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EVALUATING MBSE POTENTIAL USING PRODUCT AND DEVELOPMENT CHARACTERISTICS – A STATISTICAL INVESTIGATION

Part of: Systems Engineering and Design

Published online by Cambridge University Press:  11 June 2020

M. Schöberl ,
E. Rebentisch ,
J. Trauer ,
M. Mörtl  and
J. Fottner
M. Schöberl*
Affiliation:
Technical University of Munich, Germany
E. Rebentisch
Affiliation:
Massachusetts Institute of Technology, United States of America
J. Trauer
Affiliation:
Technical University of Munich, Germany
M. Mörtl
Affiliation:
Technical University of Munich, Germany
J. Fottner
Affiliation:
Technical University of Munich, Germany
*
*max.schoeberl@tum.de

Abstract

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As model-based systems engineering (MBSE) is evolving, the need for evaluating MBSE approaches grows. Literature shows that there is an untested assertion in the MBSE community that complexity drives the adoption of MBSE. To assess this assertion and support the evaluation of MBSE, a principal component analysis was carried out on eight product and development characteristics using data collected in an MBSE course, resulting in organizational complexity, product complexity and inertia. To conclude, the method developed in this paper enables organisations to evaluate their MBSE adoption potential.

Keywords

model-based systems engineeringcomplexityempirical studiesdesign methodology

Information

Type
Article
Information
Proceedings of the Design Society: DESIGN Conference , Volume 1 , May 2020 , pp. 2385 - 2394
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), 2020. Published by Cambridge University Press

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