STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Advancements in Robotics

Optimization and Modelling of Process Parameters for Turning Operation on Cnc Lathe for ASTM A242 Type-2 Alloy Steel by Regression Analysis and Artificial Neural Network

  1. Vijay A. Bhagora
  2. Saurabh P. Shah

Abstract

The purpose of this project is focussed on the modelling of cutting conditions to get the lowest surface roughness in turning ASTM A242 TYPE-2 ALLOYS STEEL by Artificial Neural Network and Regression Analysis method on the CNC lathe. The process of metal cutting has been well researched over the years; relatively small research has been carried out on the cutting of alloy of ASTM A242 grade materials. In this study, the effect and modelling of machining parameters cutting speed, feed rate and depth of cut and tool nose radius on surface roughness will be checked.Keywords: ASTM A242, CNC, turning process, artificial neural network, regression analysis, surface roughness Cite this ArticleBhagora A. Vijay, Shah P. Saurabh. Modelling and Optimization of Process Parameters for Turning Operation on CNC Lathe for ASTM A242 Type-2 Alloy Steel by Artificial Neural Network and Regression Analysis. Journal of Advancements in Robotics. 2015; 2(2): 40–51p.
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