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A decision support system for rapid ramp-up of industry 4.0 enabled production systems

journal contribution
posted on 23.01.2020 by Stefanos Doltsinis, Pedro Ferreira, Mohammed Mabkhot, Niels Lohse

Production ramp-up is a key phase during the introduction or changeover of a production system. Process calibration and tuning are inevitably required to make such a system fully operational and let it reach its maximum production yield. A complex decision-making process takes place in order to optimally tune the system and requires a long time for testing and experimenting that will determine the system behaviour. This work considers the sequential nature of ramp-up and proposes a Cyber-Physical Systems approach based on data capturing, learning mechanisms and knowledge extraction, leading to an Industry 4.0 compliant Decision Support System (DSS) for human operators. The proposed system is implemented as an online DSS and also supports offline learning using previously gathered knowledge. A number of experiments have been carried out on a micro scale assembly station, validating the expected benefits of the proposed DSS. Results show a reduction of over 40% in the number of ramp-up steps required when using the DSS.


History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Computers in Industry

Volume

116

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Computers in Industry and the definitive published version is available at https://doi.org/10.1016/j.compind.2020.103190

Acceptance date

14/01/2020

Publication date

2020-01-22

Copyright date

2020

ISSN

0166-3615

Language

en

Depositor

Dr Pedro Ferreira Deposit date: 21 January 2020

Article number

103190

Exports