Parametric Analysis and Optimization on Fiber Laser Micro-Milling on AZ31 Magnesium Alloy

Abstract

One of the proficient machining technologies to create micro-features in a variety of materials is the laser micro-milling process. This procedure involves irradiating a highly concentrated laser beam on the sample and performing laser cutting at various cutting patterns to change the surface conditions and enhance the characteristics of that surface tribology. In this work, an effort has been made to mill magnesium alloy (AZ31) material using a laser. The pulse frequency, laser beam power, cutting speed, number of passes, and transverse feed are among the different process variables taken into account for the current research effort. Measured results include depth of cut and surface roughness. To ensure the validity of the established empirical models, this paper also presents experimental data. Several surface plots have been used to examine the test data. To get the lowest values of surface roughness and depth of cut, multiperformance optimization is also utilized. The influence of process factors on response has also been examined using optical microscopic images. Gray relational analysis approach is also applied to obtain the multiobjective optimization parametric combination and based on the calculated results of gray relational grade, it is revealed that improvement in the value of gray relational grade at predictive setting is 0.054 compared to the initial parametric combination.