Issue |
SHS Web Conf.
Volume 189, 2024
The 2nd International Conference on Ergonomics Safety, and Health (ICESH) and the 7th Ergo-Camp (ICESH & Ergo-Camp 2023)
|
|
---|---|---|
Article Number | 01034 | |
Number of page(s) | 5 | |
DOI | https://doi.org/10.1051/shsconf/202418901034 | |
Published online | 09 April 2024 |
E-Airs: Interactive Ergonomic Monitoring System for Work Posture
1 Industrial Technology Faculty, Universitas Islam Indonesia, Sleman, Indonesia
2 Industrial Technology Faculty, Universitas Islam Indonesia, Sleman, Indonesia
3 Industrial Technology Faculty, Universitas Islam Indonesia, Sleman, Indonesia
4 Industrial Technology Faculty, Universitas Islam Indonesia, Sleman, Indonesia
* Corresponding author: irhamfth@gmail.com
Work posture and/or position of work is a crucial problem in work system. Unnatural posture will lead to discomfort when doing the task such as pain at part of body such that it will cause accident in the end. This accident will affect level of work performance of the worker so as the work productivity fails achieve a target determined. The failure mode, of course, results in a big loss for a company. This state should be avoided by use of the natural posture by worker in completing a job. However, many workers do not still understand what kind of a natural and unnatural work posture directly. So, this condition has high risk for being occurred the discomfort. Thus, it is important to develop a tool for helping them to identify a certain posture of work. Objective of this study is to design a monitoring system devices to capture and to determine an natural posture of the worker based on ergonomic principles. Rapid Upper Limb Assessment method is applied to determine a risk of work posture. Machine Learning concept is implemented to support in designing a system by also applying python programming language. Result of this study shows that monitoring system devices developed is usable in informing an unnatural posture of worker in completing a job. Thus, this result will beneficial for worker to improve work posture to be natural position so as discomfort can be prevented.
Key words: ergonomics / physical work posture / monitoring system / machine learning
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.