Operation Tasks Assignment Optimization of Human–Robot Collaboration Manufacturing System Based on NSGA-II

In smart manufacturing domain, human–robot collaboration becomes a hot topic. The operation tasks assignment is the foundational issue of human–robot collaboration manufacturing system to balance the workload between operator and robot and increase cooperation efficiency. However, there is rarely study focusing on the different characteristics between operator and robot during operation tasks assignment optimization, including operator-only operation tasks, robot-only operation tasks, etc. Therefore, an operation tasks assignment optimization of human–robot collaboration manufacturing system based on NSGA-II is proposed in this chapter. Firstly, the classification of operation task considering the different features is analysis. Secondly, a multi-objective optimization model is constructed to optimize operation tasks assignment between operator and robot, involving minimum total operation cost, minimized maximum operator-robot operation time, and minimum idle time. The skills changeover pressure of operator is considered during optimization to bring human–robot cooperation into a more real scenario. Thirdly, nondominated sorting genetic algorithm-II (NSGA-II) is adopted to solve the proposed multi objective optimization problem. Finally, a case study is provided to demonstrate the effectiveness of the proposed method for human–robot collaboration manufacturing system.