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

Author

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  • 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
    These authors contributed equally to this work.)

  • 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
    These authors contributed equally to this work.)

  • Joe Ryan

    (The School of Electrical Engineering and Computing, The College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW 2308, Australia
    These authors contributed equally to this work.)

  • Frans Henskens

    (The School of Electrical Engineering and Computing, The College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW 2308, Australia
    These authors contributed equally to this work.)

  • Mark Wallis

    (The School of Electrical Engineering and Computing, The College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW 2308, Australia
    These authors contributed equally to this work.)

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.

Suggested Citation

  • Fareed Ud Din & David Paul & Joe Ryan & Frans Henskens & Mark Wallis, 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," Future Internet, MDPI, vol. 13(6), pages 1-16, June.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:6:p:155-:d:575064
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    References listed on IDEAS

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    1. Müller, Julian Marius & Buliga, Oana & Voigt, Kai-Ingo, 2018. "Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 2-17.
    2. Freeman, Chris & Louca, Francisco, 2002. "As Time Goes By: From the Industrial Revolutions to the Information Revolution," OUP Catalogue, Oxford University Press, number 9780199251056.
    3. Ling Li, 2007. "Supply Chain Management: Concepts, Techniques and Practices:Enhancing Value Through Collaboration," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6273, February.
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    1. Govindan, Kannan & Kannan, Devika & Jørgensen, Thomas Ballegård & Nielsen, Tim Straarup, 2022. "Supply Chain 4.0 performance measurement: A systematic literature review, framework development, and empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).

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