The integration of collaborative robots, also known as cobots, in assembly processes has the potential to significantly improve both productivity and ergonomic safety, especially when handling large and bulky parts stored in remote locations. This study presents a novel approach to task allocation in a shared human–robot collaborative environment, focusing on large-parts picking typically located behind the operators. A mixed-integer linear programming (MILP) model is developed to minimize the makespan while optimally distributing tasks between two human operators and one shared cobot. The model explicitly assigns the cobot to handle the heaviest and bulkiest components. Post-optimization, ergonomic evaluation is conducted using the Rapid Entire Body Assessment (REBA) index, comparing scenarios without and with the cobot. The results demonstrate that introducing the cobot increases productivity and lowers the average REBA score, highlighting both efficiency and ergonomic gains. This study contributes to the field of Industry 5.0 by addressing the dual objective of improving productivity while prioritizing human well-being.
Granata et al. (Thu,) studied this question.