Table Of ContentSpringer Series in Supply Chain Management
Alexandre Dolgui
Dmitry Ivanov
Boris Sokolov Editors
Supply
Network
Dynamics
and Control
Springer Series in Supply Chain Management
Volume 20
SeriesEditor
ChristopherS.Tang,UniversityofCalifornia,LosAngeles,CA,USA
Supply Chain Management (SCM), long an integral part of Operations Manage-
ment, focuseson all elementsof creating a productor service, and deliveringthat
product or service, at the optimal cost and within an optimal timeframe. It spans
themovementandstorageofrawmaterials,work-in-processinventory,andfinished
goodsfrompointoforigintopointofconsumption.Tofacilitatephysicalflowsin
atime-efficientandcost-effectivemanner,thescopeofSCMincludestechnology-
enabledinformationflowsandfinancialflows.
The Springer Series in Supply Chain Management, under the guidance of
founding Series Editor Christopher S. Tang, covers research of either theoretical
orempiricalnature,inbothauthoredandeditedvolumesfromleadingscholarsand
practitionersinthefield–withaspecificfocusontopicswithinthescopeofSCM.
ThisserieshasbeenacceptedbyScopus.
Springer and the Series Editor welcome book ideas from authors. Potential
authors who wish to submit a book proposal should contact Ms. Jialin Yan,
AssociateEditor,Springer(Germany),e-mail:[email protected]
Alexandre Dolgui • Dmitry Ivanov • Boris Sokolov
Editors
Supply Network Dynamics
and Control
Editors
AlexandreDolgui DmitryIvanov
DepartmentofAutomation,Production DepartmentofBusinessandEconomics,
andComputerSciences SupplyChainandOperationsManagement
IMTAtlantique,LS2N-CNRS BerlinSchoolofEconomicsandLaw
Nantes,France Berlin,Germany
BorisSokolov
LaboratoryforInformationTechnologies
inSystemsAnalysisandModeling
St.PetersburgInstituteofInformatics
andAutomationoftheRAS(SPIIRAS)
St.Petersburg,Russia
ISSN2365-6395 ISSN2365-6409 (electronic)
SpringerSeriesinSupplyChainManagement
ISBN978-3-031-09178-0 ISBN978-3-031-09179-7 (eBook)
https://doi.org/10.1007/978-3-031-09179-7
©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicensetoSpringerNatureSwitzerland
AG2022
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ordissimilarmethodologynowknownorhereafterdeveloped.
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Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland
Contents
1 IntroductiontoSupplyNetworkDynamicsandControl................ 1
AlexandreDolgui,DmitryIvanov,andBorisSokolov
2 DigitalTransformationProcessTowardsResilientProduction
SystemsandNetworks....................................................... 11
DimitrisMourtzisandNikosPanopoulos
3 CollaborativeControl, Task Administration, and Fault
ToleranceforSupplyChainNetwork-Dynamics......................... 43
WinP.V.Nguyen,PuwadolOakDusadeerungsikul,
andShimonY.Nof
4 Managing Supply Chain Disruption by Collaborative
ResourceSharing ............................................................ 79
MelanieKesslerandJuliaC.Arlinghaus
5 ReconfigurableStrategiestoManageUncertaintiesinSupply
ChainsDuetoLarge-ScaleDisruptions ................................... 95
TowfiqueRahmanandSanjoyKumarPaul
6 Impact of Additive Manufacturing on Supply Chain
ResilienceDuringCOVID-19Pandemic................................... 121
MircoPeron,FabioSgarbossa,DmitryIvanov,andAlexandreDolgui
7 Short-Term Routing Models for COVID-19 Treatment
TransferBetweenHospitals................................................. 147
JebumPyun,Seayoung(Samantha)Park,andJihoYoon
8 AI-Enhanced Maintenance for Building Resilience
andViabilityinSupplyChains............................................. 163
FazelAnsariandLinusKohl
9 Building Viable Digital Business Ecosystems
withCollaborativeSupplyChainPlatformSupplyOn .................. 187
ArvidHolzwarth,CorneliaStaib,andDmitryIvanov
v
Chapter 1
Introduction to Supply Network
Dynamics and Control
AlexandreDolgui,DmitryIvanov,andBorisSokolov
Abstract Supply chain networks undergo transformations on the scale unlike
any seen before. Extensive technologyadoptionsin supply chain networks render
changes in network structures entailing multi-structural dynamics (i.e., new tech-
nologies such as Industry 4.0 and additive manufacturing lead to creating more
dynamicandreconfigurablesupplychains).Thischapterpresentsanintroductionto
thebookonsupplynetworkdynamicsandcontrolwithchaptersdevotedtotheory,
methods,andapplicationsinmanufacturing,service,supplychain,andIndustry4.0
systems.
