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Big data analytics has practical applications in fault prediction across various industries. For example, in manufacturing, sensor data from machines is continuously monitored to identify patterns preceding breakdowns. Predictive maintenance models use historical and real-time data to forecast failures, enabling proactive repairs that reduce downtime and costs. Similarly, in energy sectors, data analysis predicts equipment malfunctions, ensuring stable power supply. Transportation systems use fault prediction to enhance safety and efficiency. Advanced machine learning algorithms improve prediction accuracy by detecting subtle anomalies. Successful case studies demonstrate significant savings and improved operational reliability, validating big data’s critical role in fault prediction and maintenance optimization.

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