Volume 69, Issue 12 - Special Issue: Digital Twins / Eva Brucherseifer, Alexander Fay

To cope with individualization and the high costs of downtimes, modern production systems should be flexible, adaptable, and resilient. Multi-Agent Systems are suitable to address these requirements by decentralizing production systems. However, the agent paradigm is still not widely applied. One of the key reasons is that the agents’ knowledge bases had to be created manually, which is cumbersome, error-prone, and insufficiently standardized. Digital Twins have the potential to solve this issue, as they describe relevant information in a standardized way. This paper presents an approach to leveraging Digital Twins, i. e., the Asset Administration Shell, to realize Multi-Agent Systems in the production context. For this, a parser automatically extracts relevant information from the Digital Twins and initializes the individual agents in a Multi-Agent System, i. e., PADE.

With modular automation, modular industrial plants use a functional engineering approach, and modules enable plug & produce plant engineering. However, plant configuration is still a largely manual process and often not optimized with respect to the available information. In this contribution, we propose a system and algorithm to support the automation engineer in the process of joining together modules into process pipelines and in their optimization. Our solution is built upon an abstract semantic data model that facilitates the automated matching of pre- and post-condition of modules and of the things that are processed by these modules. The pipeline generation engine is further extended by means of an optimization and ranking algorithm, and thus enables automated inter-module pipeline generation and plant optimization. We evaluate our system by means of a simple fictional use case scenario and prove feasibility, applicability as well as the huge potential for time and cost savings.

Data sharing between enterprises requires both interoperability and data sovereignty. In the application domain of industrial production an integrated approach is required that encompasses standards and technologies of both Industrie 4.0 and the International Data Spaces (IDS). This paper describes how to combine them for the concept of Digital Twins following the architectural framework given in ISO DIS 23247. Furthermore, an implementation approach is described relying upon the Fraunhofer Advanced AAS Tools for Digital Twins (FA³ST). The resulting architectural approach may be combined with further open manufacturing standards, and may be applied for data analytics and the engineering of AI-based systems.

Critical infrastructures are the backbone of our societies with increasingly complex and networked characteristics and high availability demands. This makes them vulnerable to a wide range of threats that can lead to major incidents. Resilience is a concept that describes a system’s ability to absorb and respond to disturbances, as well as to learn from the past and anticipate new threats. In this article, we apply the Digital Twin concept to the infrastructure domain to improve the system’s resilience capabilities. We conduct a comprehensive requirements analysis related to infrastructure characteristics, crisis management and resilience measures. As a result, we propose a Digital Twin Conceptual Framework for critical infrastructures. We conclude that the Digital Twin paradigm is well suited to enhance critical infrastructure resilience.

Digital Twins (DTs) play an important role in current digitalization trends across industries. As maritime markets are particularly affected by recent global tendencies such as increasing delivery costs or political pressure for decarbonization, DT solutions could provide important support for shipbuilding and shipping companies to master recent and upcoming challenges. This paper provides a brief insight into the current state of the maritime industry and shows possible use-cases for DT Ship applications throughout the entire product lifecycle. To further advance the general understanding of DTs and their implementation, the concept of a Maritime Digital Twin Architecture (MDTA) is proposed to structure practical DT features.

Zusammenfassung Flughäfen entwickeln sich zu industriell-gesellschaftlichen Mobilitätsknoten. Als kritische Infrastrukturen stehen sie ebenfalls vor der Herausforderung effizient und klimaneutral zu agieren. Die Realisierung dieser Anforderungen ist nicht ausschließlich technologisch lösbar. Sie bedarf einer neuen Form des Managements, das alle genannten Aspekte berücksichtigt. Dieses Management erfordert Echtzeit- und Prognosedaten die den Zustand des Systems Flughafen wiederspiegeln. Eine Variante, die zum Management benötigten erheblich steigenden Datenmengen zu organisieren, liegt im Einsatz eines digitalen Zwillings als digitale Repräsentanz des realen Flughafens. Dessen Einbettung in eine Managementumgebung, deren Grundvoraussetzung eine What-If Fähigkeit ist, ermöglicht eine verbesserte und umfassendere Situationsbewertung und bildet die Basis für künftige Entscheidungsfindungsprozesse im Flughafen.

This article describes the use of digital twins for smart cities, i. e., the Urban Digital Twin (UDTw) concept. It shows how UDTws can be realized using the open source components from the FIWARE ecosystem that are already used in more than 200 cities worldwide. The used NGSI-LD standard is supported by the European Connecting Europe Facility, the Open and Agile Smart City community, the Indian Urban Data Exchange platform, and the Japanese Smart City Reference Model. Unlike digital twins in other domains, e. g., manufacturing, where digital twins are co-developed with their physical counterparts, UDTws often evolve driven by different stakeholders, on different time scales, as well as by utilizing many different data sources from the city. This article builds on a well-established lifecycle model for Digital Twins and combines this with a conceptual model for digital twins consisting of data, reactive, predictive and forecasting (“what if”) digital twin functionalities. The article also describes how AI-based technologies can be used to extract knowledge to build the UDTws from the IoT-based infrastructure of a smart city.