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.

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.

Modern industry in the XXI century requires high-performance and fully automated technology. The best way to meet these requirements is the introduction of new progressive technologies in the process of transportation. One of the possible ways to increase productivity, as well as automate the process of transportation, is the transition from cyclic machines to continuous transport, namely to belt conveyors. However, with the increase in the length of the conveyor there is a need for stronger belts. This can be avoided by using intermediate drives of various designs. The article describes the principle of operation of the intermediate linear drive with transverse partitions, provides formulas for calculating the values of the tractive effort, gives comparative graphs showing the effectiveness of the use of an intermediate drive in various conditions. The possibilities of increasing the capacity of an intermediate linear drive are described.