Purpose: The aim of this paper is the presentation of developed computational model build with use of artificial neural networks. This model describes the influence of PVD and CVD coatings properties on the cutting edge durability from sialon tool ceramics covered with these layers. Design/methodology/approach: Obtained model has the ability to compute the durability of the PVD and CVD coatings coated on sialon tool ceramics blades determined in technological cutting trials of grey cast iron, basing on PVD and CVD coatings microhardness, thickness, grain size and their adhesion to the substrate. Findings: Results of researches, performed with use of computational model, revealed, that the greatest influence on the durability of coated sialon tool ceramics blades have the adhesion to the substrate. Smaller influence on blades durability has the size of grains. Minor influence on the cutting tool from other properties was obtained. Practical implications: Achieved results indicates, that the best coating’s adhesion to the substrate for coating material selection and design of PVD and VD coatings deposition process should have priority in implementation. Originality/value: Obtainment and utilisation of computational model builded with use of artificial intelligence methods
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