APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE QUALITY ASSESSMENT OF AXISYMMETRIC PARTS DURING COLD STAMPING

The article discusses improving the quality of axisymmetric parts manufactured by cold stamping using artificial intelligence technologies. Traditional quality control methods are labor-intensive and limited in detecting hidden defects. Special attention is given to analyzing multidimensional data obtained during production and non-destructive testing. Neural networks enable automated inspection, increased diagnostic accuracy, and reduced inspection time. AI application helps decrease defects, minimize human factor influence, and enhance process stability. The article explores approaches to integrating AI into cold stamping quality control systems and the prospects of production digitalization.