Predictive maintenance is a proactive maintenance approach that utilizes data analysis and machine learning techniques to anticipate equipment failures before they occur. By monitoring and analyzing sensor data, such as temperature readings, predictive maintenance aims to detect early warning signs of anomalies or degradation in equipment performance.
This enables timely maintenance actions, minimizing unplanned downtime, optimizing maintenance schedules, and reducing costs. In this way, predictive maintenance helps businesses enhance operational efficiency, extend asset lifespan, and improve overall productivity.
t6 IoT platform is now capable of predict equipment failure based on custom AI Models.
I've written a recipe on how to implement such data prediction using t6 IoT.
This new feature is developped as beta version on t6. Please send me any feedbacks.
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