INDIN2015 SelSus - Towards A Reference Architecture for Diagnostics and Predictive Maintenance Using Smart Manufacturing Devices.pdf (382.34 kB)
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SelSus: Towards a reference architecture for diagnostics and predictive maintenance using smart manufacturing devices

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conference contribution
posted on 27.05.2016, 10:49 authored by Mohamed S. Sayed, Niels LohseNiels Lohse, Nicolaj Sondberg-Jeppesen, Anders L. Madsen
© 2015 IEEE. We propose a reference architecture, SelSus (SELf-SUStaining Manufacturing Systems) that aims to enable the provisioning of diagnostic and prognostic capabilities in manufacturing systems that utilize the notions of 'smart' automation devices.

Funding

This work is part of the project ”Health Monitoring and Life-Long Capability Management for SELf-SUStaining Manufacturing Systems (SelSus)” which is funded by the Commission of the European Communities under the 7th Framework Programme, Grant agreement no: 609382.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Proceeding - 2015 IEEE International Conference on Industrial Informatics, INDIN 2015

Pages

1700 - 1705

Citation

2015. SelSus: Towards a reference architecture for diagnostics and predictive maintenance using smart manufacturing devices. IN: 2015 13th IEEE International Conference on Industrial Informatics, (INDIN 2015), Cambridge, 22-24th July, pp. 1700-1705.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

Notes

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ISBN

9781479966493

ISSN

1935-4576

Language

en

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