Product Mixture of SKU to Pod Assignment Policy in Robotic Mobile Fulfillment System Warehouse

Hanifha, Nafisha Herma (2023) Product Mixture of SKU to Pod Assignment Policy in Robotic Mobile Fulfillment System Warehouse. Masters thesis, Institut Teknologi Sepuluh Nopember.

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As the tremendous positive trend of e-commerce sales, the efficiency of warehouse operations needs to keep pace. Therefore, a part-to-picker warehouse named Robotic Mobile Fulfillment System Warehouse (RMFS) was explicitly designed e-commerce warehouse. This warehouse system can reduce the number of human operators and use robots, or in RMFS, called Automated Guided Vehicles (AGV), to carry the pods. There are several ways to increase the efficiency of the warehouse. This research will focus on the decision problem, SKU to the pod, or product assignment policy.
This research has three scenarios: SKU to pod using Random—baseline, Mixed Class, and Mixed Class Affinity policy. ABC classification and association rule using Weighted Support Count is applied to design the second and third scenarios. Then, using a simulation approach, those three scenarios are compared to find the best policy to increase warehouse efficiency. It is indicated by looking at each policy's number of pods transported. The smaller the number of pods, the higher pile-on the SKU to pod policy achieves.
As a result, the last scenario yields the best pile-on with an average number of pods transported of 6.59 pods per order. Meanwhile, the first and second scenarios' results are 7.06 and 6.90, respectively. From that numbers, it can be concluded that the pile-on of the last scenario is 7% and 5% higher than the other two scenarios, even though only 8% of SKUs form the association's rule. This result is verified by using one-way ANOVA.

Item Type: Thesis (Masters)
Uncontrolled Keywords: ABC Classification, Association Rule, Pile-On, RMFS, SKU to Pod Assignment Policy
Subjects: H Social Sciences > HF Commerce > HF5485 Warehouses--Management
T Technology > T Technology (General) > T57.62 Simulation
Divisions: Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26101-(S2) Master Thesis
Depositing User: Nafisha Herma Hanifha
Date Deposited: 05 Feb 2023 08:01
Last Modified: 07 Feb 2023 02:06

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