Multi-response Optimization and Surface Texture Characterization for CNC Milling of Inconel 718 Alloy

Abstract

The objectives of any modern machining process are to continuously enhance both volume and rate of production with best utilization of the resources. Attempts are always made to innovate, explore, plan and use resources such that the machining work becomes more and more effective, efficient, economically viable and environment-friendly. This requires knowledge or awareness of the factors which govern machining economy. In this research work, a fuzzy-based desirability function analysis has been considered for selection of input parameters of a CNC milling process, which will simultaneously optimize the responses like surface roughness, axial cutting force and material removal rate for decision making. A multi-response optimization for CNC milling of Inconel 718 alloy has been performed. The results showed that observation 12 has the highest value of multi-performance characteristic index (MPCI) and optimum combination of machining parameters is speed (3500 rpm), feed (100 mm/rev) and depth of cut (0.25 mm). In addition, most influencing factors for highest value of MPCI are feed rate. Digital image processing technique is used to measure the pixel count within two successive scratches. This technique illustrates that maximum and minimum distances between two successive scratches are 45.3 mm and 3.74 mm, respectively.