Kaur, Tarandeep and ., Jasmine and Sood, Sandeep (2025) Predictive Maintenance 4.0: Transforming Industry through IoT Innovations. International Journal of Innovative Science and Research Technology, 10 (4): 25apr1169. pp. 1914-1920. ISSN 2456-2165
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Abstract
Predictive maintenance (PdM) in Industrial Internet of Things (IIoT) is revolutionizing the way industries manage equipment health and operational efficiency. By leveraging real-time sensor data, machine learning algorithms, and advanced analytics, PdM enables proactive identification of potential failures before they occur. This approach minimizes unplanned downtime, optimizes maintenance schedules, and reduces operational costs. IIoT-based predictive maintenance integrates edge computing, cloud platforms, and artificial intelligence to process large-scale industrial data, facilitating intelligent decision-making. Key challenges include data security, scalability, and integration with legacy systems. This paper examines the architecture, methodologies, and benefits of predictive maintenance in Industrial Internet of Things (IIoT), highlighting its transformative impact on industrial automation and reliability.
Item Type: | Article |
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Subjects: | T Technology > T Technology (General) |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Engineering Sciences |
Depositing User: | Editor IJISRT Publication |
Date Deposited: | 02 May 2025 10:15 |
Last Modified: | 02 May 2025 10:15 |
URI: | https://eprint.ijisrt.org/id/eprint/672 |