A Multi-objective Optimization Approach for Improving Machining Performance Using the General Algebraic Modelling System (GAMS)

Machining performance can be assessed through indicators such as cutting force and surface roughness. These indicators can be predicted and optimized by adjusting parameters such as the cutting speed, the feed rate and the depth of cut. Several studies have pointed out the conflicting nature of cutting force and surface roughness when attempting to optimize them simultaneously. Unlike previous studies, the machinability performance is analysed in this work using an improved version of the augmented ε-constraint approach that takes cutting force and surface roughness into account as objective functions. In order to illustrate the approach proposed in this study, quadratic equations were extracted from an existing study related to a CNC lathe machine. These equations relate variables such as cutting speed, the feed rate and the depth of cut to the cutting force and surface roughness considered as objective functions in the mathematical programming formulation. The General Algebraic Modeling System (or GAMS) was used to construct and implement the Non-Linear Problem. The proposed new multi-objective approach provides accurate Pareto sets that correspond to the optimal setting of the CNC lathe machine. In addition, this study provide clarity on the implication of an adjustment of machining parameters to optimize machining performance.