Multi-objective optimization of fiber laser cutting of stainless-steel plates using taguchi-based grey relational analysis

Abstract

Stainless-steel has become a widely preferred material type in the marine, aerospace, sanitary, industrial equipment, and construction industries due to its superior corrosion resistance, high mechanic properties, high strength, formability, and thermal and electrical conductivity. In this study, a multi-objective optimization method based on grey relational analysis was employed to optimize the fiber laser-cutting parameters of cutting speed, focal position, frequency, and duty cycle. Surface roughness and kerf width, which are the two most important parameters that determine laser-cutting quality, were simultaneously optimized. In order to assign the optimum level of each parameter individually, the Taguchi technique was applied. The cutting surface morphology was examined according to the grey relational grade with a 3D optical profilometer, and maps of the cutting surfaces were created. According to the results achieved using Analysis of Variance (ANOVA), it was seen that the parameters that affected surface roughness and kerf width the most were duty cycle, with a contribution rate of 49.01%, and frequency, with a contribution rate of 31.2%. Frequency was the most important parameter in terms of multiple responses, with a contribution rate of 18.55%. Duty cycle and focal position were the second and third most effective parameters, respectively. It was determined that the optimum parameter values for minimum surface roughness and minimum kerf width that could be obtained with the fiber laser cutting of 20 mm thick AISI 304L (DIN EN 1.4301) material were 310 mm/min cutting speed, -11 mm focal position, 105 Hz frequency, and 60% duty cycle.