Parametric optimization of the machining performance of Al-SiCp composite using combination of response surface methodology and desirability function

Abstract

Abstract In this study, machining parameters such as speed, feed, and depth of cut were optimized for maximum material removal rate (MMR) of Al-SiCp composite turned with a tungsten carbide tool using response surface methodology based central composite design while keeping tool wear and surface roughness within specified limits. The influence of turning factors on flank wear and surface roughness height was investigated using regression models. ANOVA analysis is used to assess the appropriateness of the projected models and the significant factors for response optimization using the desirability method. The percentage contribution of the significant machining parameters and their interactions for optimization of the response is determined using ANOVA technique. Cutting speed is found to be the most significant factor for flank wear, average roughness height Ra and maximum roughness height Rt with contribution of 65.38%, 58.7% and 37.9% respectively for optimization of the response. Confirmation tests were carried out and the percentage error between observed and predicted value of the responses is found to be within acceptable limits, demonstrating that the created models correlates well with the experimental data. Under optimal conditions, utilizing a tungsten carbide tool can prove to be a cost-effective alternative for turning Al-SiCp composite.