Minimizing residual stresses in AISI 1045 steel through optimization of cutting parameters: A particle swarm optimization approach

Abstract

This study deals with the effect of machining parameters on residual stresses caused during the end milling of AISI 1045 steel. A new tool insert was used for each trial, and residual stresses were measured on the machined surface after a single pass. From this analysis, it could be found that the increase of residual stresses becomes more tensile in nature because cutting speed and feed rate also go up along with increasing temperatures but compressive stress in cuts that require a larger depth. According to Taguchi's design of experiments, optimized cut parameters will show a decrease in the occurrence of residual stresses. Regression analysis showed that the cutting parameters explained 84% of the residual stress variation, with the feed rate being the most significant parameter (P-value = 0.004). Optimization was done using particle swarm optimization which resulted in the optimal values which are as follows. A spindle speed of 710 r/min, feed rate, of 80 mm/min, and depth of cut, of 0.2 mm, which leads to a minimum residual stress of 203.73 MPa (compressive). This work can be considered as a framework for the prediction and optimization of machining parameters.