Abstract: Methods for predictive maintenance with using machine learning in a building automation system and corresponding systems and computer-readable mediums. A method includes receiving device event data corresponding to a device and executing an inference engine to determine root cause fault data corresponding to the device event data. The method includes executing a predictive maintenance engine to produce a survival analysis for the physical device based on the root cause fault data. The method includes producing updated failure data by the predictive maintenance engine, based on the survival analysis, and providing the updated failure data to the inference engine. The inference engine thereafter uses the updated failure data in a subsequent root cause analysis. The method includes outputting the survival analysis.

Abstract: Methods for predictive maintenance with using machine learning in a building automation system and corresponding systems and computer-readable mediums. A method includes receiving device event data corresponding to a device and executing an inference engine to determine root cause fault data corresponding to the device event data. The method includes executing a predictive maintenance engine to produce a survival analysis for the physical device based on the root cause fault data. The method includes producing updated failure data by the predictive maintenance engine, based on the survival analysis, and providing the updated failure data to the inference engine. The inference engine thereafter uses the updated failure data in a subsequent root cause analysis. The method includes outputting the survival analysis.