Search Results (58)

This study investigated the complex interfaces between knowledge, attitude and practice (KAP); biomechanical risks; and musculoskeletal disorders (MSDs) among heavy manual handling workers. A cross-sectional study surveyed 99 industrial manual lifting workers within manufacturing factories (mean age: 33.4 ± 7.7 years; mean job experience: 7.95 ± 6.5 years) using a validated online questionnaire assessing demographics, occupational conditions, biomechanical risk, lifting KAP, and MSD prevalence via the Extended Nordic Musculoskeletal Questionnaire. Associations with 12-month and active 7-day MSD prevalence were analyzed using multinomial logistic regression. The 12-month prevalence of MSDs was 56.6%, predominantly affecting the lower back (51.0%). The MSD group reported significantly higher biomechanical risks. Chi-square analysis revealed significant differences in safety practices (p = 0.025), particularly regarding pre-work stretching, load-weight assessment, and overhead lifting. Higher biomechanical risk was significantly associated with 12-month MSDs without 7-day pain (RRR = 1.54, 95% CI: 1.10 to 2.16, p = 0.012). Conversely, greater knowledge demonstrated a significant protective association against 12-month MSDs without 7-day pain (RRR = 0.74, 95% CI: 0.56 to 0.99, p = 0.045). Age-related vulnerability significantly increased active 7-day MSDs. MSD prevalence is driven by cumulative biomechanical hazards. Although knowledge is associated with lower long-term risk, a critical knowledge-to-practice gap exists. Interventions must prioritize workplace ergonomic risk reduction with age-tailored adjustments. These should be integrated with active, practice-based training to foster behavioral modification. Full article

Background/Objectives: The rapid growth of the companion animal industry has increased demand for professional pet grooming services; however, occupational health risks among pet groomers remain underexplored. This cross-sectional study investigated the prevalence of musculoskeletal disorders (MSDs), occupational burnout, and associated occupational and ergonomic factors and their interrelationships among pet grooming professionals. Methods: A total of 180 pet grooming professionals were recruited through geographically stratified convenience sampling across northern, central, and southern Taiwan. Data were collected using structured questionnaires assessing demographics, workload, ergonomic equipment, and working postures. MSD symptoms were evaluated using the Nordic Musculoskeletal Questionnaire, and occupational burnout was assessed using the Taiwan Ministry of Labor Burnout Assessment Scale. Descriptive statistics, one-way analysis of variance (ANOVA), Pearson’s correlation analysis, and multiple linear regression analysis were performed to identify factors associated with MSD severity and occupational burnout. Results: MSDs were highly prevalent, with 95% of participants reporting symptoms in at least one body region. The most affected regions were the right shoulder (71.7%), neck (70.6%), upper back (65.6%), and lower back (65.6%). Significant associated ergonomic factors included excessive bathing tub depth (≥46 cm), non-adjustable grooming tables, prolonged trunk flexion, and horse-stance postures. Higher workload intensity, including frequent bathing tasks and handling aggressive or large animals, was significantly associated with greater MSD severity (p < 0.05). Moderate-to-severe personal- and work-related burnout were identified in 43.3% and 37.2% of participants, respectively. MSD severity was positively correlated with personal-related burnout (r = 0.491, p < 0.001) and work-related burnout (r = 0.428, p < 0.001). Multiple linear regression analysis results indicated the MSD score was a significant predictor of both personal- and work-related burnout (p < 0.001). Conclusions: Pet grooming professionals experience a substantial burden of MSDs and occupational burnout associated with ergonomic strain and physically demanding work. Non-neutral postures and inadequately designed equipment were significantly associated with greater MSD severity. The close association between MSDs and burnout underscores the interrelationship between physical and psychological occupational health. Ergonomic workplace modifications and targeted occupational health interventions are necessary to improve worker well-being and industry sustainability. Full article

Background: Occupational health risk assessment in industrial enterprises has traditionally focused on physical, chemical, and ergonomic hazards, while psychosocial working conditions have often been assessed separately from routine occupational surveillance. The aim of this study was to examine whether integrating working conditions, the psychosocial work environment, occupational stress, and temporary disability indicators provide a more informative health risk profile in an industrial setting. Methods: An analytical observational study was conducted at a mining and processing enterprise in Kazakhstan. This study used three data sources: 5429 temporary disability records for 2020–2024, workplace assessments covering 188 job positions, and psychosocial survey data from 392 employees. Occupational stress was evaluated in annual PSS-25 screening waves conducted in 2023 (n = 133), 2024 (n = 133), and 2025 (n = 134). The author-developed psychosocial questionnaire showed acceptable internal consistency (Cronbach’s α = 0.82). Results: During the five-year period, 4971 eligible temporary disability episodes and 61,472 lost workdays were recorded. Psychosocial profiles were less favorable in production units than in administration, and mean PSS-25 values remained relatively stable across the years. The Integral Index of Working Conditions (Iwc) was positively associated with temporary disability indicators and occupational stress, whereas the Integral Health Index (Ihr) was inversely associated with psychosocial well-being. Conclusions: The findings suggest that occupational risk assessment remains incomplete when psychosocial factors are excluded or treated separately. Integrating hygienic, psychosocial, stress-related, and medical-statistical indicators may improve the prioritization of preventive measures and support healthier workplace management in industrial enterprises. Full article

