Experimental investigation on performance characteristics of A653 Galvanized sheet steel using Fiber laser cutting process

Abstract

In laser beam cutting process the cut quality is most important. The quality of laser cut is determined by the kerf width and kerf deviation. Nowadays industries are demanding uniform kerf with minimum kerf width. The present work explores the modelling and optimization of laser beam cutting process parameters during fiber laser cutting of A653 Galvanized steel sheet for straight cut using different optimization techniques. The four input process parameters gas pressure, power, frequency and feed rate are investigated to check their effect on quality characteristics like kerf width (KW), kerf deviation (KD) and material removal rate (MRR) have been taken for the experimentation work. The multi-response optimization of process parameters has been done to improve geometrical accuracy by minimizing the kerf width and kerf deviation. Response surface methodology (RSM) technique was used to optimize the process parameters with considering the interactions. The Box–Behnken design had been utilized to plan the experiments, and response surface methodology was employed for developing the empirical models. The desirability function approach has been used for multi-response optimization. The predicted optimum result has been validated by performing the confirmation test. The confirmation result showed the percentage prediction error in kerf width, kerf deviation and MRR were 5.12 %, 5.88 % and 2.56 % respectively. Result shows the predicted model is adequate. Taguchi based fuzzy logic technique was used to optimize the process parameters assuming no interaction between the factors. The experiments were planned according to the Taguchi’s experimental design L27 Orthogonal Array. The S/N ratios taken for the KW and KD is of the smaller-the-better type and MRR is of the higher the better type . The predicting fuzzy logic model is implemented on Fuzzy Logic Toolbox of MATLAB using Mamdani technique. The fuzzy logic theory has been applied to compute the fuzzy multi-response performance index (FMRPI). This performance index was further used for multi-objective optimization. The predicted optimum results have been validated by performing the confirmation tests. The confirmation tests showed the considerable reduction in kerf width, kerf deviation and increase in material removal rate. Scanning electron microscope and Energy dispersive spectroscopy has been done to analyses HAZ and recast layer formation for the selected laser machined samples. It has been concluded that average thickness value of HAZ is increased as increase in power and frequency. The formation of recast layer decreases as gas pressure increases, the size of recast layer mainly depends on gas pressure.