The Digital Product Passport (DPP) is a vital enabler of the circular economy. However, creating interoperability among digital representations of products/assets and preserving privacy are core challenges for a successful implementation of the DPP. The Asset Administration Shell (AAS), by offering a consistent metamodel and application programming interface, helps interested parties to communicate via such a standard digital representation. In this paper, we present our Cloud-based system, which enables multiple stakeholders to build their own AAS. With the help of a user interface, different stakeholders can interact with existing AASs and add their own information based on existing templates. In earlier work on the AAS, the manufacturing phase of a product was in the focus. To both leverage the full potential of the AAS and to make the circular economy work, however, it is crucial to take later lifecycle phases and their related stakeholders equally into account. Our work therefore strongly emphasizes a multi-stakeholder perspective on the AAS and hence, the DPP. We demonstrate how the DPP is beneficial for recycling an asset in a real-world use-case. Our solution also addresses concerns about data privacy by implementing role-based access authorization constraints. We also offer the capability to deploy third-party services within our Cloud-based infrastructure.

This paper presents a novel approach to recognize a worker’s intentions for assistive systems in manual assembly. Building on previous research, it introduces a process description for assembling products, addressing the inflexibility and limitations of previous models. This enhancement enables the modeling of assemblies for a substantial amount of products. The proposed pipeline for intention recognition employs object detection, an assembly information model, and a Markov model. One major advantage of the new method is the ability to work with limited or no training data. The online learning capabilities of the model allow for adaptation to individual workers even with just one assembly. This flexibility makes this novel approach ideal for assistive systems. We also discuss about the model’s ability to suit any type of assembly product allowing offline training and guiding unskilled workers during their assembly processes.

Digital Twins and their adoption in Industry 4.0 are trending topics. Asset Administration Shell (AAS) has been introduced as a standard metamodel and application programming interface (API) to cope with interoperability issues. The specification discusses possibilities of serializing the AAS meta-model to various formats such as XML, JSON, and RDF. It also introduced various schemas to check the compliance of serialized content with the specification. In this paper, we show that Shapes Constraint Language (SHACL) is not only possible to be used for schema compliance checks but also for data entry validation. Within our use case, we show the flexibility of our solution, which is also platform independent.

To improve the fault tolerance of production systems against unforeseen events, modern production systems must be able to react more autonomously with suitable solutions to reach their goals. Such events within the company, e.g., resource breakdowns, require the possibility of internal replanning of the production schedule. Multi-Agent Systems (MAS) can provide this required flexibility. To enable standardized interaction for agents, a vendor-independent description of products and production equipment, as well as their capabilities and skills, must be developed. The Asset Administration Shell (AAS) provides the standardized meta-model to achieve this goal. In this paper, a product AAS and the submodel for the required production plan are designed. Moreover, the associated MAS and interaction for the execution and replanning of the production sequence are presented. The system is validated using an assembly use-case in the real-world demonstrator environment of the SmartFactoryKL. Combining the concepts of MAS with the standardized structures of the AAS, skills and capabilities tackles the problem of MAS to be deployed in different companies. This approach enables widespread use and scalability of MAS leveraging their advantages in terms of flexibility and efficient reconfiguration.