Multi-objective Grey Wolf Optimizer for Improved Machining Performance

Real engineering difficulties come in a variety of forms, each requiring a unique set of tools to solve. Multi-objectivity is one of the key elements of real situations that makes them difficult to solve. In this section, the machinability performance problem is studied using two indicators namely the cutting force and the surface roughness. The speed of cutting, the feed rate and the depth of cut are the parameters, describing the setting of the CNC lathe machine, to optimize. In this study, titanium alloy (Ti–6Al–4V) was chosen as the turning work material. 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 grey wolf optimizer. Details showing the formulation of the problem and the results have been disclosed. The Multi-objective grey wolf optimizer (MOGWO) 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.