Keywords Supplychain · Dynamics · Control · Industry4.0 · Cloudsupply
chain · Digitaltwin · Reconfigurablesupplychain
Supply chain networks undergo transformations on the scale unlike any seen
before. Extensive technology adoptions in supply chain networks render changes
in network structures entailing multi-structural dynamics (i.e., new technologies
such as Industry 4.0 and additive manufacturing lead to creating more dynamic
and reconfigurable supply chains). Technologies also allow for better observing
and controlling supply chain dynamics (e.g., through visibility and real-time data
A.Dolgui
DepartmentofAutomation,ProductionandComputerSciences,IMTAtlantique,LS2N–CNRS
UMR6004LaChantrerie,Nantes,France
e-mail:[email protected];
URL:https://www.imtatlantique.fr/en/person/alexandre-dolgui
D.Ivanov((cid:2))
SupplyChainandOperationsManagement,BerlinSchoolofEconomicsandLaw,Berlin,
Germany
e-mail:[email protected];URL:https://blog.hwr-berlin.de/ivanov
B.Sokolov
LaboratoryforInformationTechnologiesinSystemsAnalysisandModeling,St.Petersburg
InstituteofInformaticsandAutomationoftheRAS(SPIIRAS),St.Petersburg,Russia
e-mail:[email protected];URL:http://litsam.ru/index.php/en/staff-en/boris-v-sokolov
©TheAuthor(s),underexclusivelicensetoSpringerNatureSwitzerlandAG2022 1
A.Dolguietal.(eds.),SupplyNetworkDynamicsandControl,SpringerSeries
inSupplyChainManagement20,https://doi.org/10.1007/978-3-031-09179-7_1
2 A.Dolguietal.
analytics). On the other hand, the COVID-19 pandemic has strengthened the
disruption-relatedquestionsofsupplychainnetworkdynamicsandclearlyshowed
thekeyroleofdynamicscontrol,adaptability,andviabilityinsupplychainnetworks
bothatthestrategicandoperationallevels.
Overall, modern and future supply chain networks are increasingly challenged
by uncertainty and risks, multiple feedback cycles, adaptive mechanisms, and
dynamics. Supply network control is multi-faceted area and can be seen in
many ways, such as structuraldynamics, feedbackmechanisms, adaptationloops,
multi-period control of material flows, and operational dynamics (i.e., inventory
dynamics). Supply network dynamics has been studied by various methodologies
suchasoptimalcontrol,model-predictivecontroladaptivecontrol,feedbackcontrol,
ecologicalmodelling,chaostheory,complexadaptivesystems,differentialdynamic
games,systemsdynamics,complexadaptivesystemtonamejustafew.
Empirical problem settings, modelling approaches, mathematical techniques
differacrossthesemethodologiesbutmostofthemshareacommonsetofattributes:
systemevolutionovertime,dynamicchangesinthesystem,andchangesinsystem
behaviorsthroughinteractionswiththeenvironment.Assuch,differentcontroland
dynamicalsystemtheorieshavecommonalitiesintakingintoaccountthedynamics,
non-linearity,andnon-stationaryofsupplynetworkprocesses.
