## 1 Introduction
However, this transition is currently realized by means of a manually executed data transfer into independent calculation tools or into other Computer-Aided Engineering (CAE) tools such as 3D modeling environments, Finite Element Analysis (FEA) systems for analyzing structural safety and for deflection studies, Multi-Body Systems (MBS) for kinematic and kinetic studies, as well as systems for the analysis of thermodynamics, electromagnetic performances or the likes. Additionally, the situation is aggravated by the fact that the results from the mentioned CAE tools are currently not efficiently and effectively linked with each other to permit seamless cross-validation, because usually several data formatting and exchange problems are present [21]. As stated above, current engineering processes are characterized by a large amount of manual data transfer and an incomplete and often inconsistent linkage between different kinds of engineering information. One promising approach to address these challenges and issues are GBDLs. Like other design languages, this language creates a digital meta-model of the system, which allows the storage of all relevant information concerning a design solution. This system model can be fed into different CAE tools that are applied in order to simulate and evaluate the consequences of certain variations of the design on the resulting performance of the product. This process can be performed in an automated manner by means of digital compilers and allows the analysis of systematic product design variations for a large number of parameters and parameter settings. Consequently, GBDLs can be characterized as a powerful means of synthesizing feasible design alternatives and for rapid comparison and selections processes. These processes can be performed much quicker than the manual design process of an engineering team. Parameter variation and the computing of those variations primarily applies to the later stages of the product development process, when quantitative product information is available. In order to realize the full potential of GBDLs, it is desirable to expand their applicability into the domain of product functions. In order to achieve this, it is intended to realize cohesive links (or associations) in the form of integrative function modeling, starting with the requirements and functional level and ranging to product structures with GBDL models. This should assist in closing the gap between the early phases of product development, within which the product information is still rather abstract, and the systematic design synthesis and validation phase with powerful CAE tools, within which the product information has to be concrete. Consequently, the focus of this paper is on the implementation of system modeling that spans both the functional level and expands into a detailed design of the product geometry and structure (Figure 1). Currently, several research groups worldwide are investigating several aspects of model-based systems engineering (MBSE). The research outcomes have allowed the republishing of the well-known guideline VDI/VDE 2206 as a draft under the redesigned title \"Development of cyber-physical mechatronic systems (CPMS)\" [22]. This guideline supports engineers in the development of cyber-physical mechatronic systems by means of presenting and explaining the main logical relationships. The central content of the new VDI 2206 is represented as an updated and extended V-model and depicts an inherent flow describing the logic of the development of cyber-physical mechatronic systems [23]. In this flow logic, a successive transition of product information from requirements over a functional architecture and logic architecture to the physical architecture is visible; this general successive architecture development is also visible in earlier design ontologies, such as the function-behavior-structure ontologies [7].