Flow time prediction for a single-server order picking workstation using aggregate process times

In this paper we propose a simulation modeling approach based on aggregate process times for the performance analysis of order picking workstations in automated warehouses. The aggregate process time distribution is calculated from tote arrival and departure times. We refer to the aggregate process time as the effective process time. An aggregate model uses the effective process time distributions as input to predict tote and order flow times. Results from experimental settings show that the aggregate model accurately predicts the mean and variability of tote and order flow times. As a case study, we develop an aggregate model to predict flow times for a real, operating warehouse. The resulting flow time predictions give satisfactory accuracy for both tote and order flow times. Meaningful insights are obtained for improving the performance of the warehouse.