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MBSE INCORPORATING TIME-DEPENDENT BEHAVIOR FOR THE DESIGN OF ROBOT-LIKE SYSTEMS

Published online by Cambridge University Press:  19 June 2023

Klara Ziegler ,
Marcus Volpert ,
Maximilian Amm ,
Birgit Vogel-Heuser ,
Karsten Stahl  and
Markus Zimmermann
Klara Ziegler*
Affiliation:
Technical University of Munich
Marcus Volpert
Affiliation:
Technical University of Munich
Maximilian Amm
Affiliation:
Technical University of Munich
Birgit Vogel-Heuser
Affiliation:
Technical University of Munich
Karsten Stahl
Affiliation:
Technical University of Munich
Markus Zimmermann
Affiliation:
Technical University of Munich
*
Ziegler, Klara, Technical University of Munich, TUM School of Engineering and Design, Germany, klara.ziegler@tum.de

Abstract

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Complex systems typically consist of many components and are subject to many requirements. Approaches like the V-Model support complex systems design by providing guidelines on how to break down large systems into smaller pieces. Models built with SysML provide documentation on an abstract level. However, neither incoporates detailed information on components that may be relevant for design decisions. In robot-like systems, e.g., the choice of transmissions will depend on the system dynamics of the robot. This is modeled in the time domain, where detailed time-dependent component interaction is considered. The design perspective, however, is best represented in the property domain. Here, requirements on static component properties are formulated.

This paper presents a generic approach that connects the property and time domains to enable early-stage design decisions. The approach is applied to a 1-link robot system with a simple demonstrator transmission model, including properties that are typically not considered in the early design phase, like a nonlinear stiffness characteristic with backlash.

Keywords

Systems Engineering (SE)Product modelling / modelsSimulationMechatronicsmulti-disciplinary design
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 2585 - 2594
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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