A modeling methodology for collaborative evaluation of future automotive innovations

Autor: Stefan Puch, Kim Grüttner, Maher Fakih, Oliver Klemp
Rok vydání: 2021
Předmět:
Zdroj: Software and Systems Modeling. 20:1587-1608
ISSN: 1619-1374
1619-1366
DOI: 10.1007/s10270-021-00864-3
Popis: The rapid introduction of innovations plays a major role in automotive industries. Today, once a member of the automotive value chain devises an innovation, the time-to-market could be years due to traditional forms of collaboration. It is thus indispensable for companies to collaborate on reducing the time to find and design innovations in order to remain competitive. One idea is to streamline the innovation process outside current product development cycles (7 + years) within the automotive value chain. In our work, we propose a modeling methodology offering a better collaboration in this innovation design phase. Beginning with the innovation idea, our approach allows capturing requirements, functional, and structural aspects of the innovation under design in an innovation model with defined semantics. This innovation model can then be exchanged between automotive partners, who in their turn can refine and exchange the refined model within an iterative process toward an initial innovation evaluation. Additionally, we propose a generic description of how such innovation models can be captured in SysML, a system modeling standard. Our approach is illustrated by a “wireless car charging” innovation case-study showing how a possible collaboration at different modeling abstraction levels could take place and how consistency of the models exchanged can be verified. The consistency check is exemplified by timing specifications.
Databáze: OpenAIRE
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