Parallel Assembly Line Balancing With Human Robot Collaboration

Human-robot collaboration (HRC) will indeed transform production paradigms in intelligent manufacturing. The aim of this research is to investigate the application and merits of HRC in parallel conveyors and to identify how it may contribute to enhanced productivity, resource use, and operational flexibility. The main issue being addressed is incorporating human-robot collaboration features into the Parallel Assembly Line Balancing Problem (PALBP), which is now referred to as PALBP-HRC. These collaboration modes allow for both parallel and cooperative human-unattended robot operation while enabling the optimization of tasks allocation.For some problems of that hybrid nature associated with PALBP-HRC, a genetic algorithm is proposed to minimize cycle time along with optimal task assignment, keeping in mind the different complex restrictions such as precedence relations, zoning restrictions, and human-robot compatibility for tasks. GA also seeks to maximize benefits deriving from the distinct strengths of humans and robots by using a proper form of task allocation.The experiments show how the proposed GA has demonstrated its capability in solving PALBP-HRC. The cycle time has been significantly reduced with most improved task assignment and flexibility in operations. Thus, the results indicate that human-robot collaboration has been seamlessly included in a parallel assembly line to emphasize not only productivity enhancement but also adaptability in dynamic production environments.