Cycle Time and Human Fatigue Minimization for Human-Robot Collaborative Assembly Cell

Human fatigue, which is one of the main causes of efficiency decline and health damage, cannot be overlooked in the task scheduling of HRC that is becoming one of the latest frontiers of manufacturing. In this letter, we proposed a task scheduling model that integrated micro-breaks within job-cycles to provide recovery from fatigue accumulation by taking advantage of the characteristic of HRC. Furthermore, an improved Chemical Reaction Optimization (CRO) algorithm is developed to solve the trade-off between cycle time and human fatigue. Greedy strategy is applied in the global and local search reaction of CRO to solve the multi-objective problem which includes two conflicting goals of cycle time and fatigue minimization. The proposed model and algorithm are demonstrated on assembly cases inspired by an industry application. The results from the case study suggest that the proposed model outperforms the comparison model. Finally, computational results have demonstrated that the superiority of the proposed algorithm is proved by comparing with genetic algorithm (GA), imperialist competitive algorithm (ICA), and standard CRO.

Automated summary

This study proposes a task scheduling model and algorithm for human-robot collaboration, which mitigates human fatigue accumulation by integrating micro-breaks and balances cycle time and fatigue minimization. The experimental results demonstrate the effectiveness of the proposed model and algorithm in assembly tasks compared to the comparison model.