Common data sources for predictive maintenance problems are :
Failure history: The failure history of a machine or component within the machine. Maintenance history: The repair history of a machine, e.g. error codes, previous maintenance activities or component replacements. Machine conditions and usage: The operating conditions of a machine e.g. data collected from sensors. Machine features: The features of a machine, e.g. engine size, make and model, location. Operator features: The features of the operator, e.g. gender, past experience The data for this example comes from 4 different sources which are real-time telemetry data collected from machines, error messages, historical maintenance records that include failures and machine information such as type and age.
This project is related to how machine failure can be detected. Like if an aircraft has some signals then, on the basis of that we can predict before the proplem takes place.