Procedure to improve the measuring performance of a field device to be configured, which is installed in a defined application and which determines or monitors at least a defined physical or chemical process variable in an automation system, wherein said procedure comprises the following steps: Several field devices , which determine or monitor different physical or chemical process variables in different applications (A) and under different environmental conditions (UB) present at individual measuring positions of the field devices , are configured or parameterized using a configuration tool , Configuration data , information about the respective applications (A) and information about the environmental conditions (UB) of the different field devices present at the individual measuring positions are saved in a central data memory as training data (TD), The training data (TD) is provided to a computing program that is capable of learning, wherein the program uses at least a machine learning method, wherein the computing program that is capable of learning is trained with the training data (TD), For the purpose of configuring or parameterizing the field device to be configured, current information about the respective application (A) and the environmental conditions (UB) present at the measuring position of the field device to be configured are provided to the computing program that is capable of learning, On the basis of the current information, the computing program that is capable of learning provides the field device to be configured with configuration data based on the multiple training data items, which are adapted to the respective application (a) taking into account the environmental conditions (UB) present at the measuring position of the field device to be configured. Several field devices , which determine or monitor different physical or chemical process variables in different applications (A) and under different environmental conditions (UB) present at individual measuring positions of the field devices , are configured or parameterized using a configuration tool , Configuration data , information about the respective applications (A) and information about the environmental conditions (UB) of the different field devices present at the individual measuring positions are saved in a central data memory as training data (TD), The training data (TD) is provided to a computing program that is capable of learning, wherein the program uses at least a machine learning method, wherein the computing program that is capable of learning is trained with the training data (TD), For the purpose of configuring or parameterizing the field device to be configured, current information about the respective application (A) and the environmental conditions (UB) present at the measuring position of the field device to be configured are provided to the computing program that is capable of learning, On the basis of the current information, the computing program that is capable of learning provides the field device to be configured with configuration data based on the multiple training data items, which are adapted to the respective application (a) taking into account the environmental conditions (UB) present at the measuring position of the field device to be configured. <EOS>