Method and a system for tracking the downtime of a production machine

A method for tracking downtime of a production machine, the method comprising:

• continuously receiving, by a control unit, sensor data from the production machine and production target data,
• combining the sensor data and the production target data over a certain period providing combined data and calculating characteristic data of the combined data by the control unit,
• determining if the combined data is from a downtime period of the production machine based on the characteristic data, and
• characterizing the downtime period using a machine learning module implemented in the control unit, wherein the machine learning module provides one of a set of predefined reasons based on input values, wherein the predefined reasons are taught to the machine learning module through training, the machine learning module receiving the characteristic data of the downtime period as an input value and providing a reason for the downtime period as an output value,
• wherein the control unit stores the downtime period and the downtime period characterization time-resolved, and
• wherein, in case the downtime period is caused by a specific component of the production machine, the machine learning module additionally provides a respective identifier of the component of the production machine causing the downtime of the production machine.