Evaluation of human workload in a hybrid order picking system

Abstract

Order picking is a labor-intensive and costly process in supply chains, which is performed manually in most cases. Recently, picking robots have been developed which are capable of working together with human pickers in a shared working space. Such hybrid order picking system can ease human pickers’ workload and provide ergonomic improvements, because it partially automates the order picking process. We propose a simulation model to measure the energy expenditure of human pickers who work with the support of picking robots. The hybrid order picking system is evaluated based on its operational costs, efficiency, and ergonomic characteristics. Preliminary results presented in this study show that there are assignment rules for items to workers and robots that reduce human energy expenditure and costs per pick, as well as maintain average throughput time at a certain level. The aim of this preliminary study is to closely analyze the hybrid order picking system, evaluate managerial implications, and detect research opportunities for future works.