As mechatronic products gain in popularity, methods for mastering the complexity of these systems in development become increasingly relevant, such as model-based systems engineering (MBSE). Main pillars of MBSE are method, language and tool. A method specifies procedures in product development. The application of the method is supported by a language and tool as the language specifies a system of symbols with which development artifacts can be represented in a software environment (i.e. tool). Currently, various MBSE methods exist, such as motego. Motego specifies a framework for the function-oriented seamless development of mechatronic systems from requirements to the physical realization down to mechanical and electrical contacts and the description of these via parameters and models. Central element in MBSE is the system model, which connects all relevant development artefacts. The system model is created with a language in a software environment such as Cameo Systems Modeler. In MBSE, the graphical systems modeling language SysML is widely established. The language elements in SysML are very abstract and numerous. As a result, the language is difficult to apply. However, its reasonable applicability is an essential prerequisite for the introduction of the motego methods in industrial practice. This results in the following research need: A specific modeling language for the motego method is needed that supports its reasonable application. Therefore, in this paper a modeling language is presented whose language elements are specifically adapted to the motego method. With the help of this domain specific language, the user is guided through method-compliant modeling.

To handle increasing complexity in product development, model-based systems engineering (MBSE) approaches are well suited, in which the technical system is represented in a system model. To efficiently test requirements, domain models are integrated into the system model. For each purpose (e.g., battery lifetime calculation), there are typically several models at several fidelity levels. Since the model signatures (i.e., necessary inputs for the models and their outputs) differ depending on the fidelity level, not all models can be used in any development phase. In addition, due to the different model signatures, not all models can be combined arbitrarily to model networks. Currently, valid model networks in system models must be determined in a time-consuming, manual process. Therefore, this paper presents an approach that automates this task via the implementation of an algorithm that analyzes a system model and the model signatures and automatically returns all valid model networks. When input parameters, models or their signatures change, the algorithm updates automatically, and the user receives the valid model network without any manual effort. The approach is demonstrated with the running example of battery system development.

One major challenge of today’s product development is to master the constantly increasing product complexity driven by the interactions between different disciplines, like mechanical, electrical and software engineering. An approach to master this complexity is function-oriented model-based systems engineering (MBSE). In order to guide the developer through the process of transferring requirements into a final product design, MBSE methods are essential. However, especially in mechanics, function-oriented product development is challenging, as functionality is largely determined by the physical effects that occur in the contacts of physical components. Currently, function-oriented MBSE methods enable either the modeling of contacts or of structures as part of physical components. To create seamless function-oriented mechanical system architectures, a holistic method for modeling contacts, structures and their dependencies is needed. Therefore, this paper presents an extension of the motego method to model structures, by which the seamless parametric modeling of function-oriented mechanical system architectures from requirements to the physical product is enabled.

One approach to tackle the complexity in the development of cyber-physical systems is system decomposition and modelling in a central system model with model-based system engineering (MBSE). However, MBSE also requires increased development effort due to the high degree of formalisation of the development results using the Systems Modelling Language (SysML). One solution is reusing system elements from model libraries, which requires formalization that allows them to be networked into consistent models. Due to the abstract nature of SysML, the options for formalizing system elements are extremely diverse, meaning that even identical technical system elements are modelled with a different structure by engineers. As a consequence, no standardized structure is maintained and the reuse of system elements from model libraries is very unlikely. This leads to high, redundant modelling efforts as well as a considerable error potential and significantly hinders the economic application of MBSE in mechanical engineering. A standardized structure of the system elements can be ensured through MBSE methodology specific modelling guidelines. Current modelling guidelines for MBSE are based on the SysMLv1 language standard and cannot be used unchanged in SysML v2. Nevertheless, SysML v2 offers great potential for modelling reusable system elements, especially with its synonymous textual and graphical modelling capabilities, enabling the easy linkage of knowledge from various domain-specific tools. Consequently, modelling guidelines based on SysML v2, which guarantee a standardized structure, are required to fully exploit the potential of model libraries in MBSE. To solve this deficit, this paper presents modelling guidelines based on SysML v2 and their application for building reusable system elements.

As product development cycles become increasingly short while products grow more complex, new approaches in product development are needed to accommodate these developments. One of these approaches is Model-based Systems Engineering (MBSE). MBSE enables the representation of products, which are seen as systems, in one seamless system model. To do so the product and its different aspects, such as physical behavior, are described by different models, that are then interconnected with each other. One advantage of applying MBSE is, that the usage of physical behavior models allows efficient virtual validation of many different product features and evaluation of implication due to design changes. However, performing sufficiently accurate virtual tests, especially for mechanical properties, requires detailed behavior models, which leads to a high modeling effort. For this reason, in the past efforts were made to standardize model components, referred to as system elements, that could be reused and thus reducing the modeling effort. The aim is to enable the modeling of any technical product from the composition of these base components. However, these system elements have not yet been modeled and organized in a library, which could then be distributed across modelers. For this reason, the aim of this paper is to firstly create a model library based on previously defined system elements that satisfies the required physical model properties. Furthermore, the applicability of this library in modeling is investigated and improvement potentials are derived. To do so a simplified gearbox model is created from multiple elements contained in a predefined library. The model created is then used to specifically investigate the ability to verify static safety using the physical behavior models contained in the library. The result of this work is an expandable model library of reusable system elements, that allows the aggregation of system models, representing products and the virtual verification of these products. Thus, enabling for a faster product development process as the modeling effort for the application of MBSE is reduced.

Future cyber-physical systems (CPSs), integrating subsystems of the mechanical, electrical and software domains, are becoming increasingly interconnected and complex. As complexity grows, testing effort increases as well. This includes the test-case definition step, where the test targets and boundary conditions are specified. With rising system complexity, the effort required to ensure that all relevant conditions for each test target are identified increases. Manual test-case definition remains the norm, creating effort bottlenecks in ensuring systematic coverage and compliance with standards such as ISO 26262 and ISO 29119. This paper explores how large language models (LLMs) can support the identification of complex boundary conditions for CPS test cases through detailed requirement analysis. The impact of performing taxonomy-guided, structured requirement mapping prior to test-case generation was evaluated by comparing it with a version without this guidance. Furthermore, the influence of supplying a Model-Based Systems Engineering (MBSE) system model as context information via Graph RAG is examined. The results show that structured, stepwise reasoning significantly improves reliability and consistency over unguided generation, while system-model information provides valuable contextual insight but has a minor impact in the chosen example. These findings outline a scalable framework for AI-assisted test-case generation.