Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/54806
Title: | Demystifying xAOSF/AOSR Framework in the Context of Digital Twin and Industry 4.0 |
Contributor(s): | Ud Din, Fareed (author) ; Paul, David (author) |
Publication Date: | 2023 |
DOI: | 10.1007/978-3-031-16075-2_44 |
Handle Link: | https://hdl.handle.net/1959.11/54806 |
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.
Publication Type: | Conference Publication |
Conference Details: | IntelliSys 2022: Intelligent Systems Conference 2022, Amsterdam, Netherlands, 1st - 2nd September, 2022 |
Source of Publication: | Intelligent Systems and Applications: Proceedings of the 2022 Intelligent Systems Conference (IntelliSys), v.3, p. 600-610 |
Publisher: | Springer |
Place of Publication: | Cham, Switzerland |
Fields of Research (FoR) 2020: | 460202 Autonomous agents and multiagent systems 460603 Cyberphysical systems and internet of things 460199 Applied computing not elsewhere classified |
Socio-Economic Objective (SEO) 2020: | 220499 Information systems, technologies and services not elsewhere classified 220403 Artificial intelligence 220402 Applied computing |
Peer Reviewed: | Yes |
HERDC Category Description: | E1 Refereed Scholarly Conference Publication |
WorldCat record: | https://www.worldcat.org/title/1343197110 |
Series Name: | Lecture Notes in Networks and Systems |
Series Number : | 544 |
Appears in Collections: | Conference Publication School of Science and Technology
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