Digital Supply Chain Twins to Improve Resilience · 5 Supply Chain Resilience: Definition •...
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Digital Supply Chain Twins toImprove Resilience
Prof. Dr. Dr. habil. Dmitry IvanovProfessor of Supply Chain Management
Berlin School of Economics and Law, Germany
Blog.hwr-berlin.de/ivanov
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Berlin
Where we are located
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HWR Berlin Overview
• >11,000 students• 2,500 graduates annually• Teaching staff: 200 professors and 800 part-time
lecturers• Close cooperation with 700 companies in Germany
and abroad• Master (M.A.) in Global Supply Chain and
Operations Management (in English)• Organiser of 9th International Conference on
Manufacturing Modeling, Management and Control MIM 2019, August 28-30, 2019
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Outline
• Practical principles to manage Supply Chain Resilience and Disruption Ripple Effects
• Decision-making support in designing the Resilient Supply Chain by simulation and optimization
• From offline modelling to online, data-driven Supply Chain Digital Twins: computerized supply chain models in real-time
• Current technologies and future vision of using Digital Supply Chain Twins to improve resilience
Prof. Dr. Dr. habil. Dmitry Ivanov
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Supply Chain Resilience: Definition
• Supply chain resilience is the operational capability to withstand, adapt, and recover from disruptions to meet customer demand and ensure the target performance.
Disruption: An event which is not
planned or anticipated and may
affect the structure or dynamics of
systems.
Economic and political shocks or
changes, Terrorist attacks, Natural
disasters, Epidemics, Labor strike,
Legal disputes
Prof. Dr. Dr. habil. Dmitry Ivanov
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Supply Chain Resilience: Practical Tools
Prof. Dr. Dr. habil. Dmitry Ivanov
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Supply Chain Resilience and the Ripple Effect
Ripple effect describes the impact of a disruption on SC performance, disruption propagation, and disruption-based scope of changes in the SC structures and parameters.
Prof. Dr. Dr. habil. Dmitry Ivanov
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Supply Chain Resilience and the Ripple Effect
supply chain structure dynamics control and adaptation
operations execution and stability control
supply chain performance control
Jmin
xmin
xmax
xplan
xreal
Disruption
Impact
Recovery
Stabilization
Ivanov D., Dolgui, A., Sokolov, B. (2014) The Ripple-Effect in Supply Chains: Trade-off “efficiency-flexibility-resilience” in supply chain disruption management.
International Journal of Production Research, 52:7, 2154-2172.
Ripple effect describes the impact of a disruption on SC performance, disruption propagation, and disruption-based scope of changes in the SC structures and parameters.
Prof. Dr. Dr. habil. Dmitry Ivanov
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Simulation and Optimization to ImproveSupply Chain Resilience
• Resilient Supply Chain Design Optimization – how to protect the SC against disruptions at lower costs?
• Stress-testing of the existing and alternative SC designs
• Computing of alternative supply network topologies and back-up routes with performance assessment
• Simulation of SC dynamic behavior in the event of possible disruptions with performance assessment
• Real-time analysis of the disrupted SC performance and alternative SC designs that contain non-disrupted networks
Prof. Dr. Dr. habil. Dmitry Ivanov
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Simulation and Optimization toImprove Supply Chain Resilience
1 DC Back-up DC
Prof. Dr. Dr. habil. Dmitry Ivanov
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Data for Simulation and Optimization
Prof. Dr. Dr. habil. Dmitry Ivanov
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From offline modelling to online, data-driven Digital Twins
Supply Chain Digital Twin: computerized supply chain models in real-time
• The digital supply chain model
• At each point of time, it represents the physical supply chain with the actual transportation, inventory, demand, and capacity data.
• Can be used for planning and real-time control decisions
Product Digital Twin
Prof. Dr. Dr. habil. Dmitry Ivanov
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From offline modelling to online, data-driven Supply Chain Digital Twins: computerized supply chain models in real-time
Combination of simulation and optimization constitutes a full stack of technologies to create a supply chain digital twin – a model that always represents the state of the network in the present.
Prof. Dr. Dr. habil. Dmitry Ivanov
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Online, data-driven Supply Chain Digital Twins: supply chain models in real-time
Prof. Dr. Dr. habil. Dmitry Ivanov
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Improving Supply Chain Resilience with the help of Digital Twins
Prof. Dr. Dr. habil. Dmitry Ivanov
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Current Technologies and Future
Vision
Prof. Dr. Dr. habil. Dmitry Ivanov
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What did we learn?
Managing Supply Chain Risks and Resilience by Simulation, Optimization, and Digital Twins
• Resilient Supply Chain Design Optimization – how to protect the SC against disruptions at lower costs?
• Stress-testing of the existing and alternative SC designs
• Computing of alternative supply network topologies and back-up routes with performance assessment
• Simulation of SC dynamic behavior in the event of possible disruptions with performance assessment
• Real-time analysis of the disrupted SC performance and alternative, non-disrupted SC designs
Supply Chain Digital Twin
• The digital supply chain model based on simulation and optimization
• At each point of time, it represents the physical supply chain with the actual transportation, inventory, demand, and capacity data.
• Can be used for data-driven planning and real-time control decisions
Prof. Dr. Dr. habil. Dmitry Ivanov
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What is coming next?
• Is the Supply Chain as resilient as the digital technology behind it?
• If yes, who will compete in future: the physical supply chains or their digital twins?
• Will SC resilience be managed by Human or Artificial Intelligence, or any hybrids?
• What is the role of future Supply Chain Risk Managers?
Prof. Dr. Dr. habil. Dmitry Ivanov
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Thank you.
Prof. Dr. Dr. habil. Dmitry IvanovBerlin School ofEconomics and Law, Germany
Blog.hwr-berlin.de/ivanov
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Literature Recommendations