This book offers an introduction and advanced techniques to supply network
dynamics with applications to manufacturing,service, supply chain, and Industry
4.0 systems for larger audience. In particular, the methods of optimal control,
model-predictivecontroladaptivecontrol,feedbackcontrol,ecologicalmodelling,
chaostheory,complexadaptivesystems,networkandcomplexitytheory,differential
dynamic games, systems dynamics (but not limited to) are in the scope of this
book.Wealsoencourageempiricalresearchchapterswhichtheorizesupplynetwork
dynamicsandcontrolparadigms.
This book is intended to cover the area of SC dynamics and control at three
levels:
• SCnetworkdynamicsanalysis(e.g.,structuraldynamics)
• SCdesignandplanningdynamics(e.g.,materialflowreconfiguration)
• SCoperationaldynamics(e.g.,inventorydynamics)
The variety of quantitative analysis methodologies, optimization, simulation,
optimal control, model-predictivecontrol adaptive control, feedback control, eco-
logical modelling, chaos theory, complex adaptive systems, differential dynamic
games,systemsdynamics,Bayesiannetworks,andanalytics-drivenapproachesare
welcome. We also encourage empirical research chapters which theorize supply
networkdynamicsandcontrolparadigms.
The purpose of this book is to comprehensively present recent developments
in supply network dynamics research and to systemize these developments in
new taxonomiesand methodologicalprinciples. This book addresses the needsof
both researchers and practitioners to uncover the challenges and opportunities of
supplychainandoperationsmanagementbydynamicsystemanalysis.Wepresent
researchdonewiththehelpofdifferentmethodologiestoshowthecommonalities,
1 IntroductiontoSupplyNetworkDynamicsandControl 3
differences, and application areas of different methods to study supply network
dynamics.
The book provides both a state-of-the-artprogress and looks at new topics for
supplynetworkdynamicssuchasIndustry4.0,ViableSupplyChain,Reconfigurable
SupplyChain,digitaltwins, sustainability,cloudmanufacturing,rippleeffect,and
resilience, to name a few. For the first time, we present a book that collates
recent research on control and dynamical system applications to supply chain
and operations management. Those application areas include but are not limited
to scheduling, production and inventory control, stability, and resilience analysis.
Control and dynamical systems allow addressing conveniently some fundamental
properties of supply chains, manufacturing, and logistics systems, such as non-
linearities,informationfeedbacks,time-relatedissues,andadaptation,whichmight
bedifficulttomodelinothermethods.
DistinctiveFeaturesoftheBook:
• It uncovers fundamental principles and recent developments in control and
dynamical system theories with applications to supply chains, manufacturing,
andlogisticssystems.
• Bridging the fundamentalsof controland dynamicalsystem theories to supply
chainandoperationsmanagement.
• Systemizingnewdevelopmentsanddecipheringtaxonomiesandmethodological
principlestoshapetheresearchdomainofsupplynetworkdynamicscontrol.
• Innovativeapplicationsofuncertaintymodellingsinsupplychains,manufactur-
ing,andlogisticssystems.
• Unique multi-disciplinary view with utilization of control engineering, opera-
tionsresearch,industrialengineeringandcomputersciencetechniques.
Graduate and PhD students in industrial engineering, operations research and
managementscience, production engineers, supply chain and operations manage-
ment professionals, operations and supply chain researchers will benefit from a
varietyofchapterswrittenbytheleadingresearchersfromdifferentcontinents.
DimitrisMourtzisandNikosPanopoulosreviewintheirchapter“DigitalTrans-
formation Process Towards Resilient Production Systems and Networks” recent
advancesin adoptionof Industry4.0 technologiestowardsaccelerating the digital
transformationofglobalproductionnetworks.Theypresentaframeworkfordigital
transformation and business model change in Small Medium Enterprises (SMEs)
duringdisruption(i.e.,pandemic).Thechapterexplainshowdigitaltechnologycan
helptobuilddigital,resilient,andcloud-basedSCnetworks.
