| Title: | Evaluation of the EAWS ergonomic analysis on the assembly line: xsens vs. manual expert method—a case study |
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| Authors: | ID Breznik, Matic (Author)
ID Buchmeister, Borut (Author)
ID Vujica-Herzog, Nataša (Author) |
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| Files: |  sensors-25-04564-v2_(1).pdf (2,23 MB)
MD5: 07D10A6AA777B152CF160AB8475B32D3
 https://www.mdpi.com/1424-8220/25/15/4564
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | This study investigates the effectiveness of the Xsens motion capture system in performing ergonomic analysis compared to traditional manual assessments by experts in the specific environment of assembly lines. A comprehensive literature review emphasizes the need to investigate the reliability of new, promising high-tech systems. The main objective was therefore to compare the Ergonomic Assessment Worksheet (EAWS) assessment approach performed with Xsens motion capture technology and Process Simulate V16 software with the manual method using EAWS digital prepared by experts in the controlled workflow. The greatest value of the research conducted lies in the novel integration of the state-of-theart Xsens motion capture technology with the Process Simulate V16 software environment and the use of the licensed EAWS ergonomic method and Methods-Time Measurement Universal Analyzing System (MTM-UAS). The results are presented in the form of a case study. The results show a large similarity between the whole-body results and a large difference in the upper limb results, confirming the initial benefits of the Xsens equipment but also pointing to the need to verify its reliability on larger samples. The study highlights the potential of integrating Xsens motion capture data into ergonomic assessments and tuning of the assembly line to increase productivity and worker safety. |
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| Keywords: | Xsens, motion capture, EWAS, ergonomic analysis, reliability |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 23.04.2025 |
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| Article acceptance date: | 21.07.2025 |
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| Publication date: | 23.07.2025 |
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| Publisher: | MDPI |
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| Year of publishing: | 2025 |
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| Number of pages: | 18 str. |
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| Numbering: | Vol. 25, iss. 15, [article no.] 4564 |
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| PID: | 20.500.12556/DKUM-94321  |
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| UDC: | 658.5.331.1 |
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| ISSN on article: | 1424-8220 |
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| COBISS.SI-ID: | 245035523 |
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| DOI: | 10.3390/s25154564 |
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| Publication date in DKUM: | 13.08.2025 |
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| Views: | 171 |
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| Downloads: | 27 |
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| Metadata: |    |
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| Categories: | Misc.
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