Benakis, M. orcid.org/0000-0002-2986-2873, Du, C., Patran, A. et al. (1 more author) (2019) Welding process monitoring applications and industry 4.0. In: 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE). 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), 22-26 Aug 2019, Vancouver, BC, Canada. Institute of Electrical and Electronics Engineers (IEEE) ISBN 9781728103570
Abstract
With the fourth industrial revolution in progress, traditional manufacturing processes are being transformed. Fusion welding is no exception from this transformation. The centuries-old manual craft is being reshaped by cyber-physical systems, turning into a digitized process governed by industrial informatics. By implementing process monitoring in welding applications invaluable data are collected that can be utilized in the new, futuristic smart factories of Industry 4.0.
In this article two purposes are being served. The first is to present the status quo alongside the future trends of welding process monitoring on industrial implementation. The second is to present the results of an ongoing investigation of robotic Gas Tungsten Arc Welding (GTAW) monitoring for defect detection and characterization. Deviations from the optimal values in three welding conditions (surface integrity, shielding gas flow rate and surface contamination) were introduced during stainless steel 316L beads-on-plates welding. Acquired data during the welding process were used to extract features in order to identify correlations between the disturbances and the monitored signals.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Physics and Astronomy (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 Sep 2019 14:34 |
Last Modified: | 19 Sep 2020 00:38 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/COASE.2019.8843319 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:150228 |