Effect of Machining Parameters on Surface Roughness in Machining of Hardened AISI 4340 Steel Using Coated Carbide Inserts
Journal: International Journal of Innovation and Applied Studies (Vol.2, No. 4)Publication Date: 2013-04-02
Authors : Das Sudhansu Ranjan; Kumar Amaresh; Dhupal Debabrata;
Page : 445-453
Keywords : AISI 4340 steel; Surface Roughness; Factorial Design; ANOVA;
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 cut-cutting 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.
Other Latest Articles
- Contribution of a GIS to the management of rice project in the north-west of Côte d'Ivoire: the case of Denguele region
- The examination of factors affecting e-learning effectiveness
- Naïve Bayesian Learning based Multi Agent Architecture for Telemedicine
- Performing a pseudo-panchromatic SAR image of Radarsat-1 for lithostructural mapping of the Precambrian basement in Korhogo region (North of Côte d'Ivoire)
- Socio-economic Analysis of Cassava Marketing in Benue State, Nigeria
Last modified: 2013-04-05 09:00:27