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| Open Access | APPLICATION OF IOT-BASED PREDICTIVE MAINTENANCE IN INDUSTRIAL MACHINERY: ENHANCING OPERATIONAL EFFICIENCY
Gregory Ruper ,Abstract
The advent of the Internet of Things (IoT) has revolutionized the approach to industrial machinery maintenance by enabling real-time monitoring, predictive analytics, and data-driven decision-making. This study explores the implementation of IoT-based predictive maintenance systems in industrial settings, analyzing their effectiveness in reducing downtime, optimizing resource allocation, and extending equipment lifespan. The findings indicate that integrating IoT technologies significantly enhances operational efficiency and reduces maintenance costs.
Keywords
IoT, predictive maintenance, industrial machinery, operational efficiency, real-time monitoring
References
Lee, J., Bagheri, B., & Kao, H.A. (2015). A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18-23.
Mobley, R.K. (2002). An Introduction to Predictive Maintenance. Butterworth-Heinemann.
Wan, J., Tang, S., Li, D., Li, C., & Vasilakos, A.V. (2016). A manufacturing big data solution for active preventive maintenance. IEEE Transactions on Industrial Informatics, 13(4), 2039-2047.
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This work is licensed under a Creative Commons Attribution 4.0 International License.