Application of ANOVA and ANN Technique for Optimize Of CNC Machining Parameters

Authors

  • N.Prabhakar P.G student, Mechanical Engineering Department, MITS, Madanapalle, Indi a.
  • B. Sreenivasulu Assistant Professor Mechanical Engineering Department, MITS, Madan apalle, India.
  • U.Nagaraju P.G student, Mechanical Engineering Department, MITS, Madanapalle, Indi a.

Keywords:

Surface Roughnes, , Material removal rate, ANN (Artificial N eural Network),, ANOVA Analysis of variance and Regression modeling.

Abstract

In the present study, the influence of machining parameters on surfac e 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 mater ial removal rate are examined and also analyzed. Artificial Neural Network and Analysis of variance t echniques are effective tools for analyze and optimize the cutting parameters. Based on taguchi, design of expe riments, 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 t urner 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.

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Published

2021-03-27

Issue

Vol. 1 No. 1 (2014): IJIERT

Section

Articles

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How to Cite

N.Prabhakar, B. Sreenivasulu, & U.Nagaraju. (2021). Application of ANOVA and ANN Technique for Optimize Of CNC Machining Parameters. International Journal of Innovations in Engineering Research and Technology, 1(1), 1-12. https://repo.ijiert.org/index.php/ijiert/article/view/198