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DC Field | Value | Language |
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dc.contributor.author | Savković, Marija | - |
dc.contributor.author | Mijailovic, Nikola | - |
dc.contributor.author | Caiazzo, Carlo | - |
dc.contributor.author | Djapan, Marko | - |
dc.contributor.author | Vukicevic, Arso | - |
dc.date.accessioned | 2023-06-23T11:35:08Z | - |
dc.date.available | 2023-06-23T11:35:08Z | - |
dc.date.issued | 2022 | - |
dc.identifier.isbn | 978‐86‐6093‐112‐4 | en_US |
dc.identifier.uri | https://scidar.kg.ac.rs/handle/123456789/18500 | - |
dc.description.abstract | Workers who perform repetitive and tiring activities assembling parts and components into the final product at a traditional assembly workstation often suffer from musculoskeletal disorders (MSDs) and other occupational diseases associated with greater effort of tendons, muscles and nerves on the hands and wrists, and neck and lower back pain. These activities also reduce attention span and concentration, which causes mental fatigue and consequently, errors (which negatively affect the quality of the final product), and in some cases even injuries at work. Manual, monotonous and repetitive assembly tasks can be partially automated by the application of new technologies of Industry 4.0 which provides benefits in terms of minimizing the number of movements, inadequate body positions, bending, twisting, human errors, etc. The main focus of future development of the industry workstations is the human-centric approach and the introduction of a collaborative robot, which is in line with the goals of Industry 5.0.The aim of this paper is to present the results of advanced electro psychophysiology research (electroencephalography - EEG and electromyography - EMG) and the analysis of data collected in real-time by applying innovative technologies (EMG sensors and EEG caps) on a traditional workstation in order to establish the ergonomic risks to which assembly workers are exposed. In this way, it is possible to determine when muscle fatigue and/or reduced attention span and concentration of workers will be likely and which ergonomic risks, that can lead to occupational diseases and injuries at work, may occur. Theanalysis of the results of the experimental study shows that the assembly workers are exposed to physical and mental overload during the performance of assembly activities.Workers who perform repetitive and tiring activities assembling parts and components into the final product at a traditional assembly workstation often suffer from musculoskeletal disorders (MSDs) and other occupational diseases associated with greater effort of tendons, muscles and nerves on the hands and wrists, and neck and lower back pain. These activities also reduce attention span and concentration, which causes mental fatigue and consequently, errors (which negatively affect the quality of the final product), and in some cases even injuries at work. Manual, monotonous and repetitive assembly tasks can be partially automated by the application of new technologies of Industry 4.0 which provides benefits in terms of minimizing the number of movements, inadequate body positions, bending, twisting, human errors, etc. The main focus of future development of the industry workstations is the human-centric approach and the introduction of a collaborative robot, which is in line with the goals of Industry 5.0. The aim of this paper is to present the results of advanced electro psychophysiology research (electroencephalography - EEG and electromyography - EMG) and the analysis of data collected in real- time by applying innovative technologies (EMG sensors and EEG caps) on a traditional workstation in order to establish the ergonomic risks to which assembly workers are exposed. In this way, it is possible to determine when muscle fatigue and/or reduced attention span and concentration of workers will be likely and which ergonomic risks, that can lead to occupational diseases and injuries at work, may occur. The analysis of the results of the experimental study shows that the assembly workers are exposed to physical and mental overload during the performance of assembly activities. | en_US |
dc.language.iso | en | en_US |
dc.rights | info:eu-repo/semantics/openAccess | - |
dc.source | 19th international conference "Man and working environment" Occupational and Environmental Safety Engineering & management (OESEM) at Nis, Serbia | en_US |
dc.subject | assembly workstation | en_US |
dc.subject | EEG | en_US |
dc.subject | EMG | en_US |
dc.subject | Golden zone | en_US |
dc.subject | improvement of workplace safety | en_US |
dc.subject | Safety 4.0 | en_US |
dc.title | ADVANCED PHYSICAL ERGONOMICS AND NEUROERGONOMICS RESEARCH ON AN ASSEMBLY WORKSTATION | en_US |
dc.type | conferenceObject | en_US |
dc.description.version | Published | en_US |
dc.type.version | PublishedVersion | en_US |
Appears in Collections: | Faculty of Engineering, Kragujevac |
Files in This Item:
File | Description | Size | Format | |
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OESEM2022ConferenceProceedings-351-357-2-8.pdf | 533.02 kB | Adobe PDF | View/Open |
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