Experimental Investigation and Optimization of Process Parameters in Milling of Hybrid Metal Matrix Composites

Abstract

This article presents the experimental investigation and optimization of the machining parameters while milling of hybrid metal matrix composites (MMCs) using tungsten carbide insert. Materials used for the present investigation are Al 6061-aluminium alloy reinforced with alumina (Al2O3) of size 45 micron and graphite (Gr) of an average size 60 micron, which are produced through stir casting route. The response surface methodology (RSM) is used for modeling, optimization, and analysis of dominant machining parameters, namely, spindle speed, feed rate, depth of cut and weight fraction of Al2O3 particles in terms of their effect on cutting force and surface roughness during milling hybrid MMCs. The experimental data were collected based on a four factor-three level full central composite design (CCD). The multiple regression analysis using RSM was conducted to establish input–output relationships of the process. Mathematical models were developed and tested for adequacy using analysis of variance and other adequacy measures using the developed models. The main and interaction effects of the input variables on the predicted responses were also investigated. The predicted and measured values are fairly close, which indicates that the developed models can be effectively used to predict the responses in milling of hybrid MMCs. The optimized milling process parameters obtained by numerical optimization using RSM, ensure a minimum cutting force of 132.8 N and surface roughness of 0.28 µm. After the milling test, a scanning electron microscope (SEM) was used to investigate the machined surface and tool wear.