Supply chain simulation for resilient and cost-efficient networks

Supply chain simulation provides reliable insights into complex global supply chains. Many value creation networks are sensitive to disruptions caused, for example, by pandemics, geopolitical conflicts or blocked transportation corridors. Logistics managers need tools that make risks transparent, strengthen supply chain resilience and support data-driven decisions to reduce costs.

The Fraunhofer Institute for Material Flow and Logistics IML researches and develops methods for integrated supply chain and material flow simulation. Fraunhofer IML also develops digital assistance systems that help companies design and operate robust and cost-effective supply chains.

Globally interconnected supply chains shape the industrial landscape. Many supply chains are highly complex and sensitive to changes in demand as well as disruptions in transportation networks. Events such as COVID-19, geopolitical conflicts and blocked transportation routes highlight the importance of effective supply chain risk management and resilient network design. Companies must respond to supply fluctuations, dynamic markets and increasing transparency requirements.

Resilient supply chains can maintain efficiency and cost-effectiveness under changing conditions. Redundancy, flexibility and responsiveness are important strategic success factors. An effective approach requires proactive, holistic management of the entire value chain.

Fraunhofer IML analyzes these challenges through methodologically sound supply chain analyses. For supply chain simulation, researchers model value creation networks using real-world data and evaluate potential courses of action on a scientific basis. In logistics assistance systems, these models are integrated with enterprise resource planning (ERP) systems, ensuring continous assessment of the current supply chain state using a digital-twin approach.

Supply chain simulation supports robust decision-making within the network. Fraunhofer IML uses the discrete-event simulation suite OTD NETWORK for this purpose. OTD NETWORK supports modular modeling, analysis and evaluation of value creation networks. It maps planning, material flow and scheduling processes and assesses costs, resilience, sustainability and service levels using key performance indicators (KPIs). OTD NETWORK creates end-to-end transparency from customer order to delivery and can integrate procurement, production and distribution processes.

• Supply Chain Simulation: Holistic, event-driven analysis of supply chains, their planning processes and the resulting material flows. The analysis covers alternatives, bottlenecks, inventory levels, costs, network design, production program planning, transportation scheduling and customer behavior.
• Scenario and Risk Simulation: Simulation of disruptions, pandemics, transportation failures and supplier failures, including the evaluation of resilience measures and restart management.
• Simulation-Based Optimization: Integration of simulation and optimization to iteratively improve network structures, parameters and processes with regard to costs, service levels, sustainability and resilience.
• Supply Chain Design and Planning: Tool-supported, simulation-based design of value creation networks, including network design, site and partner selection, allocation, capacity sizing, make-or-buy decisions and sustainability criteria.
• Assistance Systems and Control Tower: Development and operation of logistics assistance systems such as OTD Control Tower for real-time monitoring, forecasting, tracking material and parts availability and recommending courses of action.
• Digitalization and AI Integration: Development of digital twins that integrate real-time data, artificial intelligence (AI), big data, the Internet of Things (IoT), smart objects, smart finance and automated decision-making.
• Visualization and Reporting: Visualization of KPIs through dashboards and web-based reporting services, together with straightforward analysis of scenarios and simulation results.

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Supply chain simulation maps complex value creation networks as digital models. Event-driven methods enable the modeling of material flows, order processing and planning logic. Tools such as OTD NETWORK use modular, object-oriented building blocks and support applications in various industries.

The OTD NETWORK simulation suite has been used across sectors ranging from the automotive industry and manufacturing to healthcare and emergency medicine. The tool suite supports scenario analysis, risk assessment, cost evaluation, network design and the analysis of bottlenecks and inventory. Companies can simulate production schedules, variable transportation plans and customer behavior across multiple stages of the value chain. Combining simulation with optimization or artificial intelligence can support decision-making and the assessment of costs, sustainability metrics and supply chain resilience. Digital twins link models with data streams from the Internet of Things (IoT), enterprise resource planning (ERP) systems and warehouse management systems. This connection helps planners identify deviations at an early stage.

