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In laser cutting, the capability of laser cutting mainly depends on optical and thermal properties of work material. The surface quality and metallurgical properties of the product is most important from the point of laser cutting quality. The present research work explores the modeling and optimization of laser beam cutting process parameters by using hybrid approach of Taguchi based fuzzy logic. The multi-response optimization of process parameters has been done to improve geometrical accuracy by minimizing the kerf width and kerf deviation. The four input parameters power, gas pressure, feed rate, pulse frequency and three output parameters kerf width (KW), kerf deviation (KD) and material removal rate (MRR) have been taken for the experimentation work. 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 is further used for multi-objective optimization. The selected samples were analyzed using scanning electron microscope. The predicted optimum results have been validated by performing the confirmation tests. The confirmation tests showed the considerable reduction in kerf deviation and increase in material removal rate.

Experimental Investigation of Multiple Quality Characteristics of Laser Beam Machined Surface using Integrated Taguchi and Fuzzy Logic Method