A fundamental approach for data acquisition on machine tools as enabler for analytical Industrie 4.0 applications
dc.contributor.author
Gittler, Thomas
dc.contributor.author
Gontarz, Adam
dc.contributor.author
Weiss, Lukas
dc.contributor.author
Wegener, Konrad
dc.contributor.editor
Teti, Roberto
dc.contributor.editor
D'Addona, Doriana M.
dc.date.accessioned
2021-07-05T11:31:57Z
dc.date.available
2019-04-23T08:13:28Z
dc.date.available
2019-04-23T08:51:16Z
dc.date.available
2019-04-23T08:55:29Z
dc.date.available
2021-07-05T11:31:57Z
dc.date.issued
2019
dc.identifier.issn
2212-8271
dc.identifier.other
10.1016/j.procir.2019.02.088
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/338956
dc.identifier.doi
10.3929/ethz-b-000338956
dc.description.abstract
Decreasing ICT-costs propel connectivity and storage solutions for data generated, harvested and analyzed in machine tools. To acquire the necessary reliable, comprehensive and structured data for analytical applications, data from multiple sources must be acquired and combined. Many approaches for data acquisition either fail to cover all relevant data or cannot be put into action due to limited access on numerical controls. The following paper demonstrates the use of a multi-channel measurement application of a machine tool including its auxiliaries. The given approach was applied and verified on prototype machines. As a result, the application in current and future use-cases is discussed.
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
Machine tools
en_US
dc.subject
ICT
en_US
dc.subject
data analysis
en_US
dc.subject
data acquisition
en_US
dc.subject
Industrie 4.0
en_US
dc.subject
Efficiency improvements
en_US
dc.subject
statistical analysis
en_US
dc.subject
Machine Monitoring
en_US
dc.title
A fundamental approach for data acquisition on machine tools as enabler for analytical Industrie 4.0 applications
en_US
dc.type
Conference Paper
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
dc.date.published
2019-03-13
ethz.book.title
12th CIRP Conference on Intelligent Computation in Manufacturing Engineering
en_US
ethz.journal.title
Procedia CIRP
ethz.journal.volume
79
en_US
ethz.pages.start
586
en_US
ethz.pages.end
591
en_US
ethz.size
6 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.event
12th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME 2018)
en_US
ethz.event.location
Gulf of Naples, Italy
en_US
ethz.event.date
July 18-20, 2018
en_US
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.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.relation.isCitedBy
10.3929/ethz-b-000438683
ethz.relation.isCitedBy
10.3929/ethz-b-000440714
ethz.date.deposited
2019-04-23T08:13:43Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-04-23T08:51:59Z
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2024-02-02T14:15:10Z
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true
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Conference Paper [34969]