Explainable Machine Learning in Industrial IoT for Predictive Maintenance of Machine Condition Monitoring
Keywords:
Keywords: Predictive Maintenance, Internet of Things (IoT), Sensor Data, Anomaly Detection, Failure Prediction.Abstract
Predictive maintenance in industrial settings is crucial for optimizing operational efficiency, reducingdowntime, and lowering maintenance costs. Traditional maintenance methods, such as reactive andpreventive maintenance, are often inefficient and costly, either leading to unplanned downtimes orunnecessary maintenance activities
References
W. Lee, S. Kim, and Y. Kim, "Predictive Maintenance of Machine Tool Systems Using Artificial Intelligence Techniques," Journal of Manufacturing Science and Engineering, vol. 140, no. 10, 2018.
T. Zonta, C. Magro, and R. Mazzanti, "A Systematic Literature Review of Predictive Maintenance in Industry 4.0," Procedia CIRP, vol. 81, pp. 688-693, 2019.
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Published
2025-01-08
How to Cite
Gudimilla Pallavi, Thota Srishanth, Mohd Raheel Umer, Nerella Vamshi Krishna, Perumandla Uday , Rallabandi Soumith. (2025). Explainable Machine Learning in Industrial IoT for Predictive Maintenance of Machine Condition Monitoring. Journal of Computational Analysis and Applications (JoCAAA), 34(4), 40–49. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2271
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