Course Project Work 

The aim of this literature is to illustrate the application of multi-objective optimization routines through a case study of the face milling operation. For this purpose, the face milling operation is designed as a multi-objective optimization problem and then solved to obtain optimum values for the machining parameters– cutting speed (Vc), feed rate (fz), and depth of cut (t); using the optimization routines. The formulated problem of face milling operation includes two conflicting objectives– maximization of Material Removal Rate (MRR) and minimization of surface roughness (Ra). Among various multi-objective optimization routines, five of them namely Global Criterion Method, Lexicographic Method, Weighted Sum Method, ε – Constraint Method, and Genetic Algorithm are used in this literature. The outcomes of these multi-objective optimization routines are then compared to reflect their relative attractiveness. 

Pareto front obtained in Weighted Sum Method, Global Criterion Method, ε – Constraint Method, Genetic Algorithm, and Lexicographic Method