Project Team
Students
ChaoJue Zhang
Industrial Engineering
Penn State Behrend
Faculty Mentors
Omar Ashour
Penn State Behrend
Engineering
Eunhye Song
Penn State University Park
Industrial and Manufacturing Engineering
Project
Project Video
Project Abstract
This work focuses on improving order picking in warehouses. Order picking is the process of items retrieval from warehouse locations to fulfill customer orders. Warehouse management is important for businesses of any size. Knowing when to pick certain items, what amount to pick, and how to pick items can easily become complex decisions. Group Technology (GT) is a management theory by which the items data is analyzed to group items based on their similarities to each other. This approach has been proven to improve systems efficiency and productivity. In this work, a dynamic GT-based classification method is used to sort items based on their similarity. With this method, items are grouped as the orders arrive based on critical characteristics, e.g., item type, priority, and order frequency. This method will potentially minimize warehouse management costs and increase efficiency. A case study is implemented where a simulation study is used to compare the current practice with the proposed method.
Evaluate this Project
Use this form link to provide feedback to the presenters, and add your project evaluation for award(s) consideration.