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    An integrated ergonomic risk assessment framework based on fuzzy logic and IVSF-AHP for optimising ergonomic risks in a mixed-model assembly line
    (Taylor & Francis Ltd, 2024) Kulac, Secil; Kiraz, Alper
    This study proposes a systematic approach to address ergonomic factors, including physical, environmental and psychosocial aspects, in solving assembly line balancing problems. A three-stage framework is developed, starting with determining weights for ergonomic risk assessment methods using the interval-valued spherical fuzzy analytical hierarchy process. In the second stage, a fuzzy logic model for integrated ergonomic risk assessment is constructed based on these weights, and the integrated ergonomic risk score is determined. In the third stage, a mathematical model is formulated to minimise the cycle time while balancing the ergonomic risk level. A case study conducted in a wire harness factory validated the effectiveness of the proposed approach, showing a 10-11% improvement in line efficiency and a 12-25% enhancement in ergonomic risk balancing performance. These findings underscore the potential benefits of implementing this approach, which can significantly improve occupational safety and overall performance. This article presents a practical and systematic approach for enhancing ergonomic conditions in assembly lines. The proposed approach aims to balance the ergonomic risk level while minimising the cycle time by considering physical, environmental and psychosocial risk factors. A case study conducted in a wire harness factory demonstrated significant improvements in balancing ergonomic risks, highlighting the real-world applicability of this research.
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    Balancing and Scheduling U-Shaped Mixed-Model Assembly Lines with Human-Robot Collaboration Considering Ergonomic Risk
    (Springer Heidelberg, 2025) Kulac, Secil; Kiraz, Alper
    The integration of collaborative robots (cobots) in assembly systems has gained prominence as a means of enhancing efficiency and supporting human operators in task execution. This study examines the U-shaped mixed-model assembly line balancing problem with human-robot collaboration (U-shaped Ergo-MMALBP-HRC), incorporating ergonomic risk factors into the task allocation process. A mixed-integer linear programming (MILP) model is formulated to minimize cycle time while ensuring an equitable distribution of physical, environmental, and psychosocial ergonomic risks across workstations. Ergonomic risks are assessed using the Quick Exposure Check (QEC), Occupational Repetitive Actions Index (OCRA), Rapid Entire Body Assessment (REBA), and the Copenhagen Psychosocial Questionnaire (COPSOQ), providing a comprehensive evaluation of human and cobot task assignments. A case study conducted on a dishwasher assembly line demonstrates the efficacy of the proposed approach, achieving up to a 15% reduction in cycle time and a 38% in ergonomic risk scores. Computational experiments with varying levels of robot integration indicate that cobot deployment enhances operational efficiency while significantly mitigating ergonomic risks. Sensitivity analysis reveals that prioritizing ergonomic objectives further decreases risk scores, albeit with a minor increase in cycle time. The findings underscore the necessity of balancing productivity and worker well-being in collaborative assembly environments. This study provides a structured methodology for integrating ergonomic considerations into assembly line balancing, offering valuable insights for industries seeking to optimize efficiency while ensuring a safer and more sustainable work environment. The proposed framework contributes to the advancement of human-centric manufacturing by facilitating the effective collaboration between human workers and robotic systems.