The process of data processing for the purpose of use in an artificial intelligence system is shown as part of the master's thesis. The latter is used for prediction of welding fixtures adjustments within the trailing arm manufacturing process. The theoretical starting points necessary for a correct understanding of the problem are presented at the beginning. Methods for approximating curves and surfaces are briefly presented here. Akaike information criterion which is used in the following for the selection of polynomial degrees is also presented. The middle part of the thesis describes the factors that affect the welding fixtures adjustments or rather the final geometry of the manufactured trailing arm. It was found that the geometry of the stamping parts has the greatest influence on the implementation of adjustments. In the following, the methods used to describe the geometry of stamping parts were presented. The method in which deviations in the normal direction to the surface are approximated with the help of polynomials proved to be the most appropriate. At the end, the concept of a system for processing data and performing welding fixtures adjustments is presented.
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