Reverse engineering in circular product development
DS 133: Proceedings of the 35th Symposium Design for X (DFX2024)
Year: 2024
Editor: Dieter Krause; Kristin Paetzold-Byhain; Sandro Wartzack
Author: Markus Breidohr; Johannes Meyer; Hariharan Ravichandran; David Inkermann
Series: DfX
Institution: Institute of Mechanical Engineering, Technische Universitat Clausthal
Page(s): 163-172
DOI number: 10.35199/dfx2024.17
Abstract
In order to preserve our planet and protect the climate, resources must be conserved. Circular product development in particular can help to conserve resources by removing components from used devices and reusing them in the development and manufacture of new product generations. Reverse engineering fulfils a central task here by digitally mapping used components and enabling their integration into new products. This article presents an approach for an automated reverse engineering process based on image recordings and convolutional neural networks, which should be able to recognize defects in components. This approach is based on previous work in reverse engineering. The steps of the proposed process chain are demonstrated and its usability evaluated on the basis of an initial test run.
Keywords: Reverse Engineering, Convolutional Neural Network, Circular Economy, Defects in Components, Circular Product Generation