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An Investigation on Effect of Depth of Cut, Feed Rate and Tool Nose Radius on Induced Vibration and Surface Roughness during Hard Turning of 41Cr4 Alloy Steel Using Response Surface Methodology

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Abstract:

This paper describes an aspect of a set of turning experiments performed in attempt to model, predict and optimize the machining induced vibration and surface roughness as functions of the machining, tool and work-piece variables during hard turning of 41Cr4 alloy special steel, with standard cutting tool, on a conventional lathe. Amongst others, the input variables of interest include the depth of cut, feed rate and tool nose radius. The response surface methodology, based on central composite design of experiment, was adopted, with analysis performed in Design Expert 9 software environment. Quadratic regression models were suggested, and proved significant by an analysis of variance, for the machining induced vibration of the cutting tool and surface roughness of the work-piece. They also have capability of being used for prediction within limits. Analysis of variance also showed the depth of cut, feed rate and tool nose radius have significant effect on the machining induced vibration and surface roughness. Whereas the depth of cut has dominant effect on the machining induced vibration, the tool nose radius has dominant effect on the surface roughness. The optimum setting of the depth of cut of 1.33095 mm, feed rate of 0.168695 mm/rev, and the tool nose radius of 1.71718 mm is required to minimize the machining induced vibration at 0.08 mm/s2 and surface roughness at 6.056 μmm with a desirability of 0.830.

Info:

Periodical:
International Journal of Engineering and Technologies (Volume 7)
Pages:
32-46
DOI:
10.18052/www.scipress.com/IJET.7.32
Citation:
C. O. Izelu and S. C. Eze, "An Investigation on Effect of Depth of Cut, Feed Rate and Tool Nose Radius on Induced Vibration and Surface Roughness during Hard Turning of 41Cr4 Alloy Steel Using Response Surface Methodology", International Journal of Engineering and Technologies, Vol. 7, pp. 32-46, 2016
Online since:
May 2016
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