A Meta-heuristic Approach for Industry 5.0 Assembly Line Balancing and Scheduling with Human-Robot Collaboration

Throughout the development of Industry 5.0 towards a para-digm prioritizing human-centricity and sustainability, the potential of assembly lines with human-robot collaboration (HRC) is substantial. In HRC environments, human and robot operators share the workplace and can perform tasks simultaneously and collaboratively, amplifying work efficiency and operators’ welfare. This research investigates solutions to the assembly line balancing problem (ALBP) with HRC, where multiple human and robot operators work together. Using an adaptive simulated annealing (SA) framework for addressing ALBP with HRC, two innovative mechanisms are introduced-a new fitness value calculation method for roulette wheel selection and a pioneering heuristic approach. These mechanisms are devised to establish an innovative meta-heuristic approach based on SA for enhancing task allocation and resource management, improving productivity and operators’ well-being through strategic workload balancing between human and robot operators, and minimizing cycle times and the total number of operators required. The computational results using actual production data show that these mechanisms significantly enhance the solution quality, particularly in the large-size case study involving collaboration between multiple humans and robots in each workstation.