Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List

Full text release has been delayed at the author's request until December 31, 2029

ETD Abstract Container

Abstract Header

A Data-Driven Framework for the Implementation of Dynamic Automated Warehouse Systems

Zakaria, Yusuf Wumpini
http://orcid.org/0009-0006-0592-2639
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1724407926783142

Abstract Details

2024, Master of Science (MS), Ohio University, Industrial and Systems Engineering (Engineering and Technology).
In response to escalating inventory costs, dynamic purchasing needs, and the demand for rapid operations in the retail sector, both the warehousing and retail industries have accelerated their pace of innovation. Among these advances, the development of automated warehousing and storage systems stands out. However, despite widespread adoption, a comprehensive framework for effectively implementing these systems remains lacking. Hence, this study proposes a systematic approach that provides a foundational blueprint for harnessing vital information from historical sales data in the deployment of intelligent warehouse systems, incorporating a wide array of Automated Storage and Retrieval Systems (AS/RS) technologies. Specifically, it employs unsupervised machine learning for time series clustering to analyze historical sales data, while adapting and modifying the Recency, Frequency, Monetary (RFM) model to optimize the prioritized management of stock-keeping units (SKUs) in periodic segments.
Tao Yuan (Advisor)
Omar Alhawari (Committee Member)
Gary Weckman (Committee Member)
Ashley Metcalf (Committee Member)
241 p.
Engineering; Industrial Engineering; Management; Sustainability; Systems Design; Technology
Dynamic automated warehousing, autonomous warehousing systems, retail, sustainable warehousing, SKU batching, compact robotic storage and retrieval systems, historical sales record, data mining, machine learning, inventory management, SKU batching, segmentation, seasonality, capacity estimation, multi-level prioritization, Effective Bin Height.

Recommended Citations

Citations

  • Zakaria, Y. W. (2024). A Data-Driven Framework for the Implementation of Dynamic Automated Warehouse Systems [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1724407926783142

    APA Style (7th edition)

  • Zakaria, Yusuf. A Data-Driven Framework for the Implementation of Dynamic Automated Warehouse Systems. 2024. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1724407926783142.

    MLA Style (8th edition)

  • Zakaria, Yusuf. "A Data-Driven Framework for the Implementation of Dynamic Automated Warehouse Systems." Master's thesis, Ohio University, 2024. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1724407926783142

    Chicago Manual of Style (17th edition)

ohiou1724407926783142
© 2024, some rights reserved.Creative Commons License A Data-Driven Framework for the Implementation of Dynamic Automated Warehouse Systems by Yusuf Wumpini Zakaria is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Ohio University and OhioLINK.