NOVATEUR PUBLICATIONS NOVATEUR PUBLICATIONS NOVATEUR PUBLICATIONS NOVATEUR PUBLICATIONS INTERNATIONAL JOURNAL OF INNOVATIONS IN ENGINEERING RESEARCH AND TECHNOLOGY [IJIERT] INTERNATIONAL JOURNAL OF INNOVATIONS IN ENGINEERING RESEARCH AND TECHNOLOGY [IJIERT] INTERNATIONAL JOURNAL OF INNOVATIONS IN ENGINEERING RESEARCH AND TECHNOLOGY [IJIERT] INTERNATIONAL JOURNAL OF INNOVATIONS IN ENGINEERING RESEARCH AND TECHNOLOGY [IJIERT] VOLUME 1, ISSUE 1 NOV VOLUME 1, ISSUE 1 NOV VOLUME 1, ISSUE 1 NOV VOLUME 1, ISSUE 1 NOV-2014 2014 2014 2014 1 | Page Application of ANOVA and ANN Technique for Optimize Of CNC Machining Parameters N.Prabhakar P.G student, Mechanical Engineering Department, MITS, Madanapalle, India. n.prabhakar88@gmail.com B. Sreenivasulu Assistant Professor Mechanical Engineering Department, MITS, Madanapalle, India. sreenivasulub@mits.ac.in U.Nagaraju P.G student, Mechanical Engineering Department, MITS, Madanapalle, India. Abstract: In the present study, the influence of machining parameters on surface roughness and material removal rate is examined by utilizing ANN& ANOVA techniques. Three important variables i.e. spindle velocity, depth of cut and feed rate which are influence on the surface roughness and material removal rate are examined and also analyzed. Artificial Neural Network and Analysis of variance techniques are effective tools for analyze and optimize the cutting parameters. Based on taguchi, design of experiments, L27 orthogonal array was selected for conducting turning experiments. 3 factors are considered at 3 levels for orthogonal array L27 design. The experimentation has been conducted on Aluminum alloy AL 6253 using CNC turner with carbide tip tool and experimental results are taken for preparing of the ANN model. The experimental results were analyzed by using ANOVA and the regression equation for predicting the surface roughness and MRR. Keywords: Surface Roughness, Material removal rate, ANN (Artificial Neural Network), ANOVA Analysis of variance and Regression modeling. INTRODUCTION AND LITERRATURE REVIEW Material removal rate and Surface roughness are very significant factors in cutting process as one of these factors will involve in the economic justification of the process and other to decide the product quality. Turning operation is a material removal process for which is used to generate cylindrical parts by removing the extra material as shown in Fig. 1. The major process parameters in turning operation are speed, feed and depth of cut. In the present work surface roughness and material removal rate are the output responses. The Taguchi technique is used to design the experiments and to examine various process parameters (cutting velocity, feed rate and depth of cut) influence on output responses. Fig. 1: Representation of figure during Turning Process Taguchi orthogonal array (TOA) offers the way of leading the base number of investigations that gives the full data of every last one of elements that influence parameters. As per the Taguchi information, the choice of orthogonal Array (OA) depending on upon the degree of freedom (DOF) of the procedure and level of opportunity can be processed. of= (number of levels-1) for each one control factor+ (number of levels for A-1) × (number of