Musculoskeletal disorders represent one of the most frequent occupational health problems in labour-intensive industries, particularly in fish processing, where repetitive tasks and prolonged postures are common. The objective was to determine the level of ergonomic risk by applying the Rapid Entire Body Assessment (REBA) method and based on the results, to formulate recommendations aimed at preventing musculoskeletal disorders and improving preventive management within the organization. The assessment included 30 workers distributed across three operational workstations, where the overall average REBA score was 8.60 ± 1.65 (range: 6–12), indicating a predominantly high level of ergonomic risk. In categorical terms, 60.0% of the workers were classified as high risk, 13.3% as very high risk, and 26.7% as medium risk, while none reached negligible or low risk levels. Significant differences were observed between workstations (Kruskal–Wallis H = 16.72, p < 0.001, ε² = 0.545), with the nobbing stage exhibiting the highest biomechanical load (mean REBA = 10.38 ± 1.06). It is concluded that ergonomic risk is structurally integrated into the operational design of the evaluated production system; therefore, ergonomic interventions focused on redesigning workstations, adjusting height, and configuring tasks are recommended to reduce biomechanical exposure and strengthen the organization’s preventive occupational safety framework. Full article

Ergonomics plays a significant role in the industrial workplaces by optimizing process efficiency while considering well-being of operators or workers. In the present case, an ergonomic study was conducted in an automotive manufacturing firm. There were discomfort- and fatigue-related complaints from workers engaged in the assembly and manual material handling operations. A thorough investigation was conducted using Body Parts Symptoms Survey (BPSS) and RULA, after discussing with the workers and observing the operations. Immediate ergonomics interventions and related issues have been identified and a new workstation with improved design was fabricated to minimize the ergonomic issues. Workers reported improvement in comfort level upon working on ergonomically sound workstations. Regular ergonomic assessments and continuous improvement with modification in workstations and processing techniques have been recommended to maintain a safe and productive workplace. Full article

Worm gears are used in various mechanical constructions, especially in heavy industrial plants, where they are exposed to high operating loads, large torques, and high temperatures, particularly in conditions where it is necessary for the input and output shafts to be at an angle of 90°. Regarding tribological optimization, the application of carbon nanotube in lubricants can lead to significant improvements in the performance characteristics of worm gears, both in terms of increasing efficiency and reducing the coefficient of friction and wear, as well as minimizing mechanical losses, noise, and vibrations. The objective of this study is for the research results, through the use of oil with varying percentages of carbon nanotube additives (CNTs), to contribute to the optimization of worm gears by improving efficiency, extending service life, and reducing vibrations—both within the gearbox itself and within the industrial facility where it is applied. The research methodology involved laboratory testing of a worm gear using lubricants with varying concentrations of carbon nanotube. During the experiment, measurements of efficiency, vibrations, and noise levels were conducted in order to determine the impact of these additives on the operational performance of the gear system. The main contribution of this research is reflected in the experimental confirmation that the use of lubricants with optimized concentrations of carbon nanotube significantly enhances the operational performance of worm gears by increasing efficiency and reducing vibrations and noise, thereby enabling tribological optimization that contributes to improved reliability, extended service life, and enhanced workplace ergonomics under demanding industrial conditions. Furthermore, experimental investigations have shown that the efficiency of the gearbox increases from an initial value of 0.42–0.65, which represents an increase of 54%, the vibrations of the worm gear decrease from an initial value of 5.83–2.56 mm/s², which represents an decrease of 56%, while the noise was reduced from 87.5 to 77.2 dB, which represents an decrease of 12% with the increasing percentage of carbon nanotube additives in the lubricant, up to a maximum value of 1%. However, beyond this experimentally determined threshold, a decrease in the efficiency of the tested worm gearbox, as well as an increase in noise and vibration levels was recorded. Full article

