Ergonomic Risk Assessment of Construction Workers and Projects Based on Fuzzy Bayesian Network and D-S Evidence Theory

Work-related musculoskeletal disorders (WMSDs) are the main causes of physical diseases of workers in the construction industry. The occurrence of WMSDs can result in project delays, cost overruns, workers' worsened health status, and even unanticipated safety risks. Ergonomic rules and instrument-based methods have enabled automatic postural ergonomic evaluation and intervention, while a research gap lies in how to consider more comprehensive personalized factors and how to integrate individual risks for project-level risk control. This study developed a two-hierarchy method to assess the ergonomic risk for both individual workers and the entire project. To alleviate the problems of data insufficiency and imprecision in real-life construction projects, experts' evaluations were incorporated with existing instrument-based methods. A methodology combining fuzzy theory, D-S evidence theory, and Bayesian network was employed to deal with fuzziness, uncertainty, and conflicting judgments, and to provide a probabilistic assessment. To measure the potential impact on projects from the perspectives both of cost and productivity, this study also developed a practical framework for project integration. A real-life case study was conducted to validate the approach and demonstrated its applicability. The results of sensitivity analysis indicate that previous WMSD records, age, working posture, and working intensity are the top critical risk factors that have the most significant impact on individuals' WMSD risk status. This study provides deeper insights into WMSD risk assessment, which can facilitate personalized instructions and intervention for individual WMSD risk control, and support managerial initiatives and decisions to mitigate the negative effects on construction projects.