A Digital Twin Framework for Industry 4.0 Enabling Next-Gen Manufacturing

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Raza, Mohsin, Kumar, Priyan Malarvizhi, Hung, Dang Viet, Davis, William, Nguyen, Huan and Trestian, Ramona (2020) A Digital Twin Framework for Industry 4.0 Enabling Next-Gen Manufacturing. In: 2020 9th International Conference on Industrial Technology and Management (ICITM), 2020-02-11 - 2020-02-13, Oxford, United Kingdom.

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Abstract

Digital twins offer a framework to support the ever-rising demands in the fast-paced industrial evolution. This technology not only adds to the reliability of industrial processes but also offers an insight in to long-term behaviors and pattern during the aging of the industrial equipment. In this paper, a digital twin framework is presented to replicate the processes of a real production line for product assembly. The proposed work implements a digital/graphical replica of Festo Cyber Physical Factory (CPF) for Industry 4.0 (I4.0). The implemented system allows to schedule orders and specify product configuration which embodies the actions of CPF in digital world. In addition, the paper also presents a viable framework to interlink the physical system with the digital instance to offer extended services and a pathway towards realization of fully functional digital twins.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	industry 4.0,cyber physical factory,digital twin,information systems and management,decision sciences (miscellaneous),management of technology and innovation,industrial and manufacturing engineering,strategy and management,management science and operations research ,/dk/atira/pure/subjectarea/asjc/1800/1802
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Cyber Intelligence and Networks
Related URLs:	http://www.scopus.com/inward/record.url?... https://ieeexplore.ieee.org/document/908...
Depositing User:	LivePure Connector
Date Deposited:	16 Jun 2025 10:30
Last Modified:	27 Jun 2025 00:10
URI:	https://ueaeprints.uea.ac.uk/id/eprint/99505
DOI:	10.1109/ICITM48982.2020.9080395

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