Gra Approach for Multi-objective Optimization of Laser Cutting

Laser cutting is a complex multi-input multi-output machining process. To satisfy different requirements regarding laser cut quality it is necessary to determine optimal laser cutting conditions. This paper demonstrates the application of the grey relational analysis for optimization of different laser cut quality characteristics such as the depth of separation line, drag line separation and burr height. Laser nitrogen cutting of a 3 mm thick AISI 304 stainless steel was performed on a 2.2 kW CO2 laser cutting system. The laser cutting experiment was planned and conducted according to the Taguchi’s L27 experimental design. Four cutting parameters such as laser power, cutting speed, assist gas pressure and focus position were considered for multi-objective optimization. The results indicate that optimized and non-optimized laser cutting conditions produce drastically different cut quality characteristics.