DINGOL - Digital and Intelligent Twin for the Sustainable Design and Optimization of Supply Chains

The DINGOL research project develops a generic framework for Digital Supply Chain Twins. A Digital Supply Chain Twin dynamically represents a real supply chain and, where possible, is continuously updated with current operational data. Through a bidirectional connection to enterprise information systems, the twin can process real-time data, simulate alternative scenarios, and transfer optimized recommendations back to the operational supply chain.

The project aims to support companies in designing more sustainable, resilient, and efficient supply chains. The framework will represent production, warehousing, transportation, and distribution processes and enable the analysis of relevant economic, environmental, and social performance indicators. To achieve this, the project develops modules for data exchange, discrete-event simulation, optimization, machine learning, and visualization.
A particular focus is placed on supply-chain resilience and sustainability. Companies should be able to analyse supplier failures, demand fluctuations, transportation disruptions, and other risks; compare possible mitigation strategies; and optimize their processes with regard to resource consumption, transportation routes, inventory levels, and emissions. The resulting solutions are intended to support early risk identification, improve operational decision-making, and monitor sustainability objectives across the entire value chain.

The project follows a Design Science Research approach. First, practical use cases and requirements for Digital Supply Chain Twins are identified through interviews and workshops with companies. Based on these findings, reference processes and a system architecture are designed. A prototype framework is then developed, comprising a model library, interfaces to enterprise resource planning systems, simulation and optimization services, and a web-based cockpit for creating and visualizing Digital Supply Chain Twins.

The framework will be instantiated and tested in a manufacturing company using selected practical use cases. The evaluation will examine both the technical and practical applicability of the framework and its benefits for companies. The results will be disseminated through scientific publications, and the framework is intended to be made available as an open-source solution for research and industrial applications.