Yan Liu (Committee Member), Pratik Parikh (Advisor), Xinhui Zhang (Committee Member)
Master of Science in Engineering (MSEgr)
Order picking is arguably the most expensive operational activity for a distribution center (DC), constituting upwards of 50% of total operating costs. Designing an optimum order picking system (OPS) for a DC depends on several system parameters, such as aisle layout, storage system configuration, storage policy, picking method, and picking strategy. From an aisle layout standpoint, traditional DCs utilize either entirely wide or entirely narrow aisles in their picking systems. Wide aisles allow pickers to pass each other, reducing blocking and requiring fewer pickers. However, the space required for wide-aisle systems is high. Narrow aisles utilize less space than wide aisles, but are less efficient because of the high likelihood of congestion experienced by pickers. Space required for the picking area and labor required to perform picking are two significant costs for a DC's OPS. Traditional approaches focus on minimizing either space or minimizing labor rather than integrating the two objectives. We propose a variation to the traditional orthogonal aisle designs where both wide and narrow aisles are mixed within the system, anticipating that the mixed-width aisles may provide a compromise between space and labor. We develop analytical models for space and travel time for systems that employ randomized storage and traversal routing policies. We illustrate the use of these models by developing a cost-based optimization model to determine the optimal aisle configuration for specific OPSs. The objective of this model is to minimize the total system cost which was divided into two components, space and labor. Results indicate that mixed-aisles appear to be optimal for certain OPSs with randomized storage and traversal routing, with the resulting savings in total cost being as high as $48,000 over pure wide aisle systems. Additional benefits may be realized by using mixed-width aisles for other storage policies, such as class-based, and for semi-automated systems, both of which need further research.
Department or Program
Department of Biomedical, Industrial & Human Factors Engineering
Year Degree Awarded
Copyright 2011, all rights reserved. This open access ETD is published by Wright State University and OhioLINK.