Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/145689
Title: Cloud-based cyber-physical robotic mobile fulfillment systems : a case study of collision avoidance
Authors: Keung, K. L.
Lee, C. K. M.
Ji, P.
Ng, Kam K. H.
Keywords: Engineering::Mechanical engineering
Issue Date: 2020
Source: Keung, K. L., Lee, C. K. M., Ji, P., & Ng, K. K. H. (2020). Cloud-based cyber-physical robotic mobile fulfillment systems : a case study of collision avoidance. IEEE Access, 8, 89318-89336. doi:10.1109/ACCESS.2020.2992475
Project: RCA-16/434
SCO-RP1
Journal: IEEE Access
Abstract: The rapid development and implementation of the Internet of Things (IoT) and Cyber-Physical Systems (CPS) in the engineering and manufacturing field have embraced a virtual identity to ensure nearly real-time adjustment. Warehouses are challenged to reassess its order fulfillment operations while simultaneously being provided with the opportunity to develop its own cloud-based CPS with the aid of IoT devices. Robotic Mobile Fulfillment System (RMFS) is a system controlling mobile robots, mobile storage rack, putaway and picking workstations, charging stations, and wireless communication infrastructure in the context of robotic-assisted warehouse. This paper addresses the value creation utilizing cloud-based CPS in RMFS. By providing an analysis of cloud services and IoT enhancement, theoretical concepts from the literatures are consolidated to solve the research que-stions on how RMFS offering better order fulfillment can gain benefits in terms of operational efficiency and system reliability. The paper also proposes a cloud-based CPS architecture, providing a comprehensive understanding on conflict avoidance strategy in the multi-layers multi-deeps warehouse layout. This research presents six conflict classifications in RMFS and provides a case study in the real-life context. Dock grid conflict is a new type of conflict appearing in multi-deeps RMFS. A scenario analysis with real customer orders is applied to present the collision detection and solution.
URI: https://hdl.handle.net/10356/145689
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2020.2992475
Rights: © 2020 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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