| Summary: | The eCommerce industry utilizes fulfillment centers for product inventory, order
packaging and distribution. The fulfillment process at Amazon has been highly
automated within their Amazon Robotics (AR) Sortable facilities, mainly within the
inventory and order picking processes.
Although there has been significant progress in introducing technology into the
fulfillment processes, there are still several opportunities for further integration. This
work proposes the integration of automated guided vehicles (AGVs) in Amazon's
fulfillment centers (FCs) to improve process efficiency, labor utilization, and improve
employee safety.
Through utilizing the Six-Sigma DMAIC method, the process path of Transport Support
associate was selected as a focus because of the manual labor involved in their role often
moving empty material throughout the facility. The improved process path is proposed
with integration of AGVs and modeled using a process-based discrete-event simulation
framework.
The specific hardware and software requirements for an AGV to fit the proposed process
path results in a recommendation for a small packet AGV which utilizes LiDAR
scanners and vision-based navigation technology. The simulation results indicate that
the integration of AGVs in Inbound Stow process can increase individual throughput by
4-6% per shift per associate and reduces total idle time. The results demonstrate the
potential for AGVs to improve the productivity of FCs while contributing to reducing
potential work-related injuries. The work concludes that AGVs can improve FC
operations in the short and long term, with the potential for significant labor cost
savings.
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