Prediction and Optimization of Flank Wear and Surface Roughness in Down Milling of Al- 7075+ (Al2O3)P MMC using Ti-N Coated Helical Milling Cutter

Abstract

During milling operations of Aluminum Metal Matrix Composites (AMMC) by using plain HSS cutters, some problems arise because of the fabrication of reinforced particles. To achieve this problem, coated helical milling cutters are used to minimize the wear rate and better surface finish. In this study, flank wear is observed on Titanium Nitride (Ti-N) coated milling cutters in down milling of Al-7075+ 4% Al2O3-p, afterwards the wear rate of the cutter and surface roughness of composite were investigated. Image processing tool in MATLAB is adopted to measure the wear rate on both the axes of cutter and surface roughness (Ra) of the MMC’s measured by using Talysurf meter. In this work, the input parameters speed, feed rate and depth of cut were taken in a range of low, medium and high; coolant conditions are dry, soluble oil and diesel. The optimum milling parameters were found by using Fuzzy- Taguchi optimization method and the practical results were compared by Fuzzy prediction values. It is observed that tool wear and surface roughness were lower at higher cutting speed, lower feed rates and lower depth of cuts when soluble oil is used as coolant and the variation between experimental data and predicted data is comparatively less.