Multi-objective Ant Lion Optimizer for Improved Machining Performance

Titanium alloys are challenging to cut due to low thermal conductivity and excessive tool wear. This work seeks to address poor machinability through optimization. In this section, titanium alloy (Ti–6Al–4V) was chosen as the turning work material. The cutting force and the surface roughness were considered indicators of the machining performance. The speed of cutting, the feed rate and the depth of cut are the variables to optimize. Quadratic equations of the cutting force and the surface roughness were extracted from an existing study to illustrate the approach. A single objective optimization problem was developed to optimize the cutting force and the surface roughness separately using the Antlion optimizer. Details showing the formulation of the problem and the results have been disclosed. The Multi-objective antlion optimizer (MALO) was the metaheuristic-based approach proposed for the formulation of the problem and the computation of the non-dominated or Pareto optimal solutions. The best compromise was obtained by optimizing these two objectives simultaneously. The optimal settings corresponding to the optimal values of cutting force and surface roughness were computed and reported in this section.