French, R., Marin-Reyes, H. orcid.org/0000-0002-2919-5388, Kapellmann Zafra, G. et al. (1 more author) (2019) Development of an intelligent robotic additive manufacturing cell for the nuclear industry. In: Karwowski, W., Trzcielinski, S. and Mrugalska, B., (eds.) Advances in Manufacturing, Production Management and Process Control. International Conference on Applied Human Factors and Ergonomics (AHFE 2019), 24-28 Jul 2019, Washington DC, USA. Advances in Intelligent Systems and Computing, 971 . Springer , pp. 3-13. ISBN 978-3-030-20493-8
Abstract
Applications of Advanced manufacturing methods in the nuclear industry to ensure quality, security, process codes and standardisation are increasingly needed to ease adoption of new technologies. Many assemblies and decommissioning tasks are still heavily dependent on experienced human engineers and practitioners. Human error in production plays a large part in the development of standardisation to avoid defects and increase productivity. Risks to humans, previously considered as “part of the job” are no longer acceptable. Within European manufacturing, a greater problem exists; a dwindling skilled workforce capable of delivering high precision manufactured products. To address these issues this paper describes the motivation, design and implementation phases of the SERFOW (Smart Enabling Robotics driving Free Form Welding) project, which is an automated fusion-welding cell, linking future nuclear industry manufacturing requirements by mimicking human skill and technical experience combined with academic knowledge and UK based innovation. Development of key machine vision systems combined with novel robotic grasping technology and experienced welding engineers has made possible the construction of a potentially disruptive robotic manufacturing platform.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2020. |
Keywords: | Robot; Grasper; Ergonomic·3D; Vision system; TIG welding; Additive manufacturing |
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: | 13 Jun 2019 10:04 |
Last Modified: | 13 Jun 2019 10:04 |
Status: | Published |
Publisher: | Springer |
Series Name: | Advances in Intelligent Systems and Computing |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-030-20494-5_1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:147198 |