Application of artificial neural networks in properties modelling of PVD and CVD coatings
L. A. Dobrzanski; M. Staszuk; R. Honysz
Archives of Computational Materials Science and Surface Engineering
Abstract
Purpose: The aim of this paper is to describe the application of artificial neural networks in development of a model, which describes the influence of PVD and CVD coatings properties on the cutting edge durability from sintered carbides covered with these layers. Design/methodology/approach: The input data used for the artificial neural networks were PVD and CVD coatings microhardness, thickness, grain size and their adhesion to the substrate. On the network's output is the durability of the PV...MoreD and CVD coatings coated on sintered carbide blades determined in technological cutting trials of grey cast iron. Findings: Research results shows, that the greatest influence on the durability of coated sintered carbide blades is adhesion to the substrate. Smaller influence on blades durability has the size of grains. Other properties have a minor influence on the cutting tool. Practical implications: The presented results indicates, that the coating material selection and design of PVD and CVD coatings deposition process should be implemented with taking into consideration in the first place the best coating's adhesion to the substrate. Originality/value: The application of artificial neural networks for influence determination of PVD and CVD coatings microhardness, grain size, thickness and adhesion to the substrate on the durability of the sintered carbide blades covered with investigated coatings.
keywords:Analysis and modelling; Computational Material Science; Working properties of materials and products; Mechanical properties; Thin and thick coatings
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