Open Access. Powered by Scholars. Published by Universities.®
Operations Research, Systems Engineering and Industrial Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Artificial Intelligence (AI) (1)
- Automated PPE Monitoring (1)
- Localized muscle fatigue (1)
- Longwall Coal Mining (1)
- Machine Learning (ML) (1)
-
- Manufacturing Workers (1)
- Methane Detection (1)
- Modeling (1)
- Multi-Nodal System (1)
- Musculoskeletal disorders (1)
- PPE Compliance (1)
- PPE Violations (1)
- Personal Protective Equipment (PPE) (1)
- Safety Professionals (1)
- Shoulder (1)
- Shoulder muscles (1)
- Stationary fatigue (1)
- Surface electromyography (1)
- Video Monitoring (1)
- Workplace Injuries and Illnesses (1)
Articles 1 - 4 of 4
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Improving The Health And Safety Of Manufacturing Workers By Detecting And Addressing Personal Protective Equipment (Ppe) Violations In Real-Time With The Use Of Automated Ppe Detection Technology, Joseph Olufemi Fasinu
Improving The Health And Safety Of Manufacturing Workers By Detecting And Addressing Personal Protective Equipment (Ppe) Violations In Real-Time With The Use Of Automated Ppe Detection Technology, Joseph Olufemi Fasinu
Graduate Theses, Dissertations, and Problem Reports
The Centers for Disease Control and Prevention (CDC) emphasized that Personal Protective Equipment (PPE) can significantly reduce the risk of occupational injuries and illnesses. However, improper use, failure to use, and other PPE-related violations can still result in injuries and fatalities. Eye and face protection violation has been one of the top 10 most frequently violated OSHA standards in fiscal years 2018, 2019, 2020, 2021 and 2022 consecutively. A common practice among safety professionals to ensure PPE compliance has been to physically inspect or monitor PPE usage among workers, which has been found to be unsustainable on a continuous real-time …
Improving Real-Time Methane Monitoring In Longwall Coal Mines Through System Response Characterization Of A Multi-Nodal Methane Detection Network, Brian Philip Cappellini
Improving Real-Time Methane Monitoring In Longwall Coal Mines Through System Response Characterization Of A Multi-Nodal Methane Detection Network, Brian Philip Cappellini
Graduate Theses, Dissertations, and Problem Reports
Machine automation and atmospheric monitoring are used by many industries to improve safety and productivity in the workplace. The underground Methane Watchdog System (MWS) is a multi-nodal network of sensors currently under development. The MWS aims to improve safety and productivity by introducing 10 compact sampling units designed to be easily integrated within the current roof support equipment of the mine. Each unit contains an array of sensors used to continuously monitor the environmental conditions which include methane concentration, temperature, pressure, and relative humidity. All MWS units report information back to a remote central processing hub (CPH) which collects nodal …
Analysis Of Factors Influencing The Stationarity Of Surface Electromyography Signals Measured In Non-Fatigued Shoulder Muscles, Hui Ci
Graduate Theses, Dissertations, and Problem Reports
A reduction in the % stationarity of surface electromyography (SEMG) signals with respect to the initial or fresh condition is used to predict localized muscle fatigue. However, factors other than muscle fatigue can also influence the stationarity of SEMG signals. This study was aimed at analyzing the effect of various work/task related factors on the stationarity of SEMG signals obtained from non-fatigued shoulder muscles. Twelve participants were recruited for data collection and each one performed 120 trials characterized by the combination of 2 shoulder angles (60° and 120°), 2 planes of exertions (sagittal and scapular), 3 force levels (0lb, 2.5lb, …
Implications Of Variability Of Electromyographic Measurements For Assessing Localized Muscle Fatigue, Hamad Nasser Alasim
Implications Of Variability Of Electromyographic Measurements For Assessing Localized Muscle Fatigue, Hamad Nasser Alasim
Graduate Theses, Dissertations, and Problem Reports
The impact of work-related musculoskeletal disorders (WMSDs) is enormous due to a combination of direct and indirect costs associated with healthcare, lost workdays and human suffering. Because of the established relationship between Localized Muscle Fatigue (LMF) development and WMSDs, and in order to reduce and/or prevent WMSDs in workplaces, different fatigue assessment methods have been developed. Surface Electromyography (SEMG) is a commonly used LMF assessment technique. The SEMG signals are typically analyzed in time and frequency domains to predict LMF based on a relative change with respect to initial, or under no-fatigue conditions. Quantifying such change, however, relies on the …