Equipment health monitoring for industrial robotic arms

Moore, J. orcid.org/0000-0002-5182-9439 and Sawyer, D. (2024) Equipment health monitoring for industrial robotic arms. In: 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE). IEEE International Conference on Automation Science and Engineering (CASE), 28 Aug - 01 Sep 2024, Bari, Italy. Institute of Electrical and Electronics Engineers (IEEE) ISBN 979-8-3503-5852-0

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Copyright, Publisher and Additional Information:

© 2024 The Author(s). Except as otherwise noted, this author-accepted version of a proceedings paper published in 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE) is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: Adaptation models; Accuracy; Service robots; Predictive models; Robot sensing systems; Manipulators; Data models; Maintenance; Robots; Long short term memory
Dates:
  • Published: 23 October 2024
  • Published (online): 23 October 2024
  • Accepted: 7 June 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > University of Sheffield Research Centres and Institutes > AMRC with Boeing (Sheffield)
The University of Sheffield > Advanced Manufacturing Institute (Sheffield) > AMRC with Boeing (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 18 Jun 2024 09:54
Last Modified: 28 Oct 2024 09:42
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: 10.1109/CASE59546.2024.10711629
Related URLs:
Open Archives Initiative ID (OAI ID):

Export

Statistics