Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/31720
Title: AOSR 2.0: A Novel Approach and Thorough Validation of an Agent-Oriented Storage and Retrieval WMS Planner for SMEs, under Industry 4.0
Contributor(s): Ud Din, Fareed  (author)orcid ; Paul, David  (author)orcid ; Ryan, Joe (author); Henskens, Frans (author); Wallis, Mark (author)
Publication Date: 2021-06
Early Online Version: 2021-06-15
Open Access: Yes
DOI: 10.3390/fi13060155
Handle Link: https://hdl.handle.net/1959.11/31720
Abstract: 

The Fourth Industrial Revolution (Industry 4.0), with the help of cyber-physical systems (CPS), the Internet of Things (IoT), and Artificial Intelligence (AI), is transforming the way industrial setups are designed. Recent literature has provided insight about large firms gaining benefits from Industry 4.0, but many of these benefits do not translate to SMEs. The agent-oriented smart factory (AOSF) framework provides a solution to help bridge the gap between Industry 4.0 frameworks and SME-oriented setups by providing a general and high-level supply chain (SC) framework and an associated agent-oriented storage and retrieval (AOSR)-based warehouse management strategy. This paper presents the extended heuristics of the AOSR algorithm and details how it improves the performance efficiency in an SME-oriented warehouse. A detailed discussion on the thorough validation via scenario-based experimentation and test cases explain how AOSR yielded 60–148% improved performance metrics in certain key areas of a warehouse.

Publication Type: Journal Article
Source of Publication: Future Internet, 13(6), p. 1-16
Publisher: MDPI AG
Place of Publication: Switzerland
ISSN: 1999-5903
Fields of Research (FoR) 2020: 460202 Autonomous agents and multiagent systems
460106 Spatial data and applications
Socio-Economic Objective (SEO) 2020: 220402 Applied computing
220403 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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