Digital Twin Technology for Real-Time Monitoring in Smart Factories

The rapid advancement of Industry 4.0 has accelerated the adoption of Digital Twin (DT) technology in smart manufacturing. Digital twins are virtual replicas of physical assets, processes, or systems that allow real-time monitoring, simulation, and predictive analysis. This paper explores the integration of digital twins for real-time monitoring in smart factories, emphasizing the architecture, data flow, implementation frameworks, and benefits. Various enabling technologies, including IoT, cloud computing, AI, and edge computing, are discussed. Case studies highlight applications in predictive maintenance, production optimization, and quality control. The paper also addresses challenges such as data management, interoperability, and cybersecurity. Results indicate that digital twins significantly enhance operational efficiency, reduce downtime, and enable informed decision-making, marking a paradigm shift in smart manufacturing.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-13
DOI
https://doi.org/10.5281/zenodo.17600281
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
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article

Digital Twin Technology for Real-Time Monitoring in Smart Factories

Zenodo (CERN European Organization for Nuclear Research)
Digital Transformation in Industry
article

Digital Twin Technology for Real-Time Monitoring in Smart Factories

article en

Abstract

The rapid advancement of Industry 4.0 has accelerated the adoption of Digital Twin (DT) technology in smart manufacturing. Digital twins are virtual replicas of physical assets, processes, or systems that allow real-time monitoring, simulation, and predictive analysis. This paper explores the integration of digital twins for real-time monitoring in smart factories, emphasizing the architecture, data flow, implementation frameworks, and benefits. Various enabling technologies, including IoT, cloud computing, AI, and edge computing, are discussed. Case studies highlight applications in predictive maintenance, production optimization, and quality control. The paper also addresses challenges such as data management, interoperability, and cybersecurity. Results indicate that digital twins significantly enhance operational efficiency, reduce downtime, and enable informed decision-making, marking a paradigm shift in smart manufacturing.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 39%
Digital Transformation in Industry
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