Analysing Body Motions Using Motion Capture Data

Benter, Martin; Kuhlang, Peter

doi:10.1007/978-3-030-20040-4_12

Cited by 7 publications

(3 citation statements)

References 2 publications

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“…This is a problem stemming from the algorithm's reliance on hard-coded sequences of data to converge to a detection. Another piece of work for an automated MTM transcription is from Benter & Kuhlang [16]. Their approach relies on Microsoft Kinect's full body tracking data, which does not track sufficiently the leg movements, as stated by the authors.…”

Section: Related Workmentioning

confidence: 99%

Automatic MTM-Transcription in Virtual Reality Using the Digital Twin of a Workplace

Andreopoulos¹,

Gorobets

Künz³

2022

Preprint

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Despite the high level of automation in industrial production, manual operations still play an important role and contribute significantly to the overall production costs. For the evaluation of these manual processes the ``Methods-Time Measurement'' (MTM) is widely used. This method is applied to real workplaces or mock-ups thereof, while also Virtual Reality (VR) can be used for the representation of such workplaces. However, the evaluation of the workers' performed actions is still done manually, which is a time-consuming and error-prone process. This paper introduces an approach to automatically detect full-body actions of users in VR and consequently derive the appropriate MTM values, without knowledge of a pre-existing workplan. The detection algorithm that was developed is explained in detail and its performance is analyzed through a user study with 30 participants.

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Section: Related Workmentioning

confidence: 99%

Automatic MTM-Transcription in Virtual Reality Using the Digital Twin of a Workplace

Andreopoulos¹,

Gorobets

Künz³

2022

Preprint

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“…With the spread of information technology, different approaches for analyzing workers' performance and training new workers had appeared. Benter et al [3] introduced an approach that used a 3D camera to capture data and analyzed working time with the MTM-1 method. The workplace consisted of three workstations, and the worker was assembling gearboxes for the duration of 20 min.…”

Section: Related Workmentioning

confidence: 99%

A VR-based approach in conducting MTM for manual workplaces

Gorobets

Holzwarth

Hirt

et al. 2021

Int J Adv Manuf Technol

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Due to current trends in the manufacturing industry, such as mass customization, manual operations contribute drastically to the overall costs of a product. Methods-Time-Measurement (MTM) identifies the optimization potential of manual workplaces, which significantly influences a worker’s productivity. However, traditional MTM requires great efforts to observe and transcribe manual assembly processes. Yet, various digital approaches exist that facilitate MTM analyses. While most of these approaches require the existence of real workplaces or cardboard mock-ups, it would be beneficial to conduct a virtual MTM in earlier phases of production planning. However, the quality of virtual MTM analyses compared to traditional MTM conducted in reality has not been assessed yet. This paper is addressing it by conducting a comparative user study with 21 participants completing the same task both at a real and virtual workplace, which they access via virtual reality technology. Our results show that participants’ MTM-2 values achieved at the VR workplace are comparable to those at the real workplace. However, time study data reveals that participants moved considerably slower in VR and thus needed more time to accomplish the task. Consequently, for the measurement of manual work in VR, it is even necessary to utilize predetermined times, such as MTM-2 since time study data is insufficient. This paper also serves as a proof of concept for future studies, investigating automated transcription systems that would further decrease the efforts conducting MTM analyses.

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“…Recently, Benter and Kuhlang [11] proposed an approach to detect body motions in accordance to MTM-1 using motion capture data from 3D cameras. In [12], the authors proposed an automatic generation of the MTM-1 code from motion capture data using convolutional neural network.…”

Section: Related Workmentioning

confidence: 99%

Towards Method Time Measurement Identification Using Virtual Reality and Gesture Recognition

Bellarbi

Jessel

Dalto³

2019

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

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Methods-Time Measurement (MTM) is a predetermined motion time system that is used primarily in industrial settings to analyze the methods used to perform any manual operation. In this paper, we introduce a system for automatic generation of MTM codes using only head and both hands 3D tracking. Our approach relies on the division of gestures into small elementary movements. Then, we built a decision tree to aggregate these elementary movements in order to generate the realized MTM code. The proposed system does not need any pre-learning step, and it can be useful in both virtual environments to train technicians and in real cases with industrial workshops to assist experts for MTM code identification. Obtained results are satisfying and promising. This work is in progress, we plan to improve it in the near future.

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Analysing Body Motions Using Motion Capture Data

Cited by 7 publications

References 2 publications

Automatic MTM-Transcription in Virtual Reality Using the Digital Twin of a Workplace

Automatic MTM-Transcription in Virtual Reality Using the Digital Twin of a Workplace

A VR-based approach in conducting MTM for manual workplaces

Towards Method Time Measurement Identification Using Virtual Reality and Gesture Recognition

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