AOSR 2.0: A Novel Approach and Thorough Validation of an Agent-Oriented Storage and Retrieval WMS Planner for SMEs, under Industry 4.0

Fareed Ud Din; David Paul; Joe Ryan; Frans Henskens; Mark Wallis

doi:10.3390/fi13060155

Future Internet (Jun 2021)

AOSR 2.0: A Novel Approach and Thorough Validation of an Agent-Oriented Storage and Retrieval WMS Planner for SMEs, under Industry 4.0

Fareed Ud Din,
David Paul,
Joe Ryan,
Frans Henskens,
Mark Wallis

Affiliations

Fareed Ud Din: The School of Science and Technology, The Faculty of Science, Agriculture, Business and Law, The University of New England, Armidale, NSW 2350, Australia
David Paul: The School of Science and Technology, The Faculty of Science, Agriculture, Business and Law, The University of New England, Armidale, NSW 2350, Australia
Joe Ryan: The School of Electrical Engineering and Computing, The College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW 2308, Australia
Frans Henskens: The School of Electrical Engineering and Computing, The College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW 2308, Australia
Mark Wallis: The School of Electrical Engineering and Computing, The College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW 2308, Australia

DOI: https://doi.org/10.3390/fi13060155
Journal volume & issue: Vol. 13, no. 6
p. 155

Abstract

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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.

Published in Future Internet

ISSN: 1999-5903 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Technology (General): Industrial engineering. Management engineering: Information technology
Website: http://www.mdpi.com/journal/futureinternet/

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