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IMPLEMENTATION AND INTERPRETATION OF A SCRAP AND FAILURE ORIENTED MULTI-OBJECTIVE OPTIMIZATION CONSIDERING OPERATIONAL WEAR

Published online by Cambridge University Press:  19 June 2023

Christoph Bode ,
Stefan Goetz ,
Benjamin Schleich  and
Sandro Wartzack
Christoph Bode*
Affiliation:
Friedrich-Alexander-Universitat Erlangen-Nurnberg, Engineering Design, MartensstraBe 9, 91058 Erlangen, Germany
Stefan Goetz
Affiliation:
Friedrich-Alexander-Universitat Erlangen-Nurnberg, Engineering Design, MartensstraBe 9, 91058 Erlangen, Germany
Benjamin Schleich
Affiliation:
Product Life Cycle Management, Technische Universitat Darmstadt, Otto-Berndt-StraBe 2, 64287 Darmstadt
Sandro Wartzack
Affiliation:
Friedrich-Alexander-Universitat Erlangen-Nurnberg, Engineering Design, MartensstraBe 9, 91058 Erlangen, Germany
*
Bode, Christoph, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Germany, bode@mfk.fau.de

Abstract

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The tolerancing of products for manufacturing is usually performed at the end of the design process and the responsibility of the designer. Although components are commonly tolerated to ensure functionality, time-based influences, like wear, that occur during operation, are often neglected. This could result in small amounts of scrap after production, but high quantities of failure during operation. To overcome this issue, this paper presents an approach to perform a multi-objective optimization considering tolerances based on a wear simulation. Thereby, mean shifts serve as optimization variables, while the aim of the optimization is to generate an optimal ratio of scrap to failure. In addition, the optimization results are interpreted and further options for the designer are presented. Moreover, the approach is exemplary applied to a use case.

Keywords

Tolerance representation and managementOptimisationSimulationScrap and failureOperational wear
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 2225 - 2234
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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