Multi-Objective Optimization of Cutting Parameters during Laser Cutting of Titanium Alloy Sheet using Hybrid approach of Genetic Algorithm and Multiple Regression Analysis

Abstract

Now a day’s advance engineering materials are playing a key role in the field of aeronautics, defense and medical. Titanium and its alloys are one of the advanced engineering materials that have great demand in the various fields of industries due to its greater behavior and better mechanical properties. These applications require precise and better quality cuts which may not be obtained by conventional machining processes due to the unfavourable properties of Ti and its alloys. This problem may be minimized by using laser cutting process. In this study, the Advanced 300 W Nd:YAG Laser cutting system has been applied for the cutting of titanium alloy sheet. The point of current research is to optimize kerf width and kerf deviation, simultaneously during the laser cutting of Titanium alloy sheet (Grade 5).The multiple regression analysis has been applied for developing the second order regression models of kerf width and kerf deviation. The optimization technique genetic algorithm has been applied for the multi-objective optimization of the developed models. The comparison results show an improvement of 29.78% for kerf width and 95% for kerf deviation, respectively. The overall percentage improvement of 27.39% has been found by considering the equal importance of both quality characteristics. The parametric effects on quality characteristic have been also discussed.