Consideration of Skewness in Designing Robotic Compact Storage and Retrieval Systems

Abstract

A relatively new goods-to-person order picking system (robotic compact storage and retrieval system, RCS/RS) has been implemented within order fulfillment centers. In such a system, robots move in x- and y-dimensions on top of a grid-based storage area to retrieve bins from stacks by "digging" in z-dimension. To transport a requested bin to a port, robots (or a robot) remove(s) all blocking bins above the requested bin and place(s) them around neighboring stacks. Defining the throughput of an RCS/RS as the number of bins processed per unit time, we analyze the time required for bins to be removed from stacks, transported to ports, returned to stacks, and placed in stacks. In making a case for considering skewness among activity levels for bins, we develop closed-form expressions to calculate the expected operation time for the movement of bins, validate the closed-form expressions using simulation, and obtain the system configuration that maximizes throughput performance (or minimizes operation time for bins) based on current practice. Then, with an objective of having an optimal RCS/ RS design based on activity levels of bins, we show the significant impact on throughput when different skewness values for activity levels of the bins are incorporated into the design.