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Demystifying xAOSF/AOSR Framework in the Context of Digital Twin and Industry 4.0

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Intelligent Systems and Applications (IntelliSys 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 544))

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Abstract

With recent advances in the information revolution, Digital Twin, with its complementary technologies, especially Big Data, Internet of Thing (IoT), Artificial Intelligence (AI) and Multi-Agent Systems (MAS), is becoming the core of novel strategies to maintain sustainability in Industry 4.0 networks and smart manufacturing. Despite the potential advantages of Digital Twin, such as virtual accessibility, remote monitoring, and timely customisation, not all sorts of enterprises have the resources or capabilities to incorporate such an advanced system, particularly Small to Medium size Enterprises (SMEs), due to their volatile nature of Supply Chains (SC). In this context, a Cyber-Physical Systems (CPS)-based, Agent Oriented Smart Factory (xAOSF) framework presents an over-arching SC architecture, with an associated Agent Oriented Storage and Retrieval (AOSR) based warehouse management strategy to help bridge the gap between Industry 4.0 frameworks and SME-oriented setups. This paper presents an approach towards realising the concept of Digital Twin via the xAOSF/AOSR framework, utilising state-of-the-art semantic modelling and analytical industrial tools. An amalgamation of CPS and Big Data Analytics is important to establish an effective Digital Twin to improve system scalability, security, and efficiency. This paper brings attention to this critical intersection and highlights how the xAOSF/AOSR framework can be scaled to implement Digital Twin effectively, which helps in analysing the bottleneck and threshold-states in real-time, especially in manufacturing organisations, which can lead towards full autonomy in an Industry 4.0 environment.

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Authors and Affiliations

  1. The School of Science and Technology, The University of New England, Armidale, NSW, 2350, Australia

    Fareed Ud Din & David Paul

  2. The School of IT and Engineering, Melbourne Institute of Technology, Sydney, NSW, 2000, Australia

    Fareed Ud Din

Authors
  1. Fareed Ud Din
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  2. David Paul
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Correspondence to Fareed Ud Din .

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Editors and Affiliations

  1. Saga University, Saga, Japan

    Kohei Arai

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Ud Din, F., Paul, D. (2023). Demystifying xAOSF/AOSR Framework in the Context of Digital Twin and Industry 4.0. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2022. Lecture Notes in Networks and Systems, vol 544. Springer, Cham. https://doi.org/10.1007/978-3-031-16075-2_44

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