Name of participant: Merlin Korth
Project’s name: Causal Digital Twin zur automatisierten Grundursachenanalyse in Simulationsstudien der Supply Chain (CauSim)
Project description:
Knowledge is an advantage! As shown through the COVID-19 pandemic, the ongoing Russia-Ukraine war, and also the Ever-Given disaster at the Suez Canal in March 2021, currently we’re living in a VUCA world, a world that is embossed by volatility, uncertainty, complexity, and ambiguity. Delivery delays, production outages, and a cascade of follow-up issues can be the consequences that do reinforce one another. These challenges make it indispensable for companies to design their supply chains to be resilient, robust and adaptable. Nevertheless, conventional approaches and systems are often designed to be reactive, meaning that it is only possible to react in the event of an escalating malfunction. Therefore, a predicative and proactive support is missing for handling problems at the network level of supply chain management. With data-based monitoring and supply chain management based on a process mining approach, available operating data can be analyzed (almost) in real-time and structured solution spaces can be identified. This allows the early identification of anomalies, the performance of root cause analyses and the assessment of causes through the identification of causal correlations. The microproject CauSim aims to develop an approach that allows building such an algorithm and evaluating it in a real use case. Special attention is paid to the resilience of production networks—understood as the ability to react to unexpected events quickly, flexibly, and structurally. The methods developed in this project aim to measurably improve resilience characteristics such as sensitivity, speed, and span.
CauSim will be conducted in cooperation with the Karlsruhe Institute of Technology (KIT) and the industry partner Celonis SE. The developed prototype shall be evaluated in a real use case and contribute to the digital transformation of industrial added value. The expected project results—among them an intelligent supportive decision-making system for supply chain management—shall be made available in scientific publications and practical demonstrators.
Software Campus Partner: Karlsruher Institut für Technologie (KIT) and Celonis SE
Implementation period: 01.02.2025 – 31.01.2027
