Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

Okokpujie, Imhade P. and Ikumapayi, O. M. and Okonkwo , Ugochukwu C. and Salawu, Enesi Y. and Afolalu, Sunday A. and Dirisu, Joseph O. and Nwoke , Obinna N. and Ajayi, O. O. (2017) Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools. Open Eng, 7. pp. 461-469.

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Abstract

In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N), feed rate (f), axial depth of cut (a) and radial depth of cut (r). The experiment was designed using central composite design (CCD) in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM). The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

Item Type:	Article
Uncontrolled Keywords:	End Milling; Tool Wear; Minimum quantity lubrication (MQL); Aluminum; Response Surface Methodology
Subjects:	T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery
Divisions:	Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User:	Mrs Hannah Akinwumi
Date Deposited:	20 Aug 2018 09:17
Last Modified:	20 Aug 2018 09:17
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/11388

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