AI-Based Predictive Maintenance for Industrial Equipment Using IoT Sensors
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Abstract
Predictive maintenance is essential for minimizing downtime and improving operational efficiency in industries. This paper proposes an AI-driven framework that utilizes IoT sensor data to predict equipment failures before they occur. Machine learning models such as Support Vector Machines and LSTM networks are used to analyze time-series data. The system demonstrates high accuracy in fault detection and reduces maintenance costs. The approach contributes to the advancement of smart manufacturing systems.
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References
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