Multi-objective Optimization of Laser Cutting Parameters Using Particle Swarm Optimization (PSO)

Studies have shown that unconventional machining offers advantages when it comes to machining ceramics in the form of higher material removal rate (MRR) and better surface finish. This present study focuses on the experimental investigations using a fibre laser to cut 7 mm thick ceramic plates used as glazed floor tiles. It involved a systematic experimental study to determine the relationships between process parameters and machining characteristics. Based on the experimental results, regression equations are developed to estimate the responses as functions of the laser process parameters and gas pressure. The developed regression equations are then used in a particle swarm optimization (PSO) technique with a MATLAB algorithm to minimize glass formation and taper angle in the cutting region which, in turn, improves productivity and surface finish. The optimal parameters of the process are found based on the minimization of the taper angle with relatively low operating energy cost.