Virtual reality training platform for a computer numerically controlled grinding machine tool
dc.contributor.author
Hirt, Christian
dc.contributor.author
Spahni, Martina
dc.contributor.author
Kompis, Yves
dc.contributor.author
Jetter, Dominic
dc.contributor.author
Kunz, Andreas
dc.date.accessioned
2022-05-30T07:03:16Z
dc.date.available
2021-06-09T04:41:47Z
dc.date.available
2021-06-09T05:20:30Z
dc.date.available
2022-05-27T10:22:18Z
dc.date.available
2022-05-30T07:03:16Z
dc.date.issued
2021
dc.identifier.issn
1753-1039
dc.identifier.issn
1753-1047
dc.identifier.other
10.1504/ijmms.2021.115460
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/488893
dc.identifier.doi
10.3929/ethz-b-000488893
dc.description.abstract
In-depth training of machine tool (MT) operators is crucial to avoid
machine damage due to faulty operation. However, machine-hours are costly and
during the training, the MT is unavailable for regular production purposes. Here, virtual real-size models offer a solution by providing basic operation principles to future operators. In this context, it is yet unknown whether a virtual teaching enhanced by real walking is similar to a real teaching scenario regarding the learning efficiency and long-term memory retention. This paper describes a study comparing the learning efficiency of a virtual training session with traditional instructions on a real MT. The learning success of both training groups is objectively and subjectively assessed on a realMTa week later. In this assessment, the task completion time and the number of errors are recorded. We observed that the virtually taught group slightly outperformed trainees taught in reality regarding both objective measurements.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Inderscience Publishers
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Virtual Reality
en_US
dc.subject
Virtual Training
en_US
dc.subject
Digital Twin
en_US
dc.subject
Machine Tool Training
en_US
dc.subject
Real walking in virtual environments
en_US
dc.title
Virtual reality training platform for a computer numerically controlled grinding machine tool
en_US
dc.type
Journal Article
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2021-05-29
ethz.journal.title
International Journal of Mechatronics and Manufacturing Systems
ethz.journal.volume
14
en_US
ethz.journal.issue
1
en_US
ethz.pages.start
1
en_US
ethz.pages.end
17
en_US
ethz.size
17 p.
en_US
ethz.version.deposit
acceptedVersion
en_US
ethz.identifier.scopus
ethz.publication.place
Meyrin
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::08844 - Kunz, Andreas (Tit.-Prof.) / Kunz, Andreas (Tit.-Prof.)
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.)
en_US
ethz.relation.hasPart
20.500.11850/383598
ethz.date.deposited
2021-06-09T04:42:07Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.date.embargoend
2022-05-28
ethz.rosetta.installDate
2021-06-09T05:20:41Z
ethz.rosetta.lastUpdated
2024-02-02T17:19:34Z
ethz.rosetta.versionExported
true
ethz.COinS
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Journal Article [130133]