One of the problems of the use of drum pelletizers in metallurgy is the lining wear, as well as the economic costs associated with it, including increased energy costs during operation and the need to periodically stop the units and then replace the lining. Most significantly the trajectory of particle motion affects the lining wear profile and wear intensity. It is assumed that during the implementation of the technological process, a monodisperse occurs, which has the greatest effect on the wear profile. In addition, the lining wear is influenced by the impact of particles at an acute angle, with a maximum impact caused by a collision at an angle of 39°18′. At present there are no universal solutions for determining the degree of lining wear in real time with a corresponding adjustment of the pelletizing process parameters. Creating a system for monitoring the lining wear is necessary for timely repair and maintenance of equipment to prevent an emergency situation, as well as increase the service life of the aggregates. This article proposes a concept of a method that allows to evaluate the trajectory of the charge during the technological process according to the coordinates of the movement and acceleration of the probe in the unit during the implementation of the technological process. The digitization and analysis of data obtained from the probe will allow to assess the integrity of the lining surface, the degree of lining wear and places with increased wear rate in real time with the possibility of adjusting technological processes to increase the lining service life. The obtained data will allow to clarify the computer model of the process by assessing the behavior of the charge in the unit and create a reserve for the further implementation of digital twin equipment.

In the article the process of destruction of the array of Cambrian clays by cutting, as a dynamic contact problem of mechanics, solved with using the software environment ANSYS Worbench, is observed. The obtained results are verified on a laboratory bench setup with experimental investigations. Analysis of the results of computational and laboratory experiments shows that in the framework of theoretical and experimental approach to solving problems of continuum mechanics, as an integral part of the basic research a finite element method can be used, which lets adequately and with sufficient accuracy to determine the power and energy indicators of process of destruction of the clay arrays by cutting. A characteristic feature of the process of destruction of flooded Cambrian clays is significant plastic deformation of rocks at the contact with the cutter. The separation of the elements of destruction from the array occurs under the action of shearing stress by the formation of shear cracks. High viscosity of arrays of Cambrian clays defines a large share of energy consumption on their destruction, comparable in value to the energy intensity of the process of cutting of hard coal and salt rocks. The use of computer simulation can significantly reduce the duration and increase the accuracy of design calculations at designing of the actuating devices of mining machines.

The research considers conducting orthogonal experiment (OT) as one of the stages in developing a new discrete element method (DEM) parameters calibration approach. The measured responses in experiment are the parameters obtained by DEM animation processing using machine vision system (MVS). The variable factors in experiment are DEM parameters. A brief overview of an existing calibration approaches given in the article. The choice of OT as a design of experiment tool among other mathematical tools discussed. Experiments conducted using specially developed rig where bulk material's flow captured as DEM animation. DEM animation converted to video and then processed using MVS that allow register the values of such parameters as angle of repose or expiration time (measured responses). The results of the OT show that it is possible to identify four measured responses with the most valuable correlation coefficient. DEM parameters with the biggest influence on the measured responses identified for each of the obtained regression. Obtained results are useful in learning or iterative algorithms development for DEM parameters calibration.