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The quality of the paint application in automotive industry depends on several process parameters. Thus, finding an optimal solution based on experimental configuration is tedious and time consuming. A first step to reduce the effort is to model the application within the framework of a simulation environment. In this study, we present an approach for the systematic variation of design parameters of the paint process to quantify their influence on the quality of the paint application. Using that information the design space is reduced by neglecting the parameters with low impact and later used to predict an optimal set of input parameters for an optimal paint application.