Open Access Conference Proceedings

The paper presents an idea and preliminary analysis of a new approach to modeling the surface geometry by applying advanced computational and analysis of data methods. It assumes that the material's surface may be treated as a random field and can be analyzed using the time series methods. The research aims to develop a model to predict surface geometry textured by a laser beam. Worked out predictive models supported by machine learning methods would indicate proper texturing process parameters to obtain specific surface geometry proprieties. The final goal of the research is to develop a model to predict the surface geometry parameters according to texturing process parameters. As a data set for the development and testing of the model, data from the profilometric test of samples with a cermet coating after laser with different beam power will be used.

Keywords: Random fields, time series, machine learning, surface geometry

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