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Parametric Optimization of Cutting Parameters of Laser Assisted Cutting Using Taguchi Analysis and Genetic Algorithm

Sandeep Kumar Singh*, Swati Gangwar**

* PG Scholar, MMMUT, Gorakhpur, Uttar Pradesh, India.

** Assistant Professor, MMMUT, Gorakhpur, Uttar Pradesh, India.

Periodicity:February - April'2016
DOI : https://doi.org/10.26634/jfet.11.3.5924

Abstract

Laser Beam Machining (LBM) is one of the most advanced machining processes that is used for shaping, cutting and machining the virtually whole varieties of engineering materials. In LBM, the surface roughness and kerf taper significant factors affects the product characteristics and quality of the product. During this analysis work, the impact of process parameters like cutting speed, frequency and Gas pressure surface roughness (Ra) of steel (AISI 321 stainless steel) material in laser cutting machining are studied. L9 orthogonal array was generated for fractional factorial design (Taguchi analysis) for better understanding of the interaction among the process parameters. The values of surface roughness for steel were calculated by Regression model equations, and Taguchi Analysis and Genetic Algorithm were employed to the parametric analysis of the experimental data. Taguchi analysis gives the optimum values of surface roughness and kerf taper, which are 2.2981 μm and 0.1637° respectively. Genetic algorithm was used for providing a set of optimum values for both outputs simultaneously.

Keywords

Laser Beam Machining (LBM), Surface Roughness, Kerf Taper, Taguchi Analysis, Genetic Algorithm

How to Cite this Article?

Singh, S. K., and Gangwar, S. (2016). Parametric Optimization of Cutting Parameters of Laser Assisted Cutting Using Taguchi Analysis and Genetic Algorithm. i-manager’s Journal on Future Engineering and Technology, 11(3), 36-42. https://doi.org/10.26634/jfet.11.3.5924

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