Machine Learning-Enabled Digital Twin Framework for Predictive Intelligence in Smart Mechanical Systems

Guterres ; Juvinal Ximenes ; Haralayya ; Bhadrappa ; Rana ; Varinder Singh
TechComp Innovations: Journal of Computer Science... 📅 2026 Vol 3, No 1 🔗 DOI: 10.70063/techcompinnovations.v3i1.182
Abstract
This study investigates the integration of digital twin technology and machine learning for predictive analysis in smart mechanical systems. The research emphasizes the role of intelligent computational frameworks in improving industrial monitoring, predictive maintenance, and operational efficiency within Industry 4.0 environments. A qualitative content analysis approach was employed by reviewing scientific literature, industrial reports, and previous studies related to digital twins, artificial intelligence, and predictive analytics. The findings indicate that digital twin architectures supported by machine learning algorithms can significantly enhance real-time monitoring, fault prediction accuracy, and maintenance optimization. The integration of IoT devices, cloud computing, and intelligent analytics also improves industrial sustainability, reduces operational downtime, and supports data-driven decision-making processes. Furthermore, the study identifies several technological challenges, including cybersecurity risks, data integration complexity, and computational limitations. Overall, the proposed intelligent digital twin framework provides a promising approach for future industrial innovation and sustainable smart mechanical system management
Keywords
Digital Twin; Machine Learning; Predictive Maintenance; Smart Mechanical Systems; Industry 4.0
How to Cite

Guterres, et al. (2026). Machine Learning-Enabled Digital Twin Framework for Predictive Intelligence in Smart Mechanical Systems. TechComp Innovations: Journal of Computer Science and Technology, 3(1). https://doi.org/10.70063/techcompinnovations.v3i1.182

Guterres, Juvinal Ximenes; Haralayya, Bhadrappa; Rana, Varinder Singh, "Machine Learning-Enabled Digital Twin Framework for Predictive Intelligence in Smart Mechanical Systems," TechComp Innovations: Journal of Computer Science and Technology, vol. 3, no. 1, 2026.

Guterres, Juvinal Ximenes; Haralayya, Bhadrappa; Rana, Varinder Singh. "Machine Learning-Enabled Digital Twin Framework for Predictive Intelligence in Smart Mechanical Systems." TechComp Innovations: Journal of Computer Science and Technology, vol. 3, no. 1, 2026.

Guterres, Juvinal Ximenes; Haralayya, Bhadrappa; Rana, Varinder Singh. "Machine Learning-Enabled Digital Twin Framework for Predictive Intelligence in Smart Mechanical Systems." TechComp Innovations: Journal of Computer Science and Technology 3, no. 1 (2026).

Guterres, et al. (2026) 'Machine Learning-Enabled Digital Twin Framework for Predictive Intelligence in Smart Mechanical Systems', TechComp Innovations: Journal of Computer Science and Technology, 3(1). doi: 10.70063/techcompinnovations.v3i1.182.

Guterres, Juvinal Ximenes; Haralayya, Bhadrappa; Rana, Varinder Singh. Machine Learning-Enabled Digital Twin Framework for Predictive Intelligence in Smart Mechanical Systems. TechComp Innovations: Journal of Computer Science and Technology. 2026;3(1).

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