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ABSTRACT. This paper provides a systematic literature review of studies investigating digital twin-enabled industrial Internet of Things, synthetic data and predictive maintenance tools, virtual simulation and computer vision algorithms, and cloud-based cognitive and machine intelligence technologies. Throughout February 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “smart shop floor autonomous manufacturing in the industrial metaverse” + “robotic navigation and digital twin-based cyber-physical production systems,” “virtual 3D scene simulation and deep learning-assisted smart process management tools,” and “immersive geospatial data visualization and distributed artificial intelligence technologies.” As research published in 2022 and 2023 was inspected, only 166 articles satisfied the eligibility criteria, and 20 mainly empirical sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: ASReview Lab, CASP, METAGEAR package for R, PICO Portal, SWIFT-Active Screener, and Systematic Review Accelerator.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: robotic navigation; digital twin; cyber-physical production; artificial intelligence; autonomous manufacturing; industrial metaverse

How to cite: Abdullah, F., Sabie, O.-M., and Bogdan, A. (2023). “Robotic Navigation and Digital Twin-based Cyber-Physical Production Systems, Virtual 3D Scene Simulation and Deep Learning-assisted Smart Process Management Tools, and Immersive Geospatial Data Visualization and Distributed Artificial Intelligence Technologies in Smart Shop Floor Autonomous Manufacturing in the Industrial Metaverse,” Journal of Self-Governance and Management Economics 11(3): 70–84. doi: 10.22381/jsme11320233.

Received 24 March 2023 • Received in revised form 22 September 2023
Accepted 25 September 2023 • Available online 30 September 2023

1Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia, This email address is being protected from spambots. You need JavaScript enabled to view it..
2Bucharest University of Economic Studies, Bucharest, Romania, This email address is being protected from spambots. You need JavaScript enabled to view it.; This email address is being protected from spambots. You need JavaScript enabled to view it. (corresponding author).

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