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Implementing Association Rules for Rack Replenishment in Kiva Systems

  • Purpose: Kiva robots system is considered as the 8th generation of warehousing picking system by Amazon. The system utilizes Automated Guided Vehicles to pick up and carry racks to picking stations to realize goods-to-man picking operations and can save 2/3 of manpower in picking operations. One of the ways for efficient operations of the system is to have right assortment of goods on racks to reduce the number of rack move completing customer orders. This research looks into correlations of customer orders to study the goods allocation plan on racks that could effectively reduce the number of rack moves for shorter order completion time and less manpower used in picking operations. Design/methodology/approach: This study aims at finding goods allocation plans considering correlations of customer orders for efficient picking operations. In calculating the correlation between and among orders, we used a priori association rules to compute the support and confidence of order items. We generate three batches of 10,000 orders with VBA, each referring to an EC company. We later implemented ABC classification and association rules to conduct different levels of order analysis. Considering put-to-light picking systems as in the Kiva systems, the correlations of order items and customer orders were computed with R programming software. The performance measure is the number of times to move racks to complete the customer orders. Different replenishment strategies for goods allocation on racks using product correlation values and order quantity ratios were implemented with simulation to find the optimal replenishment strategy. Findings: We analyzed nine replenishment strategies and found that the best strategy among the nine could reduce the number of rack moves by 77.9% when compared to a randomly allocated strategy. Value/Originality: Despite the growing application of Kiva systems in warehousing operations, there is only few studies look into operational improvement problems. This paper lies its originality in using association rules for rack replenishment strategy for efficient picking operations. The result show tremendous improvement in performance measures, which demonstrates the value of the paper.

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Metadaten
Author:Kune-muh Tsai, Mei-hui Chen, Peik Bremer, Ting-Yu Chen
Persistent identifier:https://isl21.org/wp-content/uploads/2020/04/Full-paper-20_07_2019-Final-V2.pdf
Parent Title (English):Proceedings of the 24th International Symposium on Logistics - Supply Chain Networks vs Platforms: Innovations, Challenges and Opportunities, Würzburg
Document Type:Conference Proceeding
Language:English
Year of publication:2019
Release Date:2023/08/28
First Page:555
Last Page:559
Institutes and faculty:Fakultäten / Fakultät Wirtschaftsingenieurwesen
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