocreate
smarterrobotswith“brains”(virtualcontrollers)in
thecloud.The“brain”consistsofaknowledgebase,
programpath,models,communicationsupport
andsoon,effectivelytransferringtheintelligenceof
thecontrollerintoaremotevirtualcontroller.This
approachoffersmanybenefits,including:
〉〉 on-premisescloudcapabilitythatcanreside
alongsidelegacycriticalinfrastructure,allowing
foranevolutionoflegacyservicesandaplatform
fornewservices
〉〉 loweroperatingexpensesasaresultof
maximizingtheperformanceandcapacityof
avirtualizationplatform,whichprovideshigh
reliabilityandperformance
〉〉 faulttolerancetosingleandmultiplesoftware
andhardwarefaults,withminimallossofservice
〉〉 comprehensivefaultmanagement,isolationand
recovery
〉〉 highscalabilityandperformance.
Attheoutset,4GsystemsandWi-Fiwillbeused
toprovidecloudroboticswiththenecessary
connectivity,but5Gisthetargettechnologytruly
capableofdeliveringtheperformanceneededto
supporttheapplicationsofthefuture.
Theproofofconcept(PoC)thatEricsson,
ComauandTIM(TelecomItaliaS.p.A.)have
realizedtogetherisarelevantexample.Illustrated
inFigure3,thePoCconsistsofaworkingcellwith
tworobotsandaconveyor.Thefirstrobotisa
manipulatorthatpicksanobjectandplacesitinfront
ofthesecondrobot,whichemulatessolderingusing
aweldinggun.Thefinalobjectisthenplacedbythe
manipulatorontheconveyortosendittothenext
workcell.InthisPoC,wehavemovedthecontrol
logicthatdrivestheworkingstationresponsible
fortheconcurrentactionsofthetworobotsand
theconveyor.Itwouldnormallyresideinacontrol
cabinetreferredtoasastationPLC(programmable
logiccontroller),butinourPoCwehavemovedittoa
cloudplatform.Movingarelevantpartofthecontrol
tothecloudenablesthevirtualizationofthose
functionalitiesthatcanrunasvirtualmachineson
generalpurposehardware.
Figure 3: Experimenting with cloud robotics in Comau’s industrial automation lab in Turin, Italy

Figure 4: Virtualization of control in the cloud: steps toward true cloud robotics enabled by 5G
Cloud
Work cell
Station PLC
Robot controller
Robot
Latency 1ms
Latency 5ms
Latency 30ms
With LTE
With 5G
Sensors/actuators
Driver
Control loop
Task control
Task planner
Trajectory planner
Inverse kinematics
WeusedanindoorLTEnetworkinstallationto
connecttheelementsoftheworkingcellwiththe
cloudserver,whichwaspossiblebecausetheLTE
connectivityensuresafewtensofmillisecondsof
roundtriplatency.AsshowninFigure4,thenext
stepwillbetomovethecontrolfunctionalitiesthat
resideineachrobotcontroller–thetaskplanner,
trajectoryplannerandinversekinematics–tothe
cloudaswell.Thatstep,requiringalatencyofthe
orderof5ms,requires5Gtechnology.Thelaststep
wouldbetomovethecontrolloopoftherobotinto
thecloudaswell.
ThisPoCrepresentsakeyelementofthefactory
ofthefuture,allowingeasierimplementationofnew
controlfeatures,avoidingtheneedfornewPLC
hardwarewhennewactuatorsaredeployed,and
permittingthedeploymentofadifferentlevelof
controlfunctionsonthesameplatform:factory,cell,
actuatorlevel.Cooperativedevicecontrolisalso
possible.
Cooperationbetweenhumansandrobots
Oneofthemostinterestingaspectsofthefourth
industrialrevolutionistheemergenceofhuman-
robotcooperation.Thepresentandfuture
challengeistodeveloprobotsthatcansupport
humanworkersinameaningfulwaytoperform
manipulationandassemblytasksaccordingtoa

