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Asian Journal of Research in Social Sciences and Humanities
Year : 2016, Volume : 6, Issue : 8
First page : ( 849) Last page : ( 863)
Online ISSN : 2249-7315.
Article DOI : 10.5958/2249-7315.2016.00654.7

Investigation and Prediction of Material Removal Rate and Surface Roughness in CNC Turning of En24 Alloy Steel

Dinesh S.*, Antony A. Godwin**, Rajaguru K.*, Dr. Vijayan V.*

*Department of Mechanical Engineering, K. Ramakrishnan College of Technology, Tiruchirapalli, Tamil Nadu, India

**Department of Mechanical Engineering, Shivani College of Engineering and Technology, Tiruchirapalli, Tamil Nadu, India

Online published on 2 August, 2016.

Abstract

Every manufacturing or production unit should concern about the quality of the product. Apart from quality, there exists other criterion, called productivity which is directly proportional to the profit level. Every manufacturing industry aims at producing a large number of products in relatively lesser time. In any machining process, it is most important to determine the optimal settings of machining parameters aiming at reduction of production costs and achieving the desired product quality. If the problem is related to a single quality attribute then it is called single objective optimization. If more than one attribute comes into consideration it is very difficult to select the optimal setting which can achieve all quality requirements simultaneously. In this work, EN-24 alloy steel work pieces were turned on Computer Numerical Controlled (CNC) lathe by using Cemented carbide tool (coated). The influence of four cutting parameters, cutting speed, feed rate, depth of cut, and tool nose radius on minuscule surface roughness and material removal rate (MRR) were analyzed on the basis of Response Surface Methodology approach. The experimental results were collected by following the Taguchi's L16 mixed Orthogonal Array design.

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Keywords

MRR, Surface roughness, EN24 alloy steel, Cemented carbide tool, RSM approach.

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