Calendering is an industrial process, recently abundantly employed for production of polymer foils. Main characteristic of this process is that a softened polymer or a polymer melt enters a device, called calender, that is usually composed of three (or more) heated rollers. In a series and with a chosen force they effect on an entering polymer and reform it into a foil with desired mechanical properties. The latter are important for further formation of foil into final product. In addition to numerous parameters, the mechanical properties of polymer films, which are important for the further transformation of the film into finished products, are also significantly influenced by the control of the calendering temperature, which determines the temperature of the material during travel between the cylinders. In this masters thesis we investigated the influence of the temperature of the cylinders on mechanical properties, such as the elastic modulus and hardness of the polypropylene film, which were determined by means of nanoindentation. The influence of the temperature of the rollers on the mechanical properties of the film was confirmed by the statistical method ANOVA. Using neural networks of multilayered perceptron and radial base function, we created an empirical model of the influence of cylinder temperatures on the final mechanical properties of the product. The confirmed possibility of modeling the properties of the calandered product with neural networks is the basis for further improvements and optimization of the parameters of the calendering process.
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