PARAMETRIC OPTIMIZATION OF LASER ENGRAVING PROCESSES ON STAINLESS STEEL AISI 304.

Abstract

A 15W laser engraving machine was developed from bought-out parts in which AISI 304 stainless steel (SS) is selected as the base material to which the influence of laser processing parameters (laser power, scan speed, exposure time and number of passes) was investigated on selected surface output characteristics/responses (surface roughness, kerf width, engraving depth and material removal rate). Box behnken design of experiment was adopted for creating the design of experiment having four factors and three levels giving 27 orthogonal experimental runs. Laser engraving was performed on the material and AA 3000 scanning probe microscope by means of Atomic Force Microscope (AFM) was used to obtain the surface data. Single response optimization was performed for each of the responses and the best process parameter combination for each was obtained by means of main effect plot. Also, analysis of variance (ANOVA) was employed to show the contributing effect of these process parameters and their interactions. Furthermore, multi-objective optimization was performed by using grey relational approach combined with principal component analysis to obtain the weighting values of the grey relational coefficient needed to obtain Grey Relational Grade (GRG). Based on the high grey relational grade obtained, it was used to ascertain the best combination of process parameter to give the desired target responses. The optimal combination of these process parameters for the multi-objective optimization are (1, 0, 0, -1) which implies 15 W laser power, 28.57 mm/s scan speed, exposure time of 20 ms and (1) no of pass to yield 0.169 nm surface roughness, 3.805 nm engraving depth, 2856.13 nm kerf width and 6.26 (10^11) nm3/s material removal rate. It can be concluded that the integration of grey relational analysis and principal component analysis is a robust approach of investigating multi-objective optimization of processes