This analysis evaluates wear resistance and strength in PVD coatings, highlighting the role of neural networks in optimization.
The paper considers various compositions and designs of wear-resistant PVD coatings. Varying the thickness and number of layers allows to obtain the required properties of the carbide: increased strength, wear resistance and heat resistance during cutting. The indices of microhardness and crack resistance of the investigated coatings have been calculated. Resistance tests of cutting tools (end mills and drills) during machining of stainless steel 12Kh18N10Т and titanium alloy PT-3V have been carried out. It is shown that increasing the number of layers allows to increase wear resistance and heat resistance, and decreasing the thickness of monocoating allows to obtain higher strength. The structure of neural network for determination of optimal parameters of PVD-coatings is developed.
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Bashkov et al. (2025) studied this question.
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