Russian Metallurgy (Metally)最新文献

The paper describes hardware and software for automating the measurement of linear dimensions on worn parts of tillage implements. The software package is based on the Python programming language and is integrated with the Kompas-3D CAD system and the Microsoft Excel office package. This allows for the automation of wear measurement processes, greatly accelerates measurements, and minimizes errors. The proposed software ensures precision and convenience of data processing, thus enhancing the efficiency of wear analysis for soil tillage machinery components. Special attention is paid to the application of the software under specific conditions, as demonstrated by the example of measuring the wear of Terraland chisel ploughs. The implementation of the proposed software solution will contribute to the development of technologies for the restoration and strengthening of soil tillage machinery parts.

The plastic deformation of a helical relief on the shaft surface by electromechanical smoothing is considered. It is shown that the rational shape of the cross section of the helical relief is a sinusoid. The results of the analytical study can be used to determine rational process conditions for hardening or restoring the surfaces of parts.

The process of searching for a method of plastic deformation of steel spiral drill collars (SDCs), the external surface of which has fins with a high spiral pitch angle, is considered. A heuristic procedure of searching for technical solution satisfying a given restriction system is presented. Then, on this base, it is recommended to consider two versions of manufacturing, which are then modeled using a finite element method. It is proposed to subject these pipes to rolling in three rolls with their oblique arrangement with respect to the rolling axis and gradient heating the pipe body before a shaping stand. The fins are formed in the gap between the roll ends. The metal forming is determined at a given fin configuration. All geometric and energy power parameters of the process required for designing equipment are also determined.

The technological capabilities of ultra-high-speed milling are assessed. The results of milling brass, aluminum alloys, and stainless steel at cutting speeds of 25–125 m/s are presented. The possibility of increasing the productivity and quality of metal machining is shown.

The paper presents a review of contemporary methods employed for machining gear wheel interdental spaces in small-scale production, considering their advantages and limitations. The enhancement of machining technologies, along with the integration of computer-aided manufacturing and computer-aided design systems, substantially increased production efficiency. This, in turn, reduced operational time and optimized tool selection. A particular emphasis is placed on machining worm wheel spaces, a process that involves the utilization of computer-aided design systems and hi-tech manufacturing. These technologies facilitate the development of models that enhance manufacturing processes and reduce errors associated with manual machining. The results of the study indicate a clear relationship between the diameter of the cutting tool used and the machining time required for different worm wheel parameters. This highlights the crucial role of tool selection in optimizing manufacturing processes. A mathematical model was constructed based on the collected data to predict the time of milling worm wheel spaces by numerically controlled machine tools. The developed model is of interest to engineers and designers, as it allows for the estimation of the required cutting tool diameter and machining time in advance, which greatly facilitates the planning of the production process.

Magnesium-matrix composite materials reinforced with high-alloy chrome–nickel steel are promising low-density materials with improved strength. To activate the steel surface for liquid-phase formation of steel-reinforced magnesium-matrix composite materials, we propose chloride, chloride–fluoride, and fluoride fluxes such as are widely used in soldering of magnesium alloys. Our results demonstrate how the nature of the flux and process temperature influence the wetting and spreading properties of liquid magnesium on high-alloy austenitic steel. We have identified the most efficient activating flux compositions. Preliminary aluminizing of steel has been shown to ensure a considerable increase in the spreading area of magnesium on austenitic steel.

This work explores common applications of additive technologies in the production of rotational body components from thermoplastic materials. The influence of 3D printing parameters on the maximum torsional loads of parts fabricated from ABS and PETg + GF12 (GFmax) polymers is investigated. Recommendations are given for the selection of 3D printing conditions to ensure the reliable transmission of the required torque. Additionally, the fracture behavior of torsion test specimens is analyzed, and the factors contributing to premature failure are identified.

The hydromechanical pressing of bimetallic composite material workpieces is optimized. Neural network modeling is used to determine the optimum values of key technological parameters (reduction ratio, die cone angle, contact friction conditions) to achieve a complex minimum (quality criterion) of deformation heterogeneity, fiber (filament) damage, and pressing stress.

Based on publications by Russian and international researchers, the article reviews the challenges of current copper concentrate smelting technologies. The authors identify and examine three main issues that require resolution: increasing the efficiency of smelting copper sulfide ores by lowering the copper content in slags generated during converting; improving efficiency, including through additional economic gains from waste utilization; and reducing harmful environmental impacts. The development trends toward new, efficient, environmentally safe, and economically viable technologies apply not only to the selected object of study, but also to several other nonferrous metals, such as lead and zinc.

The growing demands on the reliability and efficiency of agricultural machinery make the task of studying the wear of its implements increasingly urgent. The paper presents a review of the potential applications of machine vision technologies for analyzing the wear of structural elements in soil tillage tools. Key approaches, such as 3D surface reconstruction, image processing, and deep learning methods, are examined. We analyze the prospects of automating the assessment of part conditions, eliminating the subjective factor in diagnostics, and improving measurement accuracy. Particular attention is given to the technological capabilities of machine vision, its advantages over traditional analysis methods, and potential areas for further research to increase the service life of the working parts of soil tillage machines.