Experimental Investigation on machining of Titanium Alloy (Ti 6Al 4V) and Optimization of its Parameters using ANN
Keywords: Surface finish, Titanium alloy, Material removal rate, Design of experiments, Artificial Neural Network (ANN)
AbstractEngineering industries continuously face challenges in maintaining a consistently high product quality in terms of dimensional accuracy and surface finish, sustaining a high production rate, and economical processing of materials by minimizing cutting tool wear, rejections and rework. In this study, turning of Titanium alloy (Ti-6Al-4V) has been taken up for optimizing the material removal rate and surface finish, the reason being its wide application in aerospace industry. Cutting speed, feed rate and depth of cut were assigned as the input variables. Design of experiments based on Taguchi technique and L27 orthogonal array was employed to analyze the experimental data and the predicted values. Analysis of variance was used for identify the input parameter exerting maximum influence on surface finish and MRR. It was observed that the experimental results are in good agreement with the predicted values from DOE and multilayered feed forward Artificial Neural Network employed to predict process responses. The optimal values of the input and output parameters are tabulated.
DESIGN AND OPTIMIZATION OF MECHANICAL SYSTEMS