WinP.V.Nguyen,PuwadolOakDusadeerungsikul,andShimonY.Nofdescribe
in their chapter “CollaborativeControl, Task Administration,and FaultTolerance
forSupplyChainNetwork-Dynamics”howthedynamicrequirementsandbehaviors
of SC networks and their associated complex challenges can be and have been
addressedbythetoolsandprotocolsofthecollaborativecontroltheory.Thesetools
andprotocolshavebeendeveloped,tested,andimplementedbythePRISMCenter
atPurdueUniversityandbyotherresearchersandindustriesaroundtheworld.The
authorsstressthatcollaborativecontrolandcollaborationengineeringareimportant
4 A.Dolguietal.
for the successful coordination of supply activities and interactions, due to the
multiple parties involved in the supply processes and services, all subjected to
disruption, errors, conflicts, and dynamic many changes. The chapter offers an
overview of key relevant research, methods, and tools and illustrates case studies
ofsuccessfulimplementation.
Melanie Kessler and Julia C. Arlinghaus elaborate in their chapter “Managing
supplychaindisruptionbycollaborativeresourcesharing”onanempiricalevidence
for the value of collaboration in SC resilience. Based on a survey of 216 SC risk
managers of European production firms, this chapter introduces the collaborative
sharingofproductionandhumanresourcesasamethodtorecoverfromdisruptions.
Trustandcommitmentareidentifiedasthecorevaluesforthecollaborativeresource
sharing to increase SC resilience. The authors propose a framework to explicate
themaindriversforcollaborativehumanresourceandproductionsharingandoffer
firstpracticalrecommendationsforSCriskmanagerstosupporttheprocessofthe
developmentofmitigationstrategiestorecoverfromSCdisruptions.
TowfiqueRahmanandSanjoyKumarPauldevotetheirchapter“Reconfigurable
strategiestomanageuncertaintiesinsupplychainsduetolarge-scaledisruptions”
to understanding of the uncertainties in SC encountered in the wake of large-
scale disruptions. They offer implications of reconfigurable strategies to manage
uncertainties in SCs due to large-scale disruption. The authors conclude that
adoption of reconfigurable strategies to mitigate unknown-unknownuncertainties
causedbylarge-scaledisruptionsisimportanttomakethesupplychainsviable.
Mirco Peron, Fabio Sgarbossa, Dmitry Ivanov, and Alexandre Dolgui show in
theirchapter“ImpactofAdditiveManufacturingonSupplyChainresilienceduring
COVID-19pandemic”howsimulationcanhelpanalyzingthevalueofadditiveman-
ufacturinginthesettingofasuperdisruptionontheCOVID-19pandemicexample.
Using anyLogistix SC software, they define and test several pandemic scenarios
unveiling the impact of additive manufacturing usage on SC performance. They
generalize experimental results and deduce some general conclusions suggesting
howSCmanagerscanbeneficiallyuseadditivemanufacturinginapandemicsetting.
Jebum Pyun, Seayoung (Samantha) Park, and Jiho Yoon introduce in their
chapter “Short-term Routing Models for COVID-19 Treatment Transfer between
Hospitals”anoptimizationmodelforreactiveshort-termvehicleroutingsforsuch
transfers.Theoptimizationmodelcansimultaneouslygraspvehiclemovementand
cargolocationinformationwhileminimizingthetotaltraveltimeofvehicles,which
canhandletheurgencyoftreatmenttransfersbychangingthevalueofthelimited
traveltimeofvehicles.Althoughthemodeldoesnotincludeeveryconditionthatcan
beconsideredinthetreatmenttransfersbetweenhospitals,itshowsthepotentialof
themodelproposedinthetransferoftreatmentincaseofshortages.
Fazel Ansari and Linus Kohl provide in their chapter “AI-enhanced Mainte-
nance for Building Resilience and Viability in Supply Chains” an AI (artificial
intelligence)-enhanced approach for integrative modelling and analysis of SC
Key Performance Indicators (KPIs) towards building resilience and viability in
manufacturing and supply chains, aided by Dynamic Bayesian Networks (DBN).
Theyshowhowutilizingpredictiveanalyticsandsemanticmodellingmayimprove
