Multi-objective optimization of machining parameters on aluminum alloy metal matrix composites using response surface methodology

Due to their lightweight, new classes of materials, including aluminum-based Metal Matrix Composites (MMCs), have been popular in recent years in various industries, including aircraft and automobiles. Because of its low cost and ease of availability, aluminum alloy (LM13) MMCs were developed using Rice Husk Ash (RHA) as reinforcement in this study rather than traditional reinforcement, and composites were prepared using the stir casting technique. LM13-15wt.%RHA composite was chosen for the present machining study. The Central Composite Design (CCD) with three input parameters at three levels based on the best outcomes was adopted for this experimental study. A mathematical model was developed to predict the machining responses of Material Removal Rate (MRR) and surface roughness. The most significant variables were evaluated using ANOVA. The main and interactive effects of the input variables on the predicted responses are determined. The experimental and predicted values are nearly identical, indicating that the developed models can accurately predict responses. The optimal value of the turning parameters was obtained from desirability analysis. The obtained desirability value for turning parameters is 0.863, and for output response, the desirability value for surface roughness and MRR is 0.71663 and 0.747491, respectively, and the combined desirability is 0.731898. (c) 2023 Sharif University of Technology. All rights reserved.