Dr David Sanderson DAVID.SANDERSON@NOTTINGHAM.AC.UK
SENIOR RESEARCH FELLOW
Context-Aware Plug and Produce for Robotic Aerospace Assembly
Sanderson, David; Shires, Emma; Chaplin, Jack C; Brookes, Harvey; Liaqat, Amer; Ratchev, Svetan
Authors
Emma Shires
Dr JACK CHAPLIN Jack.Chaplin@nottingham.ac.uk
ASSISTANT PROFESSOR
Harvey Brookes
Amer Liaqat
Professor SVETAN RATCHEV svetan.ratchev@nottingham.ac.uk
CRIPPS PROFESSOR OF PRODUCTION ENGINEERING & HEAD OF RESEARCH DIVISION
Abstract
Aerospace production systems face increasing requirements for flexibility and reconfiguration, along with considerations of cost, utilisation, and efficiency. This drives a need for systems with a small number of automation platforms (e.g. industrial robots) that can make use of a larger number of end effectors that are potentially flexible or multifunctional. This leads to the challenge of ensuring that the configuration and location of each end effector is tracked by the system at all times, even in the face of manual adjustments, to ensure that the correct processes are applied to the product at the right time. We present a solution based on a Data Distribution Service that provides the system with full awareness of the context of its automation platforms and end effectors. The solution is grounded with an example use case from WingLIFT, a research programme led by a large aerospace manufacturer. The WingLIFT project in which this solution was developed builds on the adaptive systems approach from the Evolvable Assembly Systems project, with focus on extending and increasing the aerospace industrial applicability of plug and produce techniques. The design of this software solution is described from multiple perspectives, and accompanied by details of a physical demonstration cell that is in the process of being commissioned.
Citation
Sanderson, D., Shires, E., Chaplin, J. C., Brookes, H., Liaqat, A., & Ratchev, S. (2020, December). Context-Aware Plug and Produce for Robotic Aerospace Assembly. Presented at IPAS 2020: 9th International Precision Assembly Seminar, Kitzbühel, Austria
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | IPAS 2020: 9th International Precision Assembly Seminar |
Start Date | Dec 13, 2020 |
End Date | Dec 15, 2020 |
Acceptance Date | Feb 12, 2020 |
Online Publication Date | Apr 2, 2021 |
Publication Date | 2021 |
Deposit Date | Apr 21, 2020 |
Publicly Available Date | Apr 2, 2021 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Pages | 184-199 |
Series Title | IFIP Advances in Information and Communication Technology |
Series Number | 620 |
Series ISSN | 1868-422X |
Book Title | Smart Technologies for Precision Assembly. 9th IFIP WG 5.5 International Precision Assembly Seminar, IPAS 2020, Virtual Event, December 14–15, 2020, Revised Selected Papers |
ISBN | 9783030726317 |
DOI | https://doi.org/10.1007/978-3-030-72632-4_13 |
Public URL | https://nottingham-repository.worktribe.com/output/4324527 |
Publisher URL | https://link.springer.com/chapter/10.1007%2F978-3-030-72632-4_13 |
Related Public URLs | https://www.ipas-seminar.com/ |
Files
20200127 Ipas
(1 Mb)
PDF
You might also like
Optimal Manufacturing Configuration Selection: Sequential Decision Making and Optimization using Reinforcement Learning
(2023)
Presentation / Conference Contribution
Efficient decision-making in SMEs: leveraging knowledge graphs with Neo4j and AI vision
(2023)
Presentation / Conference Contribution
Semantic models and knowledge graphs as manufacturing system reconfiguration enablers
(2023)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search