e-ISSN : 0975-4024 p-ISSN : 2319-8613   
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ABSTRACT

ISSN: 0975-4024

Title : Hybridization of Response Surface Methodology and Genetic Algorithm optimization for CO2 laser cutting parameter on AA6061 material
Authors : A.Parthiban, R.Ravikumar, B.Suresh Kumar, N. Baskar.
Keywords : CO2 Laser cutting, Aluminium alloy, Kerf Dimensions, Response Surface Methodology, Genetic Algorithm
Issue Date : Feb - Mar 2014
Abstract :
Investigation of laser cutting parameters on aluminium alloy (AA6061) is important due to its high reflectivity and thermal conductivity. Generally Aluminium alloy is a widely used material in aeronautical and automation industries for its inherent properties. Although the main problem during laser cutting is occurrence of recasting layer and laser beam incidence that affecting the cutting quality is known as kerf dimensions. In a sense the relationship between the laser cutting parameters such as laser power, cutting speed, gas pressure and focal position with kerf dimensions are having important role in laser cutting operation. So this work considers the response surface methodology (RSM), for making empirical relationship between dependent and independent variables. Simultaneously, this work reveals that laser power, cutting speed, gas pressure and focal position have significant effects on kerf dimension. Thus the development of empirical model and the selection of best parameters is important for manufacturing industries. Hence this work develops the statistical model with RSM and optimizes the cutting parameters with genetic algorithm (GA).
Page(s) : 358-373
ISSN : 0975-4024
Source : Vol. 6, No.1