Industrial halls consume a large part of the heat energy resources but are only a tiny part of the building infra-structure. Improving heating efficiency in this sector will signif-icantly contribute to reach climate neutrality. Therefore, a digi-tal twin backend architecture is developed using the Asset Ad-ministration Shell framework to generate a digital twin. This has created a new data basis that lays the foundation for a score for the comparability of heating systems in terms of efficiency. In addition, some client services are implemented, such as visu-alizing the data in dashboards and generating alerts. Another service is a planning support application via augmented reality. The first tests in an industrial scenario show that using the dig-ital twin can reduce energy consumption and improve resource efficiency. Due to the containerized architecture of the gener-ated twin, it can be used as a blueprint for other digital twins of heating systems.

Industrial testbeds are spawning all across Europe, focusing on diverse topics. In our Human-Robot-Collaboration lab, we are researching how the lives of people in production can be made simpler through the use of collaborative robots, but still safe against the backdrop of the necessary changeability. Standardized digital twins based on Asset Administration Shells embedded in a service-oriented architecture are an ideal underlying information technology for this endeavor. In this paper, we describe such an infrastructure and outline its use based on two different use cases. We are convinced that this is not only relevant for testbed operators who want to achieve technical and semantic interoperability of their facilities, but can also serve as a blueprint for the implementation of Industrie 4.0 in small and medium-sized enterprises.

Functionally described capabilities play an important role in the virtualization of manufacturing and the resource-specific realization with the skill-based approach. The importance of this modeling can be seen in a formalization of production capabilities for a holistic usage in a workflow from product orders towards manufacturing on the shop floor. This paper presents a concept for modeling and usage of functionally described capabilities along this workflow with combined modeling approaches. Therefore, the formalism and the setup of product requirements, functionally described capabilities, Petri Net Plans for creation of resource-specific process sequences, and at least their execution with skills are considered. The application and validation of this concept on a virtualized demonstrator example is shown. The achieved results for a given application from a product order towards its simulated manufacturing are presented.

Modern manufacturing faces a challenge of integrating data models from various sources/domains which may differ both semantically and technically when particular domain specific data models are designed by different users and stored in different formats. This paper introduces an approach for facilitating the design of domain-specific data models using semantic web technologies. In this approach, all the information required for managing the production (including a description of a product, processes involved in the production, and existing resources and their specifications) is captured in an ontology. The proposed Product, Process, and Resource (PPR) ontology defines fundamental conceptualization of the production that can be easily applied to the arbitrary domain. Application of the PPR ontology is demonstrated in the case of simple truck assembling by means of robots. Capturing the knowledge in the form of ontology provides the advantage of employing supporting tools such as reasoners for consistency checking or query languages for information extraction. The paper demonstrates the utilization of SQWRL for searching resources suitable to manipulate given truck parts on the basis of semantic matching between properties of particular elements.