Abstract—Inconel 718, a nickel based super alloy is an extensively used alloy in the aerospace industry, marine industry, steam turbine power plants. It is difficult to cut material due to its properties like low thermal conductivity, work hardening etc and retains its strength at high temperatures. Due to low mach inability of this material the worked surface and subsurface are easily effected during machining operations. Therefore surface finish plays a vital role in machining Inconel 718. The objective of this paper is to obtain optimal turning process parameters like cutting speed, feed, and depth of cut resulting in an optimal value of surface roughness for machining Inconel 718 with Cubic Boron Nitride (CBN10) tool insert using Taguchi’s design of experiments approach. The experiments are carried out using L9 orthogonal array. Artificial Neural Networks is used to validate the experimental results.
Index Terms—Surface roughness, dry turning, Inconel 718, CBN cutting tool, artificial neural network.
M. V. R. D. Prasad is with the Department of Mechanical Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Bachupally, Hyderabad (e-mail: dpmandava.vnr@gmail.com )
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Cite: M. V. R. D. Prasad, Yelamanchili Sravya, and Karri Sai Tejaswi, "Study of the Influence of Process Parameters on Surface Roughness When Inconel 718 Is Dry Turned Using CBN Cutting Tool by Artificial Neural Network Approach," International Journal of Materials, Mechanics and Manufacturing vol. 2, no. 4, pp. 335-338, 2014.
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