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December 24, 2025SensorsOpen Access

AI-Driven Digital Twins for Manufacturing: A Review Across Hierarchical Manufacturing System Levels

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Authors

PNPhat NguyenMKMinjung KimENElaina Nichols

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Overview

Literature survey reviews AI-driven digital twins enhancing efficiency in manufacturing, indicating future trends.

Key Points

  • This review aims to explore the integration of AI with digital twins in manufacturing and their transformative effects.
  • Literature survey outlining state-of-the-art AI-driven digital twin applications and challenges.
  • Case studies organized by application levels: machine, cell, shop floor, and enterprise.
  • Analysis of technologies used, including deep reinforcement learning and convolutional neural networks.
  • AI-driven digital twins improve efficiency, reliability, and responsiveness across manufacturing domains.
  • Key applications include predictive maintenance, process optimization, quality control, and dynamic scheduling.
  • Realization of intelligent digital twins is contingent on high-fidelity, real-time data and alignment with physical systems.

Cite This Study

Nguyen et al. (2025) studied this question.

synapsesocial.com/papers/6a1a91f57ff99bba0645e171https://doi.org/10.3390/s26010124
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