alexa Optimization of Sustainable Cutting Conditions in Turning Carbon Steel by CNC Turning Machine
ISSN: 2169-0022

Journal of Material Sciences & Engineering
Open Access

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Research Article

Optimization of Sustainable Cutting Conditions in Turning Carbon Steel by CNC Turning Machine

Mohammad HM1 and Ibrahim RH2*

1Materials Engineering Department, College of Engineering, University of Basrah, Iraq

2Mechanical Engineering Department, College of Engineering, University of Basrah, Iraq

*Corresponding Author:
Ibrahim RH
Mechanical Engineering Department
College of Engineering
University of Basrah, Iraq
Tel: 009647801015687
E-mail: [email protected]

Received Date: December 23, 2016; Accepted Date: January 24, 2017; Published Date: February 04, 2017

Citation: Mohammad HM, Ibrahim RH (2017) Optimization of Sustainable Cutting Conditions in Turning Carbon Steel by CNC Turning Machine. J Material Sci Eng 6: 319. doi: 10.4172/2169-0022.1000319

Copyright: © 2017 Mohammad HM, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

The current study aims to find the optimum cutting parameters in turning process without using cutting fluids (dry cutting condition) towards sustainable manufacturing. Where the power consumption and environmental pollution increase due to increase of the machining operations in manufacturing field, so to save energy and environment and reduce cost it is important to adopt sustainability in machining processes. The experimental work in this study involves the preparation to a number of experiments on AISI 1045 carbon steel to collect the necessary data for implementing optimization process. The experiments were conducted by changing levels of cutting parameters (spindle speed, feed rate and cutting depth) in CNC turning machine. Surface roughness of the workpiece has been depended as a quality indicator. In addition, the temperature of cutting tool has been recorded during machining the work pieces in order to control the temperature of cutting process. Theoretically, empirical equations for temperature of cutting tool and surface roughness of the work piece have been discovered. By using Genetic Algorithm technique these equations have been used to find the optimum of cutting parameters spindle speed, feed rate and depth of cut. The optimum values that obtained by using Genetic Algorithm which achieve sustainable cutting were spindle speed 588.96 rpm, depth of cut 0.50 mm and feed rate 64.55 mm/min in order to have the optimum of surface roughness in low cutting temperature.

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