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EIPPM - The Executable Integrative Product-Production Model

 
: Schopper, Dominik; Kübler, Karl; Rudolph, Stephan; Riedel, Oliver

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Volltext urn:nbn:de:0011-n-6402254 (16 MByte PDF)
MD5 Fingerprint: 5242d50ce43ed9bf7a907d092af471c8
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Erstellt am: 8.9.2021


Computers 10 (2021), Nr.6, Art. 72, 27 S.
ISSN: 2073-431X
Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg MWK BW
43031423; DiP
Digitaler Produktlebenszyklus
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer IAO ()

Abstract
In this paper, a combination of graph-based design and simulation-based engineering (SBE) into a new concept called Executable Integrative Product-Production Model (EIPPM) is elaborated. Today, the first collaborative process in engineering for all mechatronic disciplines is the virtual commissioning phase. The authors see a hitherto untapped potential for the earlier, integrated and iterative use of SBE for the development of production systems (PS). Seamless generation of and exchange between Model-, Software- and Hardware-in-the-Loop simulations is necessary. Feedback from simulation results will go into the design decisions after each iteration. The presented approach combines knowledge of the domain "PSs" together with the knowledge of the corresponding "product" using a so called Graph-based Design Language (GBDL). Its central data model, which represents the entire life cycle of product and PS, results of an automatic translation step in a compiler. Since the execution of the GBDL can be repeated as often as desired with modified boundary conditions (e.g., through feedback), a design of experiment is made possible, whereby unconventional solutions are also considered. The novel concept aims at the following advantages: Consistent linking of all mechatronic disciplines through a data model (graph) from the project start, automatic design cycles exploring multiple variants for optimized product-PS combinations, automatic generation of simulation models starting with the planning phase and feedback from simulation-based optimization back into the data model.

: http://publica.fraunhofer.de/dokumente/N-640225.html