Skip to main content

Research Repository

Advanced Search

A Framework for Self-configuration in Manufacturing Production Systems

Rehman, Hamood Ur; Chaplin, Jack C; Zarzycki, Leszek; Ratchev, Svetan

Authors

Hamood Ur Rehman

Leszek Zarzycki

Professor SVETAN RATCHEV svetan.ratchev@nottingham.ac.uk
CRIPPS PROFESSOR OF PRODUCTION ENGINEERING & HEAD OF RESEARCH DIVISION



Abstract

Intelligence in manufacturing enables the optimization and configuration of processes, and a goal of future smart manufacturing is to enable processes to configure themselves-called self-configuration. This paper describes a framework for utilising data to make decisions for the self-configuration of a production system device in a smart production environment. A data pipeline is proposed that connects the production system via a gateway to a cloud computing platform for machine learning and data analytics. Agent technology is used to implement the framework for this data pipeline. This is illustrated by a data oriented self-configuration solution for an industrial use-case based on a device used at a testing station in a production system. This research presents possible direction towards realising self-configuration in production systems.

Citation

Rehman, H. U., Chaplin, J. C., Zarzycki, L., & Ratchev, S. (2021, July). A Framework for Self-configuration in Manufacturing Production Systems. Presented at 12th Advanced Doctoral Conference On Computing, Electrical And Industrial Systems (DOCEIS2021), Caparica, Portugal

Presentation Conference Type Conference Paper (published)
Conference Name 12th Advanced Doctoral Conference On Computing, Electrical And Industrial Systems (DOCEIS2021)
Start Date Jul 7, 2021
End Date Jul 9, 2021
Acceptance Date Apr 20, 2021
Online Publication Date Jun 30, 2021
Publication Date Jun 30, 2021
Deposit Date Apr 28, 2021
Publisher Springer
Peer Reviewed Peer Reviewed
Pages 71-79
Series Title Doctoral Conference on Computing, Electrical and Industrial Systems
Series ISSN 1868-422X
Book Title Technological Innovation for Applied AI Systems : 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings
ISBN 9783030782870
DOI https://doi.org/10.1007/978-3-030-78288-7_7
Keywords data analytics; smart manufacturing; agent technology; configuration
Public URL https://nottingham-repository.worktribe.com/output/5501166
Publisher URL https://link.springer.com/chapter/10.1007/978-3-030-78288-7_7


You might also like



Downloadable Citations