Fraunhofer IML integrates OTD NETWORK into logistics assistance systems for specific supply chain management tasks, including inventory management, scheduling, demand and capacity management and risk management.

“When a simulated supplier disruption occurs, supply chain simulation can quickly show which plants and customer orders may be affected, which routes may experience congestion or disruption and how inventory could be strategically reallocated. The simulation translates complex data into clear scenarios. It represents supply chain behavior in a computer model and thereby supports the assessment of measures designed to strengthen resilience.”
Marco Motta, Dipl.-Ing., heads the Supply Chain Engineering Department at Fraunhofer IML

Complex supply chains in the automotive industry are a typical use case. Manufacturers such as Volkswagen (VW), Bayerische Motoren Werke (BMW) and Audi use supply chain simulation to analyze multistage networks. Scenarios involving a pandemic, supplier failure, transportation disruption or change in demand can be examined in advance. The same applies to scenarios involving the allocation of products to different production sites.

Supply chain simulation examines the entire supply chain, identifies potential improvements, highlights bottlenecks and identifies inventories with optimization potential. The method can support measures intended to strengthen resilience and control costs.

Assistance systems such as Fraunhofer IML’s OTD Control Tower support managers and planners through real-time monitoring, forecasting and decision support. In crisis management, stakeholders from public authorities and organizations with security responsibilities, such as the fire department, can rely on simulation tools such as OTD NETWORK to develop robust supply structures and prepare the materials required for emergency operations. Simulation and digital assistance systems are some of the most important tools planning and managing complex networks.

Risk management and ramp-up: Transparency and supply chain simulation

The rapid restart of global supply chains following the COVID-19 pandemic requires precise risk management. Supply chain simulation provides transparency into asynchronous states, bottlenecks and inventory levels within a supply chain and enables companies to test ramp-up scenarios in advance. Companies can identify risks, define strategies and assess measures intended to increase network resilience.

Fast Ramp Up

Integrated demand and capacity management at the BMW Group

In collaboration with the Bayerische Motoren Werke (BMW) Group, Fraunhofer IML developed an IT-supported system for demand and capacity management. The system links production programs to bills of materials, automatically identifies capacity bottlenecks and provides transparency into potential supply chain impacts. Analytical functions, including a dashboard, scenario comparison and integrated traceability, facilitate the evaluation of production programs, support cross-functional coordination and accelerate adjustments when deviations occur. The system has been in use since late 2019 and is being expanded with additional features.

Download the project report here

Logistics assistance systems for production supply

ECO2LAS and Vistas: Availability planning in long supply chains

The web-based assistance system ECO2LAS, developed at Fraunhofer IML, supports Volkswagen Commercial Vehicles in environmentally conscious planning within the global logistics network for parts supplied to the VW Amarok. The solution provides resource transparency across long supply chains, combines operational procurement logistics with scenario-based evaluation and uses simulation-based forecasting to manage inventory and support supply security on an intercontinental scale. Under the project name Vistas, the approach was rolled out across various Group brands and used to plan long supply chains.

Download the report on ECO2LAS

EvaVe: AI-based evaluation of supply security

EvaVe is an AI-based service for evaluating supply security. Fraunhofer IML developed the service as part of the ResKriVer research project. The application analyzes data from supply relationships, inventory levels and disruption reports, simulates supply bottlenecks and identifies alternatives in critical supply chains. It provides government agencies, emergency services and companies in critical infrastructure sectors with a tool for assessing demand, capacity and indirect dependencies as well as for preparing measures to strengthen crisis resilience. 

About the EvaVe Project

Organizations interested in applying supply chain simulation can contact Fraunhofer IML for further information. In an initial discussion, Fraunhofer IML clarifies the organization’s objectives, available data and suitable models and outlines potential steps for a joint project.

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Simulation is also suitable for professional development. In workshops, participants take part in a supply chain game and make decisions within a virtual supply network. Key metrics show how decisions about inventory levels, batch sizes and transportation strategies affect service levels and resilience. These formats support supply chain management training, foster a shared understanding of complex interrelationships and strengthen acceptance of data-driven decision-making among managers.

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