Title: Automated repairing process of metal components in manufacturing with directed energy deposition

Authors: Daniel Knüttel; Anneke Orlandini; Stefano Baraldo; Anna Valente; Emanuele Carpanzano; Konrad Wegener

Addresses: Intelligent Production Machines, Inspire AG, Technoparkstrasse 1, 8005, Schweiz, Zürich, Switzerland; ETH Zürich, IWF – Institute for Machine Tools and Manufacturing, Leonhardstrasse 21, 8092 Zürich, Switzerland ' Department of Innovative Technologies, University of Applied Science and Arts of Southern Switzerland, Polo universitario Lugano, Campus Est, Via la Santa 1 CH-6962 Lugano-Viganello, Lugano, Switzerland ' Department of Innovative Technologies, University of Applied Science and Arts of Southern Switzerland, Polo universitario Lugano, Campus Est, Via la Santa 1 CH-6962 Lugano-Viganello, Lugano, Switzerland ' Department of Innovative Technologies, University of Applied Science and Arts of Southern Switzerland, Polo universitario Lugano, Campus Est, Via la Santa 1 CH-6962 Lugano-Viganello, Lugano, Switzerland ' Department of Innovative Technologies, University of Applied Science and Arts of Southern Switzerland, Polo universitario Lugano, Campus Est, Via la Santa 1 CH-6962 Lugano-Viganello, Lugano, Switzerland ' ETH Zürich, IWF – Institute for Machine Tools and Manufacturing, Leonhardstrasse 21, 8092 Zürich, Switzerland

Abstract: The importance of repairing processes is increasingly gaining in importance. In this regard, directed energy deposition (DED) is a promising metal additive manufacturing technology for the refurbishment of components. However, the practical implementation and daily utilisation of such processes for repairing purposes introduces a high amount of complexity. The repairing processes are labour and time intensive, thus limiting their adoption in industry. This work demonstrates the automation of the repairing process by leveraging AI-based methods and further algorithms to overcome current limitations. The proposed workflow covers the repairing process starting from the reverse engineering of the damaged part by a 3D scanner integrated within the machine, up to the material addition by DED, to enable a more profitable solution and a step towards circular economy.

Keywords: circular economy; manufacturing; process automation; repairing; metals; lasers; DED; directed energy deposition; additive manufacturing; artificial intelligence.

DOI: 10.1504/IJMMS.2024.143031

International Journal of Mechatronics and Manufacturing Systems, 2024 Vol.17 No.2, pp.150 - 179

Received: 30 Jan 2024
Accepted: 08 Apr 2024
Published online: 02 Dec 2024 *

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