Inhaltstyp: Article

For a successful implementation as well as sustainable use and maintenance of digital twins for production and logistics systems, it is necessary to identify relevant use cases and master the associated challenges. This paper analyzes scientific literature on common applications and challenges in the implementation of digital twins for the planning and operation of production and logistics systems. To confirm the practical relevance of the results, the results of an empirical survey have also been included. The findings are used to derive key focus areas for the successful implementation and long-term use of digital twins in production and logistics.

In today’s manufacturing industry, digital twins are a key enabler for optimizing production processes and efficient resource use. However, creating digital twins is often associated with high or difficult-to-estimate costs and typically requires unknown characteristic values, such as material parameters, making practical implementation challenging. With RAPIDZ, we present a tool for creating and using digital twins that overcomes these barriers through its modular structure. The virtual modeling of physical systems enables comprehensive analysis and real-time forecasting of material flows, energy consumption and machine performance. The use of RAPIDZ increases production line efficiency, enhances flexibility and response time, and enables proactive maintenance to minimize downtime.

Collecting data from different sources on the shop floor and making it accessible to different IT systems is one of the core tasks during the process of factory digitization. Due to the different protocols and interfaces, the data collection task comes with unique challenges. With the Sensor Technology Adapter Gateway (STAG), we present a solution that closes the gap between the shop floor and the IT system’s backend. STAG is an industry-grade middleware that automates translations between data models and protocols.

Strategic Product Planning must adapt to current challenges such as circular economy, digital business models and interdisciplinarity. Established process models, for example, can only be applied to Product-Service Systems to a limited extent. This article presents a new SPP model developed through an analysis of 230 existing approaches and enhanced by the integration of digital twins, enabling continuous feedback throughout the entire product life cycle. This allows product monitoring and dynamic adjustments to the SPP. The model adopts an agile, iterative framework consisting of five cyclical key activities, guided by five control points aligned with increasing levels of maturity. By factoring in circularity from the outset, the model promotes resource-efficient products and production processes. Its emphasis on flexibility, information circularity and sustainability ensures future value and adaptability across industries of the proposed SPP model.

Digital Twin (DT) adoption remains a challenge due to high costs, complexity and lack of skills. This study proposes a cost-effective, TRL 5-validated DT model that can be built using open-source and office suite tools within just two weeks. Integrating real-time sensor data, predictive analytics, anomaly detection and notification, the model improves efficiency and sustainability in agriculture. Even with cloud service constraints, the system delivers a 7.76% average relative error and rapid, automated notifications. The findings show how open-source in combination with common commercial tools technologies can make advanced digital tools accessible to all, creating scalable, human-centered, and affordable solutions in line with Industry 5.0 principles.