Optimization and Modeling Approaches in Machining of High Temperature Super Alloy Steels: An Overview

Abstract

Over the years, the need for appropriate selection and implementation of optimal cutting conditions has been a major issue among the metal cutting researchers. The implementations of multicriteria decision tools in modern machining were highly valued due to a better capacity to select the optimum parametric combinations. In the optimization method, an objective function is developed with or without mathematical model whereas a mathematical equation based model is formulated, based on input and response parameter in modeling technique to obtain the best efficient cutting environment. In this review paper, various modeling techniques like artificial neural networks, fuzzy modeling, and regression modeling analysis along with Taguchi technique, genetic algorithm and response methodology for application in turning have been focused. Moreover, some new investigations and observations are focused on the advancement of new strategies like (PSO) Particle Swarm Optimization, as it is simple and easy to utilize. In addition, multi-objective optimization is an essentially needed when a single optimization technique can’t produce a satisfactory result. This overview states the significance of optimization and modeling technique in the field of high-temperature material and discloses the critical issues related to it.