Great attention is paid to the issues of improving the methods of product quality prediction, in particular, a comprehensive approach to its evaluation is being developed based on the principles of qualimetry. The example of experimental approach is provided to predict one of the mechanical properties - tensile strength which is an important indicator of the steel forgings quality. The investigation has been carried out to estimate the accumulated strain degree, chemical composition, friction conditions at contact surface influencing on temporal resistance distribution in the forging volume. The accumulation of strain degree was carried out by crimping of cubic billets in three mutually perpendicular directions with different number of crimping cycles according to cube-cube scheme. The distribution of strain degree over the volume of a deformed billet was experimentally determined for lead samples by coordinate grid technique. The lead cubic billets were cut in half. A square grid was applied to one of the halves, and then the halves were fused with a fusible Wood alloy and subjected to the first upsetting. After upsetting the sample was unsoldered and the Λ value in each cell was calculated from the curvature of the coordinate grid. The forging of steel billets was carried out in a similar way. After forging the steel billets, the specimens were cut out for mechanical testing. As a result of experimental data processing, the equation of regression has been received, which enables to predict the level of forgings’ tensile strength at the known technological parameters. Significance of the coefficients of the obtained equation was validated by the Student's criterion and the adequacy by the Fisher's criterion. The developed technique can be applied for selection of rational mode of deformation during forging for maintenance of the given level of mechanical properties
Translated title of the contributionPREDICTION OF THE TENSILE STRENGTH OF STEEL FORGINGS
Original languageRussian
Pages (from-to)53-58
Number of pages6
JournalЧерная металлургия. Бюллетень научно-технической и экономической информации
Volume78
Issue number1
DOIs
Publication statusPublished - 2022

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ID: 29857173