The results of experiments on determination of the cylindrical part mass loss of the cone-shaped strikers made of 38XM (AISI P20), У8 (AISI W1-A), and X12MФA (AISI D2) steels, which have been subjected to heat treatment applied by the striking tools manufacturers, and additional cold treatment, with their friction and abrasive wear on granite, are presented. It was found that the strikers made of steel X12MФA with all types of heat treatment show the greatest wear resistance under the wear conditions (static conditions), while the strikers made of 38XM have the lowest wear resistance. Cryogenic treatment and, to a lesser extent, cold treatment increase the wear resistance of all materials. The comparison of set values of wear resistance Ist and hardness HV of the strikers, as well as the analysis of their microstructure allows to conclude that wear resistance of a tool depends not only on its hardness, but also on the type, volume, shape of carbides forming the structure of material used for tool manufacturing. For this reason, after the cryogenic treatment, the tool made of X12MФA steel shows the greatest wear resistance, because its material has the highest content of carbon (~1.5%) and alloying elements (~13%), which provides up to 10.8% increase in the number of fine carbide particles in its structure, that ensure wear resistance increase, after the cold treatment. The results obtained for Ist are compared with the earlier obtained data on wear resistance of the same striker at striking upon granite (in dynamic conditions). The conclusion about similarity of the wear mechanisms of the analyzed strikers in dynamic and static conditions is made.

The causes of failure of the tangential rotary cutter bits of the road header during stonedrift in rocks of medium strength are analyzed in the article. It was revealed that the most typical cause of failure of cutter bits is premature wear of the toolholder (body) of the cutter bit. It is well known that the most effective way to improve the wear resistance is to increase hardness. The influence of the thermomechanical treatment of the material of the cutter bit toolholder on its hardness is studied. It was established that the thermomechanical treatment of the cutter bit toolholder material results in the increase of its hardness. It was found that the increase of material hardness is proportional to the increase of material strain intensity during thermomechanical treatment. It was concluded that the use of thermomechanical treatment can lead to the increase of both the hardness and wear resistance of the cutter bit material.

The paper presents a methodology for training neural networks for vision tasks on synthe-sized data on the example of steel defect recognition in automated production control systems. The article describes the process of dataset procedural generation of steel slab defects with a symmetrical distribution. The results of training two neural networks Unet and Xception on a generated data grid and testing them on real data are presented. The performance of these neural networks was assessed using real data from the Severstal: Steel Defect Detection set. In both cases, the neural networks showed good results in the classification and segmentation of surface defects of steel workpieces in the image. Dice score on synthetic data reaches 0.62, and accuracy—0.81.