Development of Mathematical Models and Evaluation of the Optimal Process Parameters for Laser Surface Hardening of Low Alloy Steel Using Elitist Non-dominated Sorting Genetic Algorithm

Abstract

The process parameters of the laser hardened zone play a vital role in determining the surface hardness of the material after the hardening process. The most influencing input parameters such as laser power and traveling speed are considered in conducting the experimental work. The ultimate aim is to obtain maximum hardness, minimum width, and maximum depth after the laser surface hardening (LSH). The desired output responses are obtained by optimizing the process parameters and suggesting it for future research to eliminate the unnecessary trials. Trial and error procedures of finding out the optimal conditions incur more time and effort. Thus, the optimization was carried out using the non-conventional technique, elitist non-dominated sorting genetic algorithm (NSGA-II). The laser surface hardening was carried out on the low alloy steel using fiber laser source. The experimental trials were designed using response surface methodology (RSM), and the mathematical equations were developed using regression analysis. The mathematical models are utilized by the NSGA-II algorithm by conducting ‘n’ iterations for ‘m’ population levels to find out the optimized zone for performing the hardening process.