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Predictive Maintenance: Literature Review and Future Trends
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-8906-630X
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-8679-8049
2015 (English)In: Proceedings of the 25th International Conference on Flexible Automation and Intelligent Manufacturing: Volume I - Designing for Advanced, High Value Manufacturing and Intelligent Systems for the 21st Century / [ed] Chike F. Oduoza, Wolverhampton, UK: The Choir Press , 2015, Vol. 1, p. 232-239Conference paper, Published paper (Refereed)
Abstract [en]

In manufacturing industry machines and systems become more advanced and complicated. Proper maintenance is crucial to ensure productivity, product quality, on-time delivery, and safe working environment. Recently, the importance of the predictive maintenance has been growing rapidly. Well applied predictive maintenance can be in many cases more cost effective than traditional corrective and preventive approaches to maintenance. Targeting this vibrant field, this paper reviews the literature of Predictive Maintenance (PdM). Published literature is systematically categorised and then methodically reviewed and analysed. Methodology for data acquisition, feature extraction, failure detection and prediction are presented. The connection between Maintenance field and Information Fusion has been highlighted. Statistical analysis based on Elsevier’s Scopus abstract and citation database has been performed. Various emerging trends in the field of Predictive Maintenance are identified to help specifying gaps in the literature and direct research efforts.

Place, publisher, year, edition, pages
Wolverhampton, UK: The Choir Press , 2015. Vol. 1, p. 232-239
Keywords [en]
Predictive Maintenance, Condition Based Maintenance
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Technology; Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-11243ISBN: 978-1-910864-00-5 (print)ISBN: 1910864005 (print)OAI: oai:DiVA.org:his-11243DiVA, id: diva2:827420
Conference
The International Conference on Flexible Automation and Intelligent Manufacturing (FAIM), 23-26 June 2015, University of Wolverhampton, UK
Available from: 2015-06-26 Created: 2015-06-26 Last updated: 2019-12-20Bibliographically approved

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Schmidt, BernardWang, Lihui

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