Automatic Transcription of the Basic MTM-2 Motions in Virtual Reality

Valentina Gorobets (), Emmanouil Andreopoulos and Andreas Kunz
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Valentina Gorobets: ETH Zurich
Emmanouil Andreopoulos: ETH Zurich
Andreas Kunz: ETH Zurich

A chapter in Smart Services Summit, 2024, pp 263-266 from Springer

Abstract: Abstract This paper presents our approach for the automatic transcription of the MTM-2 basic motions in VR. We give an overview of what Methods-Time Measurement (MTM) is and how it is used for the improvement of manual workplace layouts. We describe the conventional approach used to deliver MTM codes by the MTM experts and explain the benefits of using automatic transcription in comparison to the conventional approach. We discuss the reasonability of using our approach and potential use cases for it, followed by presenting the hard- and software used for our implementation. Further, we explain the user study procedure that was used to receive data for the assessment of the proposed automatic transcription. Lastly, we present the metrics we used to evaluate our algorithm and deliver measurable results based on those metrics. In conclusion, we summarize our work and present ideas for future work on this topic.

Keywords: Methods-time measurement; Virtual reality; Action detection; Workplace optimization (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-031-60313-6_19

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DOI: 10.1007/978-3-031-60313-6_19

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