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IJARI-ME-14-09-106 (1)



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Parametric Analysis of Surface Roughness Studies in Turning Using Artificial
Neural Network
Article
· September 2014
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Ranganath M Singari
Delhi Technological University, Formerly Delhi college of Engineering, Delhi, India
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Vipin vp
Delhi Technological University
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Sonu Yadav
Indian Institute of Information Technology Allahabad
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Volume 2, Issue 3 (2014) 676-683 
ISSN 2347 - 3258
International Journal of Advance Research and Innovation 
676 
IJARI 
Parametric Analysis of Surface Roughness Studies in Turning Using 
Artificial Neural Network 
Ranganath M. S. 
*, a
, Vipin
a
, Sudhanshu Maurya
b
, Sonu Yadav
b
a
Department of Production and Industrial Engineering, Delhi Technological University, New Delhi, India 
b
Department of Mechanical Engineering, Delhi Technological University, New Delhi, India 
 
 
 
 
 
Abstract 
Neural Networks are information processing systems and can be used in several 
areas of engineering applications and eliminate limitations of the classical 
approaches by extracting the desired information using the input data. The 
advantage of the usage of neural networks for prediction is that they are able to 
learn from examples only and that after their learning is finished, they are able 
to catch hidden and strongly nonlinear dependencies, even when there is 
significant noise in the training set. One of the most specified customer 
requirements in a machining process is surface roughness. For efficient use of 
machine tools, optimum cutting parameters are required. Therefore it is 
necessary to find a suitable optimization method which can find optimum 
values of cutting parameters for minimizing surface roughness. The turning 
process parameter optimization is highly constrained and nonlinear. Many 
researchers have used an artificial neural network (ANN) model for the data 
obtained through experiments to predict the surface roughness. The results 
obtained, conclude that ANN is reliable and accurate for solving the cutting 
parameter optimization. The paper work presents on all studies where ANN has 
been used to analyse surface roughness in turning process.

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