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Statistical approach for optimization of influencing parameters in laser assisted machining (LAM) of Inconel alloy
Published in Elsevier BV
Volume: 89
Pages: 97 - 108
Laser assisted machining (LAM) is one of the innovative methods to machine difficult to cut materials to obtain maximum benefits of machinability. In this method, the influence of both the laser and cutting parameters affects the quality of machining. Hence it is required to identify the optimal levels of the parameters in order to maximize benefits. The present study focused on optimization of laser beam approach angle, laser power and cutting parameters during LAM of Inconel 718 alloy using chemical vapour deposition (CVD) coated carbide tool. The experimental trials are planned in accordance with central composite design (CCD) in response surface methodology. The ranges for selected parameters are as follows as: cutting speed (50 < Vc < 100 m/min), feed rate (0.05 < f < 0.1 mm/rev), laser power (1.25 < PL < 1.75 kW), and approach angle (60° < θ < 90°). Cutting force and workpiece temperature, the two responses which are measured using Kistler force dynamometer and infra-red pyrometer respectively. The effects of each parameter were analysed using 3D surface plot and analysis of variance (ANOVA). A second order regression equation has been developed and model shows good agreement with experimental and predicted results. Desirability function analysis (DFA) is used to determine the optimal operating conditions. Finally, the results were validated using confirmation experiments. © 2016 Elsevier Ltd.
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