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Title	Sustainable Manufacturing: Digital Twinning For A Mechanical Assembly Production Line
ID_Doc	53982
Authors	Hassan A.A.; Aggarwal G.
Year	2023
Published	Proceedings - 2023 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Autonomous and Trusted Vehicles, Scalable Computing and Communications, Digital Twin, Privacy Computing and Data Security, Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PCDS/Metaverse 2023
DOI	http://dx.doi.org/10.1109/SWC57546.2023.10449295
Abstract	There has been a rise in interest in the concept of the digital twin (DT) in both academia and industry in smart cities. The DT's implementation architecture generally consists of physical, virtual, and information-processing layers for a system. There are several theoretical frameworks presented and documented for DT implementation in the context of the manufacturing industry, but there is a lack of actual implementation studies published in the literature. The primary objective of this article is to show that a production unit that specialises in making manually assembled mechanical products can successfully adopt DT in practise. Tecnomatix Plant Simulation (P-sim) software was used to develop a simulation DT model. The DT then used for bottleneck identification to improve the efficiency of the production line. The DT proved to be a promising and evolving real-time optimisation tool for sustainable manufacturing. © 2023 IEEE.
Author Keywords	Bottleneck analysis; Digital twin; Optimisation; Smart Cities; Sustainable Manufacturing

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