An ergonomic zone polyhedral representation-based mathematical program to prevent work-Related musculoskeletal risks

The human-centric approach of Industry 5.0 underscores the integration of advanced technologies and information systems to enhance worker well-being, productivity, and safety. Significant progress has been made in automation and digitalization; however, the high prevalence of work-related musculoskeletal disorders (WRMSDs) remains a critical challenge, translating into a significant socioeconomic burden. Nevertheless, industrial practice still predominantly relies on observational ergonomic assessment methods and reactive ergonomic strategies, creating an urgent need for flexible, proactive, individualized, and easy-to-implement risk mitigation approaches. This paper addresses this gap by proposing an intelligent decision-support system based on a multi-objective optimization model that integrates heterogeneous information - workers’ anthropometric measures, task requirements, and personal habits - within an expert-system architecture for industrial applications. The method relies on a convex integer program that can be embedded in machine controllers to compute the relative position between the product and the operator, minimizing ergonomic risks. Key innovations include the adoption of ergonomic principles without complex inverse kinematics, the explicit involvement of workers to account for their preferences, and the joint consideration of tasks involving both visual and physical interaction with the product. Experimental validation was conducted in a virtual environment simulating typical manufacturing scenarios, with diverse users and products. Results showed significant reductions in ergonomic risks with optimized positions, especially for smaller products, whereas larger ones posed challenges due to their size and task distribution. Statistical analyses validated these findings, highlighting the model’s potential to reduce the REBA (Rapid Entire Body Assessment) risk index and enhance operational efficiency. Overall, the proposed system provides actionable set-points for workstation configuration and practical guidance for implementation, thus supporting human-centric manufacturing in Industry 5.0.