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Journal of Applied Sciences and Environmental Management
World Bank assisted National Agricultural Research Project (NARP) - University of Port Harcourt
ISSN: 1119-8362
Vol. 16, No. 1, 2012, pp. 65-68
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Bioline Code: ja12011
Full paper language: English
Document type: Research Article
Document available free of charge
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Journal of Applied Sciences and Environmental Management, Vol. 16, No. 1, 2012, pp. 65-68
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Empirical model for estimating the surface roughness of machined components under various cutting speed
Osarenmwinda, J.O.
Abstract
The increasing importance of turning operations is gaining new dimensions
in the present industrial age, in which the growing competition calls for all the efforts to be
directed towards the economical manufacture of machined parts as well as surface finish is
one of the most critical quality measure in mechanical products. In the present work,
empirical models for estimating the surface roughness of machined components under
various cutting speed have been developed using regression analysis software. The centre
lathe was used to turn the components (stainless steel, mild steel and aluminum cast) at
different cutting speed ranging between 76 rev/min to 600 rev/ min at a constant depth of
cut of 1 mm/pass and feed rate of 0.5 mm/rev. and surface roughness of machined
components measured with a digital portable surface roughness tester (TR100 Model) using
centre line average method. The values obtained from the empirical models were found to
compare favourably with the experimental values. The Mean Absolute Percent Deviation
(MAPD) which measures absolute error as a percentage was found to be 1.46% (stainless
steel), 4.55 %( mild steel) and 4.76% (aluminum cast) respectively. These values were
insignificant and below the maximum recommended value of 10%. These model
performances were therefore found to be satisfactory and show good predictability.
Keywords
cutting speed, centre lathe, empirical model, surface roughness, Mean absolute percentage deviation
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© Copyright 2012 - Journal of Applied Sciences and Environmental Management
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