International Journal on Science and Technology

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Unlocking Predictive Maintenance in Industry 4.0: A Digital Twin-IoT Perspective

Author(s) Tarandeep Kaur, Dr. Pankaj Deep Kaur
Country India
Abstract The convergence of Digital Twin (DT) technology and the Internet of Things (IoT) is reshaping predictive maintenance strategies in smart manufacturing environments. By enabling real-time synchronization between physical assets and their virtual counterparts, Digital Twins offer a powerful platform for condition monitoring, anomaly detection, and maintenance optimization. This paper explores the evolving role of DTs in enhancing the intelligence, efficiency, and reliability of predictive maintenance systems. The foundational principles, architectural components, and enabling technologies that underpin DT deployment in IoT-enabled manufacturing have been examined. The paper further presents real-world case studies illustrating tangible benefits across industries, while also addressing practical challenges such as data integration, model fidelity, and security. Finally, emerging research directions have been discussed to outline the trajectory of innovation in this rapidly advancing domain. This review aims to provide researchers and practitioners with a comprehensive understanding of how Digital Twins are driving a paradigm shift from reactive to proactive maintenance in the era of Industry 4.0 and beyond.
Keywords Digital Twin, Predictive Maintenance, Smart Manufacturing, Industrial IoT (IIoT), Industry 4.0.
Field Computer > Automation / Robotics
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-06-15
Cite This Unlocking Predictive Maintenance in Industry 4.0: A Digital Twin-IoT Perspective - Tarandeep Kaur, Dr. Pankaj Deep Kaur - IJSAT Volume 16, Issue 2, April-June 2025.
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