ayush-agarwal-0502/Machine-Predictive-Maintainence-Anomaly-Detection
Anomaly Detection deployed on machine data dataset for Predictive Maintenance
This project helps operations engineers and plant managers predict when industrial machines might fail, enabling proactive maintenance. It takes sensor data from machines, such as temperature, pressure, and RPM, and outputs a prediction of whether the machine is operating normally or if an anomaly suggests a potential upcoming failure. This helps prevent costly breakdowns and unscheduled downtime.
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Use this if you need to identify unusual machine behavior that could lead to equipment failure, allowing you to schedule maintenance before major problems occur.
Not ideal if you require predictions on the specific *type* of failure, rather than just identifying that an anomaly exists.
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Feb 14, 2024
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