Use of parameters determined in a production line for coating at least one carrier material with at least one resin layer, in particular at least two, three or four parameters determined simultaneously, for controlling at least one production line, wherein the production line includes: - at least one NIR multi-meter head for recording at least one NIR spectrum of the resin layer applied to the carrier material in a wavelength range between 500 nm and 2500 nm, preferably between 700 nm and 2000 nm, particularly preferably between 900 nm and 1700 nm and especially advantageously between 1450 nm and 1550 nm; and - at least one control system comprising at least one computer aided evaluation unit and a database, - wherein the at least one NIR multi-meter head is connected to the at least one control system with evaluation unit and database for processing and storing the recorded NIR data, - wherein the evaluation unit is configured to simultaneously determine several desired parameters by an automated comparison of the single NIR spectrum recorded for the resin layer applied to the carrier material with a calibration model created for the respective parameters, - whereby the database is configured to store the parameter data determined in this way in the database, where the calibration model is determined using reference samples as follows: - Recording of at least one NIR spectrum of several reference samples, each with different values of the desired parameters, using at least one NIR multi- measurement head in a wavelength range between 500 nm and 2500 nm, preferably between 700 nm and 2000 nm, particularly preferably between 900 nm and 1700 nm, and especially advantageously between 1450 nm and 1550 nm; - Determination of the desired parameters of the measured reference samples using non-spectroscopic methods; - Assignment of the determined parameters to the recorded NIR spectra of the measured reference samples, - Creation of the calibration model for the relationship between the spectral data of the NIR spectra and the corresponding parameter values by means of multivariate data analysis, wherein the determined parameters are fed to a "self-learning" Al-based evaluation system (machine learning) for further optimization of the control of the at least one production line and/or for predicting the function of the at least one production line and/or for optimizing the start-up process of the at least one production line, - at least one NIR multi-meter head for recording at least one NIR spectrum of the resin layer applied to the carrier material in a wavelength range between 500 nm and 2500 nm, preferably between 700 nm and 2000 nm, particularly preferably between 900 nm and 1700 nm and especially advantageously between 1450 nm and 1550 nm; and - at least one control system comprising at least one computer aided evaluation unit and a database, - wherein the at least one NIR multi-meter head is connected to the at least one control system with evaluation unit and database for processing and storing the recorded NIR data, - wherein the evaluation unit is configured to simultaneously determine several desired parameters by an automated comparison of the single NIR spectrum recorded for the resin layer applied to the carrier material with a calibration model created for the respective parameters, - whereby the database is configured to store the parameter data determined in this way in the database, - Recording of at least one NIR spectrum of several reference samples, each with different values of the desired parameters, using at least one NIR multi- measurement head in a wavelength range between 500 nm and 2500 nm, preferably between 700 nm and 2000 nm, particularly preferably between 900 nm and 1700 nm, and especially advantageously between 1450 nm and 1550 nm; - Determination of the desired parameters of the measured reference samples using non-spectroscopic methods; - Assignment of the determined parameters to the recorded NIR spectra of the measured reference samples, - Creation of the calibration model for the relationship between the spectral data of the NIR spectra and the corresponding parameter values by means of multivariate data analysis,