Digital Approaches for Mitigating Occupational Vibration Exposure in the Context of Industry 4.0
Whole-body vibration (WBV) exposure presents occupational health risks across multiple industries, particularly in tasks involving heavy machinery and prolonged seating. This study examines WBV risk factors, intervention strategies, and the potential for digital monitoring solutions to strengthen wo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Safety |
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| Online Access: | https://www.mdpi.com/2313-576X/11/2/31 |
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| author | Doru Costin Darabont Lucian-Ionel Cioca Daniel Onut Badea |
| author_facet | Doru Costin Darabont Lucian-Ionel Cioca Daniel Onut Badea |
| author_sort | Doru Costin Darabont |
| collection | DOAJ |
| description | Whole-body vibration (WBV) exposure presents occupational health risks across multiple industries, particularly in tasks involving heavy machinery and prolonged seating. This study examines WBV risk factors, intervention strategies, and the potential for digital monitoring solutions to strengthen workplace safety. A sector-wide analysis assessed vibration exposure levels, worker-reported discomfort, and the effectiveness of the existing control measures. The study introduces a conceptual framework for a mobile application designed to integrate real-time exposure tracking, structured worker feedback, and predictive risk assessment. The findings confirm that WBV exposure varies across industries, with the energy and maritime logistics sectors showing the highest levels of noncompliance. A tiered intervention strategy, classified by impact and effort, provides a structured method for prioritizing risk reduction measures. Immediate actions, such as real-time monitoring and preventive maintenance, require minimal effort but provide high-impact benefits, while long-term strategies, including ergonomic workstation redesign, demand greater investment but contribute to sustained exposure reduction. The proposed framework offers a scalable, data-driven approach to WBV risk management, transitioning workplace safety from compliance-based monitoring to proactive prevention. Future research should explore implementation feasibility, worker adoption, and the integration of AI-driven safety recommendations to support continuous improvements in workplace safety strategies. |
| format | Article |
| id | doaj-art-5c66433d447c45e79b5df50f4f296cbc |
| institution | Kabale University |
| issn | 2313-576X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Safety |
| spelling | doaj-art-5c66433d447c45e79b5df50f4f296cbc2025-08-20T03:27:22ZengMDPI AGSafety2313-576X2025-04-011123110.3390/safety11020031Digital Approaches for Mitigating Occupational Vibration Exposure in the Context of Industry 4.0Doru Costin Darabont0Lucian-Ionel Cioca1Daniel Onut Badea2National Research and Development Institute on Occupational Safety—I.N.C.D.P.M. “Alexandru Darabont”, 35A Ghencea Boulevard., Sector 6, 061692 Bucharest, RomaniaIndustrial Engineering and Management Department, Faculty of Engineering, Lucian Blaga University of Sibiu, 550024 Sibiu, RomaniaNational Research and Development Institute on Occupational Safety—I.N.C.D.P.M. “Alexandru Darabont”, 35A Ghencea Boulevard., Sector 6, 061692 Bucharest, RomaniaWhole-body vibration (WBV) exposure presents occupational health risks across multiple industries, particularly in tasks involving heavy machinery and prolonged seating. This study examines WBV risk factors, intervention strategies, and the potential for digital monitoring solutions to strengthen workplace safety. A sector-wide analysis assessed vibration exposure levels, worker-reported discomfort, and the effectiveness of the existing control measures. The study introduces a conceptual framework for a mobile application designed to integrate real-time exposure tracking, structured worker feedback, and predictive risk assessment. The findings confirm that WBV exposure varies across industries, with the energy and maritime logistics sectors showing the highest levels of noncompliance. A tiered intervention strategy, classified by impact and effort, provides a structured method for prioritizing risk reduction measures. Immediate actions, such as real-time monitoring and preventive maintenance, require minimal effort but provide high-impact benefits, while long-term strategies, including ergonomic workstation redesign, demand greater investment but contribute to sustained exposure reduction. The proposed framework offers a scalable, data-driven approach to WBV risk management, transitioning workplace safety from compliance-based monitoring to proactive prevention. Future research should explore implementation feasibility, worker adoption, and the integration of AI-driven safety recommendations to support continuous improvements in workplace safety strategies.https://www.mdpi.com/2313-576X/11/2/31occupational vibrationrisk assessmentworkplace exposuresensor-based monitoringpredictive risk analysis |
| spellingShingle | Doru Costin Darabont Lucian-Ionel Cioca Daniel Onut Badea Digital Approaches for Mitigating Occupational Vibration Exposure in the Context of Industry 4.0 Safety occupational vibration risk assessment workplace exposure sensor-based monitoring predictive risk analysis |
| title | Digital Approaches for Mitigating Occupational Vibration Exposure in the Context of Industry 4.0 |
| title_full | Digital Approaches for Mitigating Occupational Vibration Exposure in the Context of Industry 4.0 |
| title_fullStr | Digital Approaches for Mitigating Occupational Vibration Exposure in the Context of Industry 4.0 |
| title_full_unstemmed | Digital Approaches for Mitigating Occupational Vibration Exposure in the Context of Industry 4.0 |
| title_short | Digital Approaches for Mitigating Occupational Vibration Exposure in the Context of Industry 4.0 |
| title_sort | digital approaches for mitigating occupational vibration exposure in the context of industry 4 0 |
| topic | occupational vibration risk assessment workplace exposure sensor-based monitoring predictive risk analysis |
| url | https://www.mdpi.com/2313-576X/11/2/31 |
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