Multiple quality optimization in laser cutting of difficult-to-laser-cut material using grey–fuzzy methodology

Abstract

This paper investigates the laser cutting performance of 1 mm Duralumin sheet with the aim to improve quality of cut by simultaneously optimising multiple performances such as cut edge surface roughness, kerf taper and kerf width. The experimental data obtained by Taguchi methodology-based L27 orthogonal array experimentation have been used in the hybrid approach optimization of grey relational analysis and fuzzy logic theory. The predicted optimum results have been verified by conducting confirmation experiments. The verification results show an overall improvement of 19 % in multiple quality characteristics. The effects of significant factors on quality characteristics have also been discussed.