IoT-Driven Predictive Maintenance for Industrial Electronic Systems: Enhancing Reliability and Reducing Downtime
Author(s): Raghav P. Thakur¹, Amit K. Yadav², Poonam C. Bansal³
Affiliation: 1,2,3Department of Electrical and Electronics Engineering, Himalayan Institute of Technology, Dehradun, Uttarakhand, India
Page No: 9-13-
Volume issue & Publishing Year: Volume 2 Issue 2,Feb-2025
Journal: International Journal of Modern Engineering and Management | IJMEM
ISSN NO: 3048-8230
DOI:
Abstract:
The integration of Internet of Things (IoT) in industrial electronic systems has transformed traditional maintenance strategies by enabling real-time monitoring, predictive analytics, and early fault detection. Predictive maintenance (PdM) supported by IoT sensors and data-driven algorithms offers a proactive approach to minimize unexpected failures, enhance system reliability, and reduce downtime in critical industrial processes. This study explores the architecture, implementation challenges, and benefits of IoT-based predictive maintenance in industrial electronics, focusing on sensor networks, data acquisition frameworks, and machine learning-based fault prediction. The research emphasizes the economic and operational impact of this approach and provides insights into future directions for smart industrial maintenance.
Keywords:
IoT, Predictive Maintenance, Industrial Electronics, Fault Detection, Reliability Optimization, Downtime Reduction
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