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SELECTION OF MODEL APPROACHES AND MODELLING METHODS FOR LIFETIME PROGNOSIS

Published online by Cambridge University Press:  19 June 2023

Robin Steve Bauer  and
David Inkermann
Robin Steve Bauer*
Affiliation:
Technische Universität Clausthal
David Inkermann
Affiliation:
Technische Universität Clausthal
*
Bauer, Robin Steve, Technische Universität Clausthal, Germany, bauer@imw.tu-clausthal.de

Abstract

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Lifetime prognoses are fundamentally important to improve products regarding safety, costs, availability and sustainability. To modelling the lifetime of a system or its components and subsystems different methods and model approaches are available, which are not compatible in any case. Depending on the system, use case and available data, the existing model approaches and modelling methods are differently suitable for a precise lifetime prediction. In this contribution a procedure was developed to help in the selection of suitable approach-method combinations. For this purpose, the compatibility of method types with the different model approaches was assessed and criteria for the pre-selection of suitable approaches and methods for lifetime modelling were defined. The selection procedure was applied to the example of entities for electric powertrains of aircraft in early design stages. Finally, the results were summarized and evaluated. The insights gained in this paper can help to enhance lifetime models of products in early design phases.

Keywords

Product Lifecycle Management (PLM)Product modelling / modelsOptimisationLifetime HeterogeneityAircraft
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 3125 - 3134
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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