In Model-Based Systems Engineering (MBSE) there is yet no converged terminology. The term ‘system model’ is used in different contexts in literature. In this study we elaborated the definitions and usages of the term ‘system model’, to find a common definition. We analyzed 104 publications in depth for their usage and definition as well as their meta-data e.g., the publication year and publication background to find some common patterns. While the term is gaining more interest in recent years, it is used in a broad range of contexts for both analytical and synthetic use cases. Based on this, three categories of system models have been defined and integrated into a more precise definition.

Appropriateness of models through modelling languages, tools, and methods is at the core of systems modelling. A concrete example is that useful abstraction depends on the contextual case of modelling purpose and need. Naturally, this results in different modelling formalisms and languages being appropriate at different stages of a common development process and for different stakeholders. In Model-Based Systems Engineering (MBSE) many stakeholders are involved in procedural modelling activities. Consequently, there is a need to identify appropriate modelling approaches at each modelling activity and development stage. Current MBSE adoption and application is still in early stages, and consequently lacking in overall modelling contextualisation. In this paper we discuss what facilitates an appropriate systems engineering model and how practitioners can reason about models in industrial contexts by providing an initial conceptual model of how model artefacts support governing systems engineering concerns.

Technische Systeme werden mithilfe von Modellbasiertem Systems Engineering (MBSE) beschrieben, um eine domänenübergreifende Wissensbasis zu erzeugen, die es den beteiligten Stakeholdern ermöglicht, Systemelemente konsistent und parallel zu entwickeln. Die Qualität dieser Modelle ist maßgeblich dafür, wie effizient dieses Wissen aus dem MBSE auch zur Systemexploration verwendet werden kann, um Systemzusammenhänge zu analysieren, indem verschiedene Modellarten gemeinsam simuliert werden.

Electric flight accelerates innovation and demands digitalization. DIREKT develops digital twins across the lifecycle of (hybrid) electric propulsion systems to fuse data, cut costs, and shorten time-to-market. In this context we present a production-to-design feedback approach. A system is developed which compares the scanned manufactured part with the design to visualize manufacturing deviations to improve upcoming designs. The system is tested with three different additive manufacturing technologies and two parts from an urban air mobility electric propulsion system. Furthermore, the comparison data is stored in a knowledge base for machine-learning-driven deviation prediction later on.