Although the Asset Administration Shell (AAS) standard provides a structured and machine-readable representation of industrial assets, their semantic comparability remains a major challenge, particularly when different vocabularies and modeling practices are used. Engineering would benefit from retrieving existing AAS models that are similar to the target in order to reuse submodels, parameters, and metadata. In practice, however, heterogeneous vocabularies and divergent modeling conventions hinder automated, content-level comparison across AAS. This paper proposes a hybrid graph matching approach to enable semantics-aware comparison of Digital Twin representations. The method combines rule-based pre-filtering using SPARQL with embedding-based similarity calculation leveraging RDF2vec to capture both structural and semantic relationships between AAS models. This contribution provides a foundation for enhanced discovery, reuse, and automated configuration in Digital Twin networks.

The value added by virtual commissioning of in-dustrial production systems is evident through significant cost savings achieved via early error detection. Detecting errors early in the development process enhances project success. However, the development of simulation models is associated with manual effort, particularly during the early phases of the project when it comes to creating the first models. To reduce costs and increase automation in the redesign of simulation models, a novel concept is presented that automatically transforms unstructured customer requirements into initial model placeholders within a simulation environment. The approach employs a large language model to identify necessary processes and machines, estimating their dimensions and positioning them relative to each other. The output is then converted to a simulation model format and imported into a simulation environment for further refinement. To verify the solution, a synthetic expert, trained using a large language model, learns the probability correlations between plant types, machines, and processes, thereby enabling a more accurate assessment of the resulting simulation model.

In flexible production systems with distributed control systems which communicate with each other via a real time network, changes in the requirements for real time communication during operation must not lead to a temporary failure of the deterministic communication. Rather, the changes of the network configuration must become active at exactly predictable times in order to guarantee the functionality of the deterministic communication all the time. This paper shows a realization of how the configuration of a real time network schedule under Linux can be adjusted at predetermined times without interrupting the communication. For this purpose, the real time scheduler TAPRIO is integrated into the library libnl, and the performance of this extension is evaluated in a test case. It is shown that the modification of the network configuration is reliably possible in several successive communication cycles.

In the commissioning of industrial plants, it has been shown that the utilization of virtual commissioning reduces the overall commissioning time and at the same time increases the software quality of the plant control system. This is achieved by starting the development of the control software earlier in the plant development process, allowing more time for its development. Virtual commissioning is performed in advance of the commissioning of the physical plant using a simulation model of the plant. However, the transition from the simulated to the physical plant proves to be problematic if components or modules of the plant are not physically available. In these cases, the hybrid commissioning method, a hardware-in-the-loop simulation setup that includes both physical and simulated components, is desirable. This article first briefly discusses the disadvantages of virtual commissioning and the concept of hybrid commissioning of industrial plants. Then, aspects of an implementation of hybrid commissioning for PROFINET fieldbuses are discussed.

For the commissioning of production plants, the virtual commissioning (VCOM) method has proven to accelerate the overall commissioning time by increasing the software quality of the plant controller. VCOM is carried out in advance of the commissioning of the real plant, using a simulated plant. However, the hard transition from the simulated to the real plant proves to be problematic if components of the real plant are not available. In these cases the hybrid commissioning (HCOM) method, a hardware-in-the-loop (HIL) simulation setup including both real and simulated components, is desirable. In this article, the disadvantages of a hard transition of VCOM, the concept of the HCOM and it's benefits for commissioning production plants are explained and discussed. Also, an evaluation of an implementation is briefly presented.

As many of the common mistakes made by engineering students are based on weak spatial imagination, the use of virtual reality could help to enhance those skills in undergraduate teaching. As part of a university lecture in product development that covers methods of product development and technical design, the use of virtual reality was integrated into an engineering exercise. Supplementing the usual technical tools like CAD, half of the 14 student groups were allowed to use a dedicated VR-application to review their machine designs in virtual reality. While the objective performance of those groups was not better in comparison to the “non-VR” groups, most of the student groups were able to identify design issues or mistakes through the use of VR, which they couldn't find using only CAD. According to interviews, 69.7% of the VR-users reported that they were only able to experience and realize “the true spatial dimensions” through the use of VR.

Abstract Reinforcement learning is a promising approach for manufacturing processes. Process knowledge can be gained automatically, and autonomous tuning of control is possible. However, the use of reinforcement learning in a production environment imposes specific requirements that must be met for a successful application. This article defines those requirements and evaluates three reinforcement learning methods to explore their applicability. The results show that convolutional neural networks are computationally heavy and violate the real-time execution requirements. A new architecture is presented and validated that allows using GPU-based hardware acceleration while meeting the real-time execution requirements.

The digitalization of production is a strategic goal in the automation industry, though visions and industrial reality remain far apart. A key issue is that today's segmented communication architecture based on fieldbus networks does not fulfill the future requirements. Converged networks connecting IT and OT systems while maintaining deterministic guarantees for real-time communication are required instead. Time Sensitive Networking (TSN) in the context of IEEE 802.1 Ethernet is a key enabling technology for converged networks. The transition from current communication architectures towards converged networks will not be a disruptive change, but rather an evolutionary process involving many steps. In this paper, an analysis of different dimensions of this transition process and their evolutionary steps is presented. Potential migration paths from current to future production architectures and resulting intermediate brownfield scenarios are identified and analyzed with a focus on their communication architectures.

In this work we present a collaborative virtual reality application for distributed engineering tasks, including a simple avatar calibration method. Use cases for the application include CAD review, ergonomics analyses or virtual training. Full-body avatars with approximately natural motion characteristics are used to improve collaboration in terms of co-presence and embodiment. Through a calibration process, scaled avatars based on body measurements can be generated by users from within the VR application. For motion tracking, only the tracking capabilities of the VR devices used (head mounted display and hand controllers) are required, in order to achieve a low initialization effort for usage of the application. We demonstrate a simple, yet effective method for measuring the human body which requires these VR devices only. Tracking only the user's head and hands, we require inverse kinematics (IK) for avatar motion reconstruction. On the other hand, this requires a calibrated avatar, otherwise body postures and gestures will be misrepresented. In the first step of the demo, two users can create their calibrated avatar at the same time and then carry out a collaborative CAD review in the second step.

In current public perception, VR is often considered a fairly new thing, being around for only the last three to four years - while of course it's not at all new. Being researched for more than the last 25 years, VR has been a valuable tool in the industry almost as long. This talk will take the journey from some of the early VR pioneers to industrial VR applications of today and tomorrow, and look into the past and the future of enabling technologies for VR - including a close look to some of the really early VR hardware.