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Knowledge Documentation Based on Automatic Identification and Clustering of Change Intentions in CAD Data of Wiring Harnesses

Published online by Cambridge University Press:  26 May 2022

K. Eder ,
W. Herzog ,
M. M. Altner ,
O. Tas ,
J. Neckenich  and
K. Paetzold
K. Eder*
Affiliation:
Mercedes-Benz AG, Germany Technische Universität Dresden, Germany
W. Herzog
Affiliation:
Mercedes-Benz AG, Germany
M. M. Altner
Affiliation:
Mercedes-Benz AG, Germany Karlsruhe Institute of Technology, Germany
O. Tas
Affiliation:
Mercedes-Benz AG, Germany
J. Neckenich
Affiliation:
Mercedes-Benz AG, Germany
K. Paetzold
Affiliation:
Technische Universität Dresden, Germany
*
kevin.eder@mercedes-benz.com

Abstract

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High amount of changes and increasing complexity in CAD design of wiring harnesses result in a lack of time for documentation and transfer of acquired knowledge. To be able to transfer the gained knowledge efficiently during development automating the identification, analyzation and documentation of changes is necessary. This paper shows a methodology to address this challenge for CAD data of wiring harnesses. Thus, it is shown how interrelated change elements can be combined or separated from each other according to their change intention.

Keywords

design knowledgeknowledge managementknowledge representationscomputer-aided design (CAD)

Information

Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 683 - 692
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), 2022.

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