Potentials of Motion Capturing in the Creation of Time Measurements and Ergonomic Execution Analysis

Jansing, S; Brockmann, B; Möhle, R; Patzelt, D; Deuse, J

Potentials of Motion Capturing in the Creation of Time Measurements and Ergonomic Execution Analysis

Jansing, S Brockmann, B Möhle, R Patzelt, D Deuse, J

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Publisher:: De Gruyter
Publication Type:: Journal Article
Citation:: ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, 2023, 118, (1-2), pp. 74-78
Issue Date:: 2023-02-01

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Field	Value	Language
dc.contributor.author	Jansing, S
dc.contributor.author	Brockmann, B
dc.contributor.author	Möhle, R
dc.contributor.author	Patzelt, D
dc.contributor.author	Deuse, J https://orcid.org/0000-0003-4066-4357
dc.date.accessioned	2024-03-20T06:07:03Z
dc.date.available	2024-03-20T06:07:03Z
dc.date.issued	2023-02-01
dc.identifier.citation	ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, 2023, 118, (1-2), pp. 74-78
dc.identifier.issn	0947-0085
dc.identifier.issn	2511-0896
dc.identifier.uri	http://hdl.handle.net/10453/176944
dc.description.abstract	In addition to economic design, the ergonomic optimization of work systems is gaining in importance. However, high personnel costs for the creation of movement-economic analyses are obstacles for industrial use. Markerless motion capturing offers potential for the effort-reduced creation of these analyses based on the process building block system MTM-Human Work Design. The paper describes how machine learning can be used for motion analysis using abstracted video data.
dc.language	en
dc.publisher	De Gruyter
dc.relation.ispartof	ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb
dc.relation.isbasedon	10.1515/zwf-2023-1008
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Industrial Engineering & Automation
dc.subject.classification	4014 Manufacturing engineering
dc.title	Potentials of Motion Capturing in the Creation of Time Measurements and Ergonomic Execution Analysis
dc.type	Journal Article
utslib.citation.volume	118
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
pubs.organisational-group	University of Technology Sydney/Strength - CAM - Centre for Advanced Manufacturing
utslib.copyright.status	closed_access	*
dc.date.updated	2024-03-20T06:07:02Z
pubs.issue	1-2
pubs.publication-status	Published
pubs.volume	118
utslib.citation.issue	1-2

Abstract:

In addition to economic design, the ergonomic optimization of work systems is gaining in importance. However, high personnel costs for the creation of movement-economic analyses are obstacles for industrial use. Markerless motion capturing offers potential for the effort-reduced creation of these analyses based on the process building block system MTM-Human Work Design. The paper describes how machine learning can be used for motion analysis using abstracted video data.

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

http://hdl.handle.net/10453/176944