Equipment effectiveness in manufacturing environment

A method of training a server to measure Operational Equipment Effectiveness for one or more machines, the method comprising:

• providing a machine learning model to the server;
• establishing training data for the machine learning model, wherein the training data comprises output from the one or more machines comprising a plurality of tags, wherein the tags are defined according to an open standard for providing machine data, wherein the tags are provided together with Operational Equipment Effectiveness parameter values applying at the time of creation of the respective tag;
• training the machine learning model with the training data to provide a trained analysis model adapted to identify Operational Equipment Effectiveness parameter values from a stream of tags from the one or more machines and to determine Operational Equipment Effectiveness thereby, wherein the determined Operational Equipment Effectiveness for the one or more machines is configured for diagnosing and solving problems in a manufacturing environment that comprises the one or more machines, wherein the open standard for providing machine data is OPC-UA, and wherein the server is an OPC server.