The main focus of this paper is the integration of an integrated function modeling (IFM) framework in an engineering framework based on graph-based design languages (GBDLs). Over the last decade, GBDLs have received increasing attention as they offer a promising approach for addressing several important challenges in engineering, such as the frequent and time-consuming transfer of data between different computer aided engineering (CAE) tools. This absorbs significant amounts of manual labor in engineering design projects. GBDLs create digital system models at a meta level, encompassing all relevant information concerning a certain product design and feeding this into the relevant simulation tools needed for evaluating the impact of possible design variations on the performance of the resulting products/parts. It is possible to automate this process using digital compilers. Because of this, it is also possible to realize systematic design variations for a very large number of parameters and topological variants. Therefore, these kinds of graph-based languages are a powerful means for creating a large number of viable design alternatives and for permitting fast evaluation processes against the given specifications. While, thus far, such analyses tend to be based on a more or less fully defined system, this paper proposes an expansion of the applicability of GBDLs into the domain of product functions to cohesively link conceptual with embodiment design stages. This will also help with early systematic, automated generation and the validation of design alternatives through relevant simulation tools during embodiment design. Further, it will permit the automated exploration of function paths and enable extended analysis possibilities, such as the detection of functional bottlenecks, while enhancing the traceability of the design over the development process. For these extended analysis possibilities, a function analysis tool was developed that adopts core ideas of the failure mode and effects analysis (FMEA). In this, the functional distinction between function carriers and function-related processes allows the goal-directed assessment of component reliabilities and the detectability and importance of processes in a technical system. In the paper, the graph-based modeling of functions and the function analysis tools are demonstrated on the example of a multicopter.
Graph-based design languages offer a promising approach to address several major issues in engineering, e. g. the laborious manual transfer between CAD and CAE. Such languages generate a digital meta- or system model storing all relevant information about a design and feed this into any relevant CAE tool as needed to simulate and test the impact of any design variation on the resulting product performance. As this can be automated in digital compilers to perform systematic design variation for an almost infinite amount of parameters, such graph-based languages are a powerful means to generate viable design alternatives and thus permit fast evaluations.To leverage the full potential of graph-based design languages, possibilities are presented to expand their applicability into the domain of product functions. This possibilities allow to cohesively link integrative function modelling to product structures. This intends to close the gap between the early, abstract stages and the systematic, concrete design generation and validation with relevant CAE tools. In this paper, the IFM Framework was selected as integrated function model to be linked with the graph- based design languages.
Kurzfassung Labs Network Industrie 4.0 e. V. (LNI) ist ein Partner der Plattform Industrie 4.0. Der vorwettbewerbliche und gemeinnützige Verein dient kleinen und mittelständischen Unternehmen (KMU) als Dialog-, Kompetenz- und Experimentierplattform. Über Testfelder können Unternehmen Industrie-4.0-Anwendungen risikolos probieren. In einem Anwendungsfall testen Forscher aus Australien und Deutschland nun gemeinsam den Einsatz von Faserverbundwerkstoffen in der Automobilindustrie. Das Projekt wird im Forschungscampus ARENA2036 umgesetzt.
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