Predictive modeling and multi objective optimization of Al 6063 for engraving depth and surface roughness using grey relational and regression analysis

The goal of this experiment is to investigate the effect of laser engraving parameters on Al 6063 aluminum alloy specimens using a fiber laser engraving equipment. The experimental design makes use of Taguchi's L16 orthogonal array. Surface roughness and engraving depth are the responses which are to be optimum for machining process parameters such as fill spacing, power, frequency, and scan speed. Using regression analysis, the mathematical models for individual responses were created. Grey relational analysis coupled with the Taguchi technique has been presented for simultaneous response optimization. The optimal setting parameters for multiple performance characteristics is fill spacing at level-3, power at level-4, frequency at level-2 and scan speed at level-4 i.e., FS3-P4-F2-SS4. To determine the significance of the models, the Analysis of Variance (ANOVA) approach is used. Finally, in the confirmation test, it is observed that the grey relational grade is improved from the initial process parameter combination.