Integrating Digital Human Modeling, Anthropometry, and Human Factors in Welding Workstation Redesign

Vollständiger Abstract

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Introduction: Musculoskeletal disorders (MSDs) among workers remain a concern in the context of occupational health. MSDs affect physical fitness and can lead to work disability. One industry at risk of MSDs is welding. Welding workstation designs that fail to consider body posture are a major factor contributing to the increase in MSDs complaints. One approach that can be used to design workstations is anthropometry-based Digital Human Modeling (DHM). This study aims to redesign informal welding sector workstations by integrating DHM, anthropometry, and human factors. Methods: A quantitative cross-sectional design (Stage 1) and descriptive analytical approach (Stage 2) were employed, involving 100 purposively selected informal welding workers in Bandung Raya. Data collection was carried out using the REBA instruments, NBM, and interviews. In Stage 1, the bivariate analysis used the chi-square test (χ²), and the multivariate analysis used logistic regression. Stage 2 data analysis was conducted using an AutoCAD-based 3D Model for DHM. The visualization results were verified using the REBA analysis. Results: The study indicate that human factors namely work duration (p = 0.006), risk perception (p = 0.008), work capacity (p = 0.003), work stress (p = 0.014), and work posture (p = 0.001) simultaneously influenced MSDs complaints among informal welding workers. In addition, anthropometric diversity formed the basis for redesigning workstations using anthropometric data P5, P50, and P95, reducing MSDs risk from very high risk (11) to low (3). Conclusion: Integrating digital human modeling, anthropometry, and human factors effectively supports the ergonomic redesign of informal welding workstations to reduce MSDs risks.