Hybrid order picking: A simulation model of a joint manual and autonomous order picking system

Order picking is a key process in supply chains and a determinant of business success in many industries. Order picking is still performed manually by human operators in most companies; however, there are also increasingly more technologies available to automate order picking processes or to support human order pickers.One concept that has not attracted much research attention so far is hybrid order picking where autonomous robots and human order pickers work together in warehouses within a shared workspace for a joint target. This study presents a simulation model that considers various system characteristics and parameters of hybrid order picking systems, such as picker blocking, to evaluate the performance of such systems. Our results show that hybrid order picking is generally capable of improving pure manual or automated order picking operations in terms of throughput and total costs. Based on the simulation results, promising future research potentials are discussed.

Automated summary

Order picking is a critical process that affects business success in various industries. While manual operations are still common, there are also technologies available to automate or support order picking. This study examines hybrid order picking, where autonomous robots and human pickers work together, and evaluates its performance using a simulation model. The results show that hybrid order picking can improve throughput and reduce costs compared to pure manual or automated order picking. Future research potentials are discussed based on the simulation results.