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The programming of robots for spray painting jobs is a time-consuming and cumbersome task. On the one hand, a good understanding of the paint process and on the other hand a good intuition to program the robot paths are required. This paper presents a simulation tool to predict accurately the thickness of a coating layer on highly curved surfaces. Starting from a model of a spray cone with an infinite length, and the results of several experiments, an accurate model for the spray cone is developed. A density distribution function is used to describe the concentration of paint drops inside the spray cone. Reference or calibration tests are used to evaluate the influence of the process parameters like the spraying distance, spraying velocity, paint flow rate, paint pressure and atomization air pressure. Starting from the prediction of the paint thickness on flat surfaces, the simulation is extended to surfaces with arbitrary shape and curvature. Experiments with an industrial robot and state-of-the-art coating equipment show a high accuracy of the simulation results.