Predictive Maintenance in production

Wöstmann, R; Strauss, P; Deuse, J

Predictive Maintenance in production

Wöstmann, R Strauss, P Deuse, J

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Publication Type:: Journal Article
Citation:: WT Werkstattstechnik, 2017, 107, (7-8), pp. 524-529
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Wöstmann, R
dc.contributor.author	Strauss, P
dc.contributor.author	Deuse, J https://orcid.org/0000-0003-4066-4357
dc.date.accessioned	2022-09-22T23:04:59Z
dc.date.available	2022-09-22T23:04:59Z
dc.date.issued	2017-01-01
dc.identifier.citation	WT Werkstattstechnik, 2017, 107, (7-8), pp. 524-529
dc.identifier.issn	1436-4980
dc.identifier.uri	http://hdl.handle.net/10453/162015
dc.description.abstract	Due to new possibilities of connectivity and data processing of assets and components, predictive maintenance has gained a growing importance. While it has been used in aerospace, supply or energy technology for many years, there are still few applications to be found within production. This paper outlines unused potential in presenting a classification of existing predictive maintenance applica- tions and their transferability to production as well as prerequisites for a successful implementation.
dc.language	en
dc.relation.ispartof	WT Werkstattstechnik
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Predictive Maintenance in production
dc.type	Journal Article
utslib.citation.volume	107
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2022-09-22T23:04:57Z
pubs.issue	7-8
pubs.publication-status	Published
pubs.volume	107
utslib.citation.issue	7-8

Abstract:

Due to new possibilities of connectivity and data processing of assets and components, predictive maintenance has gained a growing importance. While it has been used in aerospace, supply or energy technology for many years, there are still few applications to be found within production. This paper outlines unused potential in presenting a classification of existing predictive maintenance applica- tions and their transferability to production as well as prerequisites for a successful implementation.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/162015