Integration of Artificial Intelligence and Digital Twins for Real-Time Control in Smart Manufacturing

Author(s)	Patil Chinmay, Sarang Kamalakar
Country	United States
Abstract	The rapid evolution of smart manufacturing necessitates innovative approaches for real-time monitoring, control, and optimization of production processes. Artificial Intelligence (AI) and Digital Twins (DT) have emerged as transformative technologies capable of enhancing operational efficiency, predictive maintenance, quality assurance, and adaptive process control. This paper presents a comprehensive framework for integrating AI with digital twin systems to enable real-time manufacturing control. The study reviews current methodologies, architectures, and use cases, highlights the key capabilities and benefits of AI-enabled digital twins, and discusses practical challenges and implementation considerations. Additionally, schematic representations of system architecture, data flow, and closed-loop control are provided to guide practitioners and researchers. The findings suggest that the integration of AI and digital twins significantly enhances manufacturing responsiveness, flexibility, and overall performance while offering a foundation for future manufacturing systems.
Keywords	Artificial Intelligence, Digital Twin, Real-Time Manufacturing Control, Smart Manufacturing, Predictive Maintenance, Process Optimization
Field	Engineering
Published In	Volume 16, Issue 4, October-December 2025
Published On	2025-11-04
DOI	https://doi.org/10.71097/IJSAT.v16.i4.9606
Short DOI	https://doi.org/hbcbj8

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International Journal on Science and Technology