Ergonomic risk classification during manual lifting tasks is crucial for the prevention of workplace injuries. This study addresses the challenge of classifying lifting task risk levels (low, medium, and high risk, labeled as 0, 1, and 2) using multi-modal time-series data comprising raw facial landmarks and bio-signals (electrocardiography [ECG] and electrodermal activity [EDA]). Classifying such data presents inherent challenges due to multi-source information, temporal dynamics, and class imbalance. To overcome these challenges, this paper proposes a Multi-Adaptive Functional Neural Network (Multi-AdaFNN), a novel method that integrates functional data analysis with deep learning techniques. The proposed model introduces a novel adaptive basis layer composed of micro-networks tailored to each individual time-series feature, enabling end-to-end learning of discriminative temporal patterns directly from raw data. The Multi-AdaFNN approach was evaluated across five distinct dataset configurations: (1) facial landmarks only, (2) bio-signals only, (3) full fusion of all available features, (4) a reduced-dimensionality set of 12 selected facial landmark trajectories, and (5) the same reduced set combined with bio-signals. Performance was rigorously assessed using 100 independent stratified splits (70% training and 30% testing) and optimized via a weighted cross-entropy loss function to manage class imbalance effectively. The results demonstrated that the integrated approach, fusing facial landmarks and bio-signals, achieved the highest classification accuracy and robustness. Furthermore, the adaptive basis functions revealed specific phases within lifting tasks critical for risk prediction. These findings underscore the efficacy and transparency of the Multi-AdaFNN framework for multi-modal ergonomic risk assessment, highlighting its potential for real-time monitoring and proactive injury prevention in industrial environments. Full article

Human Factors and Ergonomics (HF/E) play an essential role in the development of sustainable manufacturing systems. By prioritizing worker wellbeing through the mitigation of occupational hazards and the enhancement of workplace health, HF/E contributes significantly to improved system performance. In accordance with the principles of Industry 5.0 and Society 5.0, which emphasize human-centered design and wellbeing, organizations that effectively integrate HF/E principles can achieve a competitive advantage on the market. Based on a globally recognized ranking system utilized by investors in making informed decisions, the study focuses on manufacturing companies ranked by their occupational health and safety (OHS) scores, a key criterion for assessing the social dimension of company performance. This research aims to identify and analyze top-ranked companies that explicitly highlight HF/E-related benefits within their public documents and sustainability reports. The paper investigates aspects related to the integration of AI and digital technologies to enhance safety and health in manufacturing systems, with a specific focus on human presence detection in hazardous zones, improvements in machines and equipment design, occupational risk assessments, and initiatives for enhancing worker wellbeing. The findings are expected to provide compelling evidence for companies to prioritize HF/E consideration during the design and redesign phases of sustainable manufacturing systems. The paper provides significant value to non-indexed companies by offering a dual approach for improving OHS performance, based on an empirical evaluation assessment method and practical strategies for effective OHS implementation in different manufacturing industries and countries. Full article

An important step toward automation and digitization in Industry 4.0 is the automobile sector’s use of smart manufacturing integrated systems (SMISs). Although this change increases productivity and competitiveness, it also creates new hazards for workplace safety. Key issues include ergonomic and cognitive strain from greater human–machine interactions, particularly with collaborative robots (cobots), and cybersecurity threats from the IIoT and cyber–physical systems. This paper looks at these hazards and stresses the value of safety precautions like predictive maintenance, traceability, and real-time monitoring. This case study investigates how the integration of smart manufacturing integrated systems (SMISs) and cyber–physical systems (CPSs) within Industry 4.0 frameworks enhances workplace safety in the automotive sector. Through a comprehensive case study of the final assembly line, this research explores how these technologies contribute to predictive maintenance, real-time monitoring, and human–machine collaboration, leading to significant reductions in ergonomic and cybersecurity risks. Full article

Aircraft mechanical maintenance involves high loads, repetitive movements, and awkward postures, significantly increasing the risk of work-related musculoskeletal disorders (WMSDs). Traditional static evaluation methods based on posture analysis fail to capture the complexity and dynamic nature of these tasks, limiting their applicability in maintenance settings. To address this limitation, this study introduces a novel quantitative WMSD risk assessment model that leverages 3D motion data collected through an optical motion capture system. The model evaluates dynamic human postures and employs an inverse trigonometric function algorithm to quantify the loading effects on working joints. Experimental validation was conducted through quasi-real-life scenarios to ensure the model’s reliability and applicability. The findings demonstrate that the proposed methodology provides both innovative and practical advantages, overcoming the constraints of conventional assessment techniques. Specifically, it enables precise quantification of physical task loads and enhances occupational injury risk assessments. The model is particularly valuable in physically demanding industries, such as aircraft maintenance, where accurate workload and fatigue monitoring are essential. By facilitating real-time ergonomic analysis, this approach allows managers to monitor worker health, optimize task schedules, and mitigate excessive fatigue and injury risks, ultimately improving both efficiency and workplace safety. Full article

