Method of Hierarchical Machine Learning for an Industrial Plant Machine Learning System

A computer-implemented method of hierarchical machine learning for an industrial plant machine learning system, comprising:

• receiving, by a machine learning unit, a topology model comprising structural information on hierarchical relations between components of the industrial plant, wherein the components comprise data signals of sensors of the industrial plant and hierarchical units, wherein the hierarchical units comprise assets, plant sub-units, plant units and plant sections of the industrial plant;
• determining, by the machine learning unit, a representation hierarchy comprising a plurality of levels using the received data signals and the received topology model, wherein the representation hierarchy comprises a signal representation for each of the plurality of received data signals and a hierarchical representation for each of the hierarchical units on different levels;
• wherein each representation on a higher level represents a group of representations on a lower level;
• wherein each of the signal representation and the hierarchical representation comprise a machine learning model;
• training, by the machine learning unit, an output machine learning model of the machine learning unit using the determined hierarchical representations.