Analysis of the possibility of applying the machine learning methods for the prediction the surface geometry after its technological treatment
Autor
Gądek-Moszczak, Aneta
Nowakowski, Dominik
Lempa, Paweł
Opublikowane w
METAL 2023: 32nd International Conference on Metallurgy and Materials, May 17-19, 2023, Brno, Czech Republic
Numeracja
2023
Strony
445-448
Data wydania
2024
Miejsce wydania
Ostrava
Wydawca
Tanger Ltd.
Język
angielski
ISSN
2694-9296
ISBN
978-80-88365-12-9
DOI
https://doi.org/10.37904/metal.2023.4725
Słowa kluczowe
random fields, time series, machine learning, surface geometry
Abstrakt
The paper presents an idea and preliminary analysis of a new approach to modelling 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.
