1. A method for automatic on-line calibration of a process model for real-time prediction of process quality from raw process measurements which method comprises a) collecting raw process data, b) processing data collected in step a) through the process model to obtain a prediction of the quality, c) processing this prediction through dynamic transfer functions thus creating two intermediate signals, d) storing the two intermediate signals obtained in step c) as a function of time in history, e) retrieving at the time of a real and validated measurement of the quality from the history the absolute minimum and maximum value of the two intermediate signals in the time period corresponding to a minimum and maximum specified deadtime, which values define the minimum and maximum prediction possible, f) calculating the deviation as being the difference between the real and validated measurement and the area encompassed between the minimum and maximum prediction possible as obtained in step e), g) proceeding with step i) if the absolute value of the deviation obtained in step f) is zero, or, proceeding with step h) if the absolute value of the deviation obtained in step f) is larger than zero, h) incorporating the deviation into the process model, and i) repeating steps a)-h).