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dc.contributor.author
Engeler, Marc
dc.contributor.author
Elmiger, Andreas
dc.contributor.author
Kunz, Andreas
dc.contributor.author
Zogg, David
dc.contributor.author
Wegener, Konrad
dc.contributor.editor
Outeiro, José
dc.contributor.editor
Poulachon, Gérard
dc.date.accessioned
2021-07-05T13:20:01Z
dc.date.available
2017-06-18T14:25:11Z
dc.date.available
2017-06-20T08:43:30Z
dc.date.available
2017-06-20T08:47:03Z
dc.date.available
2018-07-16T07:37:36Z
dc.date.available
2021-07-05T13:18:54Z
dc.date.available
2021-07-05T13:20:01Z
dc.date.issued
2017
dc.identifier.issn
2212-8271
dc.identifier.other
10.1016/j.procir.2017.04.003
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/161251
dc.identifier.doi
10.3929/ethz-b-000161251
dc.description.abstract
In order to increase machinery resource, energy and time efficiency, Condition Monitoring (CM) offers a wide set of beneficial tools. Those tools can basically be segmented in maintenance improvements or the optimization of process parameters. CM requires data input from a component, which is then analyzed using data based or physical models, which return an estimate of the component_s current condition. The use of high quality sensors in a stable laboratory environment generally leads to an overemphasizing of the results which CM systems achieve in an industrial environment. Additionally, the installation of sensors is not always economically feasible for low-cost machinery. To overcome this, the CM system which is presented in this paper uses data, which is usually present in the PLC, as a consequence thereof, the data quality is significantly lower compared to dedicated sensor equipment. A real production machinery is further used to demonstrate the capabilities of condition monitoring in an industrial environment. The data driven CM process, which is used in this application example is compared to a model driven approach, conducted on a test equipment machine.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject
Monitoring
en_US
dc.subject
Diagnostics
en_US
dc.subject
Optimisation of Machining Processes
en_US
dc.title
Online Condition Monitoring Tool for Automated Machinery
en_US
dc.type
Conference Paper
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
dc.date.published
2017-05-31
ethz.book.title
16th CIRP Conference on Modelling of Machining Operations
en_US
ethz.journal.title
Procedia CIRP
ethz.journal.volume
58
en_US
ethz.pages.start
323
en_US
ethz.pages.end
328
en_US
ethz.size
6 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.code.ddc
DDC - DDC::6 - Technology, medicine and applied sciences::670 - Manufacturing
en_US
ethz.event
16th CIRP Conference on Modeling of Machining Operations (CIRP CMMO 2017)
en_US
ethz.event.location
Cluny, France
en_US
ethz.event.date
June 15-16, 2017
en_US
ethz.identifier.wos
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing::03641 - Wegener, Konrad (emeritus) / Wegener, Konrad (emeritus)
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing::08844 - Kunz, Andreas (Tit.-Prof.) / Kunz, Andreas (Tit.-Prof.)
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing::03641 - Wegener, Konrad (emeritus) / Wegener, Konrad (emeritus)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing::08844 - Kunz, Andreas (Tit.-Prof.) / Kunz, Andreas (Tit.-Prof.)
ethz.tag
Numerical and Analytical Modeling
en_US
ethz.date.deposited
2017-06-18T14:25:12Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-06-20T08:43:35Z
ethz.rosetta.lastUpdated
2024-02-02T14:15:35Z
ethz.rosetta.versionExported
true
ethz.COinS
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