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IoT and Predictive Maintenance in Industrial Engineering: A Data-Driven Approach

Published: November 7, 2025 | arXiv ID: 2511.04923v1

By: P. Vijaya Bharati , J. S. V. Siva Kumar , Sathish K Anumula and more

Potential Business Impact:

Fixes machines before they break down.

Business Areas:
Predictive Analytics Artificial Intelligence, Data and Analytics, Software

Fourth Industrial Revolution has brought in a new era of smart manufacturing, wherein, application of Internet of Things , and data-driven methodologies is revolutionizing the conventional maintenance. With the help of real-time data from the IoT and machine learning algorithms, predictive maintenance allows industrial systems to predict failures and optimize machines life. This paper presents the synergy between the Internet of Things and predictive maintenance in industrial engineering with an emphasis on the technologies, methodologies, as well as data analytics techniques, that constitute the integration. A systematic collection, processing, and predictive modeling of data is discussed. The outcomes emphasize greater operational efficiency, decreased downtime, and cost-saving, which makes a good argument as to why predictive maintenance should be implemented in contemporary industries.

Page Count
9 pages

Category
Electrical Engineering and Systems Science:
Systems and Control