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This study explores the application of artificial intelligence for predictive maintenance in industrial systems, utilizing machine learning on sensor data to identify anomalies and foresee failures. The approach enhances maintenance scheduling, minimizes unexpected downtime, and leads to improved operational efficiency and cost savings compared to traditional methods. By shifting from reactive to proactive maintenance, AI facilitates better planning and early detection of potential issues.

Author

gamedark01

Language

EN