Programme: Bachelor of Business Administration (Honours) in Supply Chain Management
Project Title: Improving Storing and Picking Operations in Warehouse Using Pick Face Replenishment Strategy and ANFIS Model
Supervisor: Dr Cathy LAM
Students: LAI Wai Shan, LAM Tsz Wai, LI Wing Tung, LUI Yan Wing, WONG Lap
Under COVID-19, e-commerce becomes a hot business globally. More and more people are purchasing items through the internet and online shops. The increasing demand may bring immense pressure to the warehouse storage. Effective warehouse management and item storing become essential issues in the logistics industry. Due to the limited land problem, most of the warehouses in Hong Kong are using high-rise rack storage methods to stock more goods resulting in workers needing to spend more time picking the customer-ordered items through pallet trucks forklifts. Two issues may occur in this situation: the lack of resources to handle the high-volume demand for e-commerce orders and the lack of guidelines to manage storage space effectively. To increase the warehouse operation efficiency, a pick face replenishment strategy is studied in this project. The pick face strategy allows storage of bulk cargo on the upper deck of the rack to increase the storage capacity in the warehouse while keeping only a small quantity of stock-keeping units (SKUs) in the lower deck to allow operators to pick orders with minimal need of movement. By adopting the Adaptive Network-based Fuzzy Inference System (ANFIS), the picking quantity of the outbound orders can be predicted based on historical data. A case study was conducted in a freight forwarding company in Hong Kong to validate the model feasibility and the testing items focused on wine storage. The result shows that the optimal solution of the model could predict the majority of wines outbound quantities among the lowest errors successfully.