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The fifth generation of mobile communication (5G) is expected to bring immense benefits to automated guided vehicles by improving existing respectively enabling 5G-distinctive network control systems, leading to higher productivity and safety. However, only 1% of production companies have fully deployed 5G yet. Most companies currently lack an understanding of return on investment and of technical use-case benefits. Therefore, this paper analyses the influence of 5G on an automated guided vehicle use case based on a five-step evaluation model. The analysis is conducted with a use case in the Digital Experience Factory in Aachen. It shows a difference of net present value between 4G and 5G of 1.3 M€ after 10 years and a difference of return of investment of 66%. Furthermore, analysis shows an increase of mobility (13%), productivity (20%) and safety (136%). This indicates a noticeable improvement of a 5G-controlled automated guided vehicle compared to a 4G-controlled automated guided vehicle.
Komplexe Anforderungen an das operative Supply-Chain-Management führen zu komplexen Entscheidungssituationen innerhalb des betrieblichen Alltags. Ein konzeptioniertes, modulares Simulationsmodell für das operative Supply-Chain-Management kann die Entscheidungsfindung auf Grundlage von Analysen und Daten unterstützen. Die Modularisierung ermöglicht eine flexible, effiziente und unternehmensspezifische Anwendung des Simulationsmodells. Die Modularität ist durch die individuelle Kombination geeigneter Module und Funktionen sowie der Abbildung dazugehöriger Informationsflüsse realisiert. Informationsflüsse werden dabei durch definierte Informationsobjekte, wie z. B. einen Fertigungsauftrag oder eine Maschine, spezifiziert. Die Module und Funktionen bilden die unterschiedlichen Prozessschritte ab.
Die notwendige Transformation der Linear- zur Kreislaufwirtschaft ermöglicht die Entkopplung des Wirtschaftswachstums und Ressourcenverbrauchs. Das ökonomische und ökologische Potenzial der Kreislaufwirtschaft wird durch die zeitgleiche Umsetzung mehrere, simultaner Kreislaufstrategien gesteigert. Diese Umsetzungsform bedingt allerdings vielfältige und komplexe Entscheidungen für die operative Abwicklung. Das entwickelte kaskadierte Entscheidungsmodell differenziert diese Entscheidungen innerhalb verschiedener Ebenen des Wertschöpfungssystems.
Climate change, one of the most significant threats to humanity, underscores the urgent need to advance the circular economy, particularly in promoting sustainability. Implementing R-strategies such as refurbishment and remanufacturing within the home appliances industry is central to establishing sustainable and environmentally friendly business models. Key processes, such as workpiece disassembly, reassembly, and component status evaluation, are inherently more complex and variable than conventional production workflows. This requires workers with extensive experience handling comparable products and a deep understanding of critical decision-making processes. Due to the skilled worker shortage and the impact of demographic shifts, developing precise and comprehensive work instructions is increasingly vital for maintaining process quality. A worker assistance system is essential to meet this need, providing robust decision support to ensure accurate and sufficient decision-making. This paper proposes a framework for a worker assistance system tailored to the application of R-strategies in washing machine production. Data from an industrial scenario validates the framework and identifies critical information that should be incorporated into the system, enhancing the applicability and feasibility of the framework in real-world contexts. Within the framework, potential data sources and information flows are proposed, and illustrative processes are employed to demonstrate the derivation of work instructions utilizing the framework.