Accident rates are notably high in industrial metalworking processes. This study aimed to identify and manage occupational health and safety (OHS) risks using the ELMERI observation method to minimize workplace accidents within a foundry operating in the metalworking sector. A quantitative case study was conducted, during which the foundry was monitored quarterly over the course of 1 year. For each of the processes considered—melting, molding, casting and thermal process—1800 observations were made, culminating in a total of 28,800 observations by the end of the year. The average safety index was calculated for each department, and the variability in OHS risks throughout the year was analyzed on a departmental basis. In calculating the safety index, seven key criteria from the ELMERI scale were emphasized, as follows: safety behavior, order and tidiness, machine safety, industrial hygiene, ergonomics, floor and access ways, and first aid and fire safety. Assessing the level of safety in these processes based on these criteria provides a strong foundation for effectively analyzing and managing OHS risks. This case study demonstrates that the periodic application of the ELMERI scale in foundries characterized by hazardous work environments is a valuable tool for managing fluctuating OHS risks. Full article

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. Full article

The fourth industrial revolution has transformed industrial ergonomics through the adoption of wearable technologies to enhance workplace safety and well-being. This study conducts a comprehensive scoping review, structured according to PRISMA guidelines, examining how wearable devices are revolutionizing ergonomic practices within Industry 4.0. After analyzing 1319 articles from major databases including SpringerLink, MDPI, Scopus, and IEEEXplore, 36 relevant studies were selected for detailed analysis. The review specifically focuses on how wearable technologies improve worker comfort and safety, promoting more productive work environments. The findings reveal that wearable devices have significantly impacted ergonomic conditions in industrial settings, with artificial intelligence integration showing the highest presence in analyzed applications. Over the past years, wearable technology implementations have demonstrated a 38% improvement in optimizing ergonomic conditions compared to traditional approaches. Full article

This paper is aimed at understanding the possibility of applying ergonomics in the reorganisation of the work environment with the aim to improve working conditions and to increase the productivity of the examined workplace in an industrial company. Due to constant changes in markets, industrial companies are forced to seek new methods and paradigms for planning and managing innovations in order to ensure their competitiveness. An essential part of this process is the emphasis on improving production processes, where various methods with different focuses can be used. These methods not only optimise work processes, but also allow companies to minimise the resources needed for production and increase overall productivity. Another useful tool for industrial enterprises can be ergonomic rationalisation. The importance of ergonomics in improving employee working conditions and production process efficiency has been the subject of studies promoting various concepts. This study focuses in particular on examining the possibility of extending the outputs obtained by the REFA method to outputs obtained through ergonomic analysis. To achieve the objectives of the paper, the case study method was chosen, given that it was necessary to apply the REFA method in combination with ergonomic rationalisation in the specific conditions of the industrial company for the possibility of identifying bottlenecks in the production process from the point of view of its productivity, efficiency, and workforce involvement. Based on the results, it was possible to propose measures to increase the efficiency of the production process while respecting the principles of ergonomics. As part of the solution, the author team concluded that the findings obtained by combining both methods do not show significant differences, but rather complement each other and provide a broader view of the issue under study. At the same time, it can be stated that the solution cannot be considered definitive due to possible dynamic changes in the industrial environment (changes in the composition of the workforce and the scale of production and evolving technology, e.g., AI). The subject of future research will be to adapt the applied combination of methods so that it is universally applicable to any industrial sector, with minimal required adjustments to meet the specifics of individual industries. Full article

Ergonomics is essential to improving workplace safety and efficiency by reducing the risks associated with physical tasks. This study presents a decision support system (DSS) aimed at enhancing production ergonomics in the construction sector through an analysis of high-risk postures. Using the Ovako Work Posture Analysis System (OWAS), the Revised NIOSH Lifting Equation (NIOSH equation) and Rapid Entire Body Assessment (REBA), the DSS identifies ergonomic risks by assessing body postures across common construction tasks. Three specific postures—X, Y and Z—were selected to represent typical construction activities, including lifting, squatting and repetitive tool use. Posture X, involving a forward-leaning stance with arms above the shoulders and a 25 kg load, was identified as critical, yielding the highest OWAS and NIOSH values, thus indicating an immediate need for corrective action to mitigate risks of musculoskeletal injuries. The DSS provides recommendations for workplace adjustments and posture improvements, demonstrating a robust framework that can be adapted to other postures and industries. Future developments may include application to other postures and sectors, as well as the use of artificial intelligence to support ongoing ergonomic assessments, offering a promising solution to enhance Occupational Safety and Health policies. Full article