Nowadays pelletizing drums are widely used in the steel industry. These units are characterized by high endurance and low cost of maintenance. However, use and control of these units in the process of coarsening have a number of issues. For most of the cases pelletizing drums are “black box” and control accuracy can not be estimated exactly. It is explained by low existing theoretical basis of this production process. Particularly it is tied up with the variability of the bulk materials (charges) parameters supplied to the unit. Overcome of this issues can be reached with development of intelligent control systems for drum pelletizing machines. Main requirement for such systems is possibility to level or consider the effect of charges properties variability in control. However, it is necessary to study the behavior of bulk materials inside the units. Visual assessment of pelletization does not allow to evaluate the ongoing physical processes. Development of mathematical and numerical models can help studying the process and take a lot of parameters into account including charges properties and even interaction with water. But the adequacy of the resulting models also has to be clarified using physical devices to record or capture bulk materials behavior inside the units. This research proposes a DEM simulation test of the concept for bulk material behavior control through the recognition of the mixture movement fragments using special capsules. This part is dedicated to the simulation model set up and extracting the particles trajectories for further processing.

The results of tests for resistance to abrasive wear on highly abrasive hard rock white electrocorundum are presented. The main material of fast-wearing elements of mining and processing equipment-110G13L steel (Gadfield steel) in comparison with other 9 grades of steel and cast iron, including specially developed wear-resistant foreign steels such as Hardox and Miiluks, is analyzed. The studies were carried out using an experimental stand for studying the material wearing process. On the stand the sample was fixed in a holding device and, after being brought into contact with the abrasive, it was rotated under a constant load. As a result of the experiments, it was confirmed that the order of placement of the tested materials in terms of increasing wear resistance coincides with their placement in terms of increasing hardness. At the same time, the wear resistance of the most resistant material – U8A steel after quenching – is about 4 times higher than this indicator for the least resistant components – low-carbon steel 25L, including gray and high-strength cast iron SCH21, VCH35. The wear resistance of 110G13L steel, as well as 65G, U8 steels in the hardened state, is from 1.5 to 2 times higher than that of foreign steels M400, H450, M500, H500. The results of the conducted studies allow us to evaluate the analyzed materials on the basis of their wear resistance and hardness indicators on the feasibility of using them in the manufacture of fast-wearing parts of mining equipment. Based on the research data, it seems promising to develop new ways to increase the wear resistance of domestic steel, including 110G13L steel traditionally used in mining.

Today the industry is facing a shortage of skilled workers and an aging workforce, which will eventually lead to a loss of knowledge. But augmented reality technology can connect field workers with experts who are able to provide remote guidance in real time. The subsequent advantage is that the information obtained by AR devices can be used as accumulated successful experience in the future, which facilitates decision-making in specific business processes of the company. With AR, employees gain experience and skills much faster. This paper shows the application of augmented reality technology in the maintenance of electromechanical equipment. The main functions of the augmented reality system for servicing electrical equipment are presented, the solution to the problem of integrating an augmented reality software application with existing automation systems is shown, and the methods of interaction of the developed software module with third-party modules, for example, various analytical modules, etc. are described.