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.

Technical folding systems are rigid, three-dimensional surface structures that can be folded at their joints. Due to their foldable structure, technical folding systems can produce lightweight structures that have a high load-bearing capacity and can also flexibly change their shape. In order to develop products with technical folding in a function-oriented product development process, a folding principle must be defined that realises the individual functions. Since there is hardly any expert knowledge on technical folding, in general, and on the use of the technical folding principle in particular, technical folding is not very widespread despite its promising properties. Therefore, there is a need for a software-supported evaluation of whether functions can be realised by the principle of technical folding. The software-supported applicability evaluation (EvalTech) developed here is based on case-based reasoning methods, as these can artificially simulate evaluations based on expert knowledge. The expert knowledge used for the evaluation includes functions, function structures and properties of known technical folding systems, which are compared with functions and function structures of the development task. EvalTech was successfully used in the development and realisation of a large-scale foldable cover for industrial robots.