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Next Generation Condition Based Predictive Maintenance
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Adaptive Manufacturing)ORCID iD: 0000-0002-8906-630X
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Adaptive Manufacturing)
Department of Production Engineering Royal Institute of Technology, Sweden.
2014 (English)In: Proceedings of The 6th International Swedish Production Symposium 2014 / [ed] Johan Stahre, Björn Johansson, Mats Björkman, 2014Conference paper, Published paper (Refereed)
Abstract [en]

Maintenance of assembly and manufacturing equipment is crucial to ensure productivity, product quality, on-time delivery, and a safe working environment. Predictive Maintenance is an approach that utilises the condition monitoring data to predict the future machine conditions and make decisions upon this prediction. The main aim of the presented research is to achieve an improvement in condition based Predictive Maintenance through the Cloud-based approach with usage of the largest information content possible. The objective of this paper is to outline the first steps of a framework to handle and process maintenance, production and factory related data from the first life-cycle phase to the operation and maintenance phase.

Place, publisher, year, edition, pages
2014.
Keyword [en]
predictive maintenance, prognosis, cloud-based maintenance
National Category
Reliability and Maintenance
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-9988ISBN: 978-91-980974-1-2 OAI: oai:DiVA.org:his-9988DiVA: diva2:748786
Conference
The 6th International Swedish Production Symposium 2014 16-18 September 2014
Available from: 2014-09-22 Created: 2014-09-22 Last updated: 2017-11-27Bibliographically approved

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fulltext(374 kB)1777 downloads
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b6e995fc24c9ae89c42c50c3899bd4ac357064d44d1eccc1a401ffd49b2825b4c9ce15d993f8c8c32c84254109b260b890e900909270ae94fd49efad9487c427
Type fulltextMimetype application/pdf

Authority records BETA

Schmidt, BernardSandberg, UlfWang, Lihui

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CiteExportLink to record
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