Multi-Objective Optimization of Dry Sliding Wear in Cryogenically Treated High-Performance AISI 9310 Steel: An Integrated Approach Using Grey Relational Analysis and Taguchi Method

Abstract

AISI 9310 steel is widely used in the aerospace and defense industries due to its superior mechanical properties and corrosion resistance. This study introduces a novel approach by investigating the effects of both shallow (SCT) and deep (DCT) cryogenic treatments on the wear resistance and surface properties of AISI 9310 steel. An integrated methodology that combines Grey Relational Analysis and the Taguchi method for optimization was applied. Wear performance was evaluated using a ball-on-disc tribometer in dry sliding wear tests, revealing significant improvements. The results show that the hardness of the samples processed with DCT increased by 30%, while their volume loss decreased by 14%. In samples processed with SCT, hardness increased by 12%, with a corresponding 7% reduction in volume loss. Furthermore, the friction coefficient improved by 9% in DCT samples and by 5% in SCT samples. As the load increased, volume loss increased by 16% (from 3400 mm³ to 3950 mm³), while the friction coefficient decreased by 11% (from 0.448 ? to 0.498 ?). ANOVA analyses indicated that cryogenic treatment had the greatest effect on both volume loss and the friction coefficient. Regression analysis revealed an excellent model fit, with R2 values of 97.63% for volume loss and 99.42% for the friction coefficient. These findings suggest that cryogenic treatments significantly enhance the wear resistance of AISI 9310 steel and improve performance under varying load conditions. Additionally, they highlight the critical role of cryogenic processes in extending the service life of materials used in industrial environments, providing valuable insights for future engineering applications.