Showing 2 results for Surface Roughness
S. R. Das, D. Dhupa, A. Kumar,
Volume 3, Issue 1 (3-2013)
Abstract
Turning of hardened steels using a single point cutting tool has replaced the cylindrical grinding now as it
offers attractive benefits in terms of lower equipment costs, shorter set up time, fewer process setups,
higher material removal rate, better surface quality and elimination of cutting fluids compared to cylindrical
grinding. In order to obtain desired surface quality by machining, proper machining parameters selection is
essential. This can be achieved by improving quality and productivity in metal cutting industries. The
present study is to investigate the effect of machining parameters such as cutting speed, feed and depth of
cut on surface roughness during dry turning of hardened AISI 4340 steel with CVD
(TiN+TiCN+Al2O3+ZrCN) multilayer coated carbide inserts. A full factorial design of experiment is
selected for experimental planning and the analysis of variance (ANOVA) has been employed to analyze
the significant machining parameters on surface roughness during turning. The results showed that feed
(60.85%) is the most influencing parameter followed by cutting speed (24.6%) at 95% confidence level.
And the two-level interactions of feed-cutting speed (F*V), depth of cut-feed (D*F) and depth of cutcutting
speed (D*V) are found the significant effects on surface roughness in this turning process.
Moreover, the relationship between the machining parameters and performance measure i.e. surface
roughness has been modeled using multiple regression analysis.
S.r Das, R.p. Nayak, D. Dhupal, A. Kumar,
Volume 4, Issue 3 (9-2014)
Abstract
The current experimental study is to investigate the effects of process parameters (cutting speed, feed rate
and depth of cut) on performance characteristics (surface roughness, machining force and flank wear) in
hard turning of AISI 4340 steel with multilayer CVD (TiN/TiCN/Al2O3) coated carbide insert. Combined
effects of cutting parameter (v, f, d) on performance outputs (Ra, Fm and VB) are explored employing the
analysis of variance (ANOVA). An L9 Taguchi standard design of experiments procedure was used to
develop the regression models for machining responses, within the range of parameters selected. Results
show that, feed rate has statistical significance on surface roughness and the machining force is influenced
principally by the feed rate and depth of cut whereas , cutting speed is the most significant factor for flank
wear followed by cutting speed. The desirability function approach has been used for multi-response
optimization. Based on the surface roughness, machining force and flank wear, optimized machining
conditions were observed in the region 147 m/min cutting speed and 0.10 mm/rev feed rate and 0.6 mm
depth of cut.