productionprogram.Arobotthatworksclosetoa
humanworkermustinteractsafelyandbeableto
‘understand’andinterpretdirectusercommands
andsupporttheworkerinexecutingdifferent
actions.
Collaborativeroboticsisanovelparadigm
ofhuman-robotcooperationthatisbasedon
lightweightandflexiblerobotsthataresafe,smart,
andeasytoprogram,andareintendedtooperate
inclosesymbiosiswithhumanworkers.Compared
withthepreviousgenerationofrobots,collaborative
robotsrequiresensorysystemstodetectand
preventcollisionsandimpacts,aswellashuman-
robotinterfacestounderstandandinterprethuman
intentions.Forthesereasons,massiveeffortsin
roboticsandautomationresearcharededicated
tothedevelopmentofsensoryskinsandproximity
sensors,andtothedesignofnovelinterfacesthat
enabledifferentkindsofcommandsfromtheuserto
therobot.
Robot-humancooperationinthefactoryof
thefuturewillmakecomplexdecision-making
advancementspossible.Forexample,collaborative
robotscanhelphumansby:
〉〉 evaluatingcomplexrealitiesandproviding
synthesizedandunderstandable
representationsthatenablebetterdecision
making
〉〉 helpingthemtounderstandrisksinadvance
andtherebyreducetheprobabilityoffaultsor
fatalities
〉〉 makingtime-sensitivedecisionswhena
humanisnotavailabletodoso.
Conclusion
Cooperationbetweenhumansandintelligent
machinesisanewrealitythatwillhaveaprofound
effectonbothindustryandsocietyintheyears
ahead.Alreadytoday,itispossibletoleveragea
combinationofhumanwisdomandintuition
togetherwiththestrongelaborationcapabilitiesof
artificialintelligence,artificiallearningand
thinking,tocreatesolutionsthatprovideahigh
levelofindustrialautomation.Thenextstep,the
factoryofthefuture,willberealizedthroughthe
digitizationofthemanufacturingprocessand
plants,whichwillbeenabledby5Gnetworksand
alltheirbuildingblocks.
Asaleaderin5Ginfrastructure,includingcloud
technologies,bigdataanalyticsandITcapabilities,
Ericssoniscommittedtoplayingaleadingrole
inthistransformation.Thefirstresultsfromour
cooperationwithComauandtheSant’AnnaSchool
ofAdvancedStudiesareveryencouraging,and
suggestthatweareinagoodpositiontobeakey
partnerformanyindustriesintheyearstocome.
ROBOT-HUMAN
COOPERATIONINTHE
FACTORYOFTHEFUTUREWILL
MAKECOMPLEXDECISION-
MAKINGADVANCEMENTS
POSSIBLE

Further reading
〉〉 Ericsson white paper, 5G Systems, January 2017, available at:
https://www.ericsson.com/assets/local/publications/white-papers/wp-5g-systems.pdf
〉〉 Ericsson white paper, 5G Radio Access, April 2016, available at:
https://www.ericsson.com/assets/local/publications/white-papers/wp-5g.pdf
References
1. GünterSchuhetal.,Industrie4.0MaturityIndex,Acatechstudy,availableat:www.acatech.de/fileadmin/
user_upload/Baumstruktur_nach_Website/Acatech/root/de/Publikationen/Projektberichte/acatech_STUDIE_
Maturity_Index_eng_WEB.pdf
2. YoramKoren,TheGlobalManufacturingRevolution:Product-Process-BusinessIntegrationand
ReconfigurableSystems,JohnWileySons,Inc.,2010,availableat:http://onlinelibrary.wiley.com/
book/10.1002/9780470618813
3. EricssonTechnologyReview,June2016,Cloudrobotics:5Gpavesthewayformass-marketautomation,
availableat:https://www.ericsson.com/en/publications/ericsson-technology-review/archive/2016/cloud-
robotics-5g-paves-the-way-for-mass-market-automation

Roberto Sabella
◆ joined Ericsson in 1988
after having graduated in
Electronics Engineering at
the University of Rome “La
Sapienza” the year before.
He is manager of the Italian
branch of Ericsson Research
and leader of the Innovation
with Industries in Tuscany
initiative related to the 5G for
Italy program in cooperation
with TIM. His expertise
covers several areas of
telecom networks, such as
packet-optical transport
networks, transport
solutions for mobile
backhaul and fronthaul, and
photonics technologies for
radio and data centers. He
has authored more than
150 papers for international
journals, magazines and
conferences, as well as
two books on optical
communications, and holds
more than 30 patents.
Andreas Thuelig
◆ joined Ericsson in 1991.
He is currently responsible
for the 5G for Europe
program, which focuses
on the relevance of 5G for
industries and Industry 4.0.
During his time at Ericsson,
he has held leading positions
in systems and technology
organizations and in product
management and solution
management.
He holds an M.Sc. in
electrical engineering from
the RWTH Aachen University
in Germany.
Maria Chiara
Carrozza
◆ contributed to this article
in her role as coordinator
of the neuro-robotics area
in the BioRobotics Institute
at the Sant’Anna School of
Advanced Studies in Pisa,
Italy. She is also a partner in
IUVO, a startup in wearable
robotics that was founded
in 2015 as a spinoff from
the institute. She served as
rector of Sant’Anna from
2007 to 2013, when she
was elected to the Italian
national parliament and was
appointed to the Foreign and
European Affairs Committee.
She has been president
of the Italian National
Bioengineering Group since
2016 and became a member
of the Agency for Digital
Italy’s task force on Artificial
Intelligence in 2017.
Massimo Ippolito
◆ contributed to this article
in his role as innovation
manager at Comau, a
multinational company
specializing in industrial
automation, where he has
worked since 2012. He
holds a Ph.D. in industrial
production engineering from
Parma University and an
M.Sc. in computer science
from the University of Milan.
He has extensive experience
in methodologies and tools
for product and production
system design. Since
2000, he has been involved
in various international
research projects in
the product design and
manufacturing area, ranging
from methodologies
for product design for
manufacturing to process
design for energy efficiency.
From 2007 to 2012, he was
responsible for a Fiat Group
innovation research program
on manufacturing purpose.
theauthors
Theauthorswish
toacknowledge
MarzioPuleriand
GiulioBottari
atEricsson
Researchand
GuidoRumiano
andPietro
Cultronaat
Comaufor
theirvaluable
contributionsto
thisarticle.

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Ericsson Technology Review: Industrial automation enabled by robotics, machine intelligence and 5G