Prediction of cutting force, tool wear and surface roughness of Al6061/SiC composite for end milling operations using RSM

The results of mathematical modeling and the experimental investigation on the machinability of aluminium (Al6061) silicon carbide particulate (SiCp) metal matrix composite (MMC) during end milling process is analyzed. The machining was difficult to cut the material because of its hardness and wear resistance due to its abrasive nature of reinforcement element. The influence of machining parameters such as spindle speed, feed rate, depth of cut and nose radius on the cutting force has been investigated. The influence of the length of machining on the tool wear and the machining parameters on the surface finish criteria have been determined through the response surface methodology (RSM) prediction model. The prediction model is also used to determine the combined effect of machining parameters on the cutting force, tool wear and surface roughness. The results of the model were compared with the experimental results and found to be good agreement with them. The results of prediction model help in the selection of process parameters to reduce the cutting force, tool wear and surface roughness, which ensures quality of milling processes.

[1]  P. V. Rao,et al.  Selection of optimum tool geometry and cutting conditionsusing a surface roughness prediction model for end milling , 2005 .

[2]  Liangchi Zhang,et al.  Prediction of cutting forces in machining of Metal Matrix Composites , 2006 .

[3]  K. Palanikumar,et al.  Modeling and analysis for surface roughness in machining glass fibre reinforced plastics using response surface methodology , 2007 .

[4]  Yuji Sugiyama,et al.  Experimental Analysis of Chatter Vibration in End-Milling Using Laser Doppler Vibrometers , 2008, Int. J. Autom. Technol..

[5]  Joseph C. Chen,et al.  Tool condition monitoring in an end-milling operation based on the vibration signal collected through a microcontroller-based data acquisition system , 2008 .

[6]  O. Çakır,et al.  Investigation of mechanical and machinability properties of SiC particle reinforced Al-MMC , 2008 .

[7]  V. K. Jain,et al.  Development of a cutting tool condition monitoring system for high speed turning operation by vibration and strain analysis , 2008 .

[8]  Min-Yang Yang,et al.  Experimental study of surface integrity during end milling of Al/SiC particulate metal–matrix composites , 2008 .

[9]  J. Paulo Davim,et al.  Optimization of machining parameters of Al/SiC-MMC with ANOVA and ANN analysis , 2009 .

[10]  A. R. Daud,et al.  PREPARATION AND CHARACTERIZATION OF STIR CAST-ALUMINUM NITRIDE REINFORCED ALUMINUM METAL MATRIX COMPOSITES , 2009 .

[11]  Tae-Il Seo,et al.  Indirect cutting force measurement in the micro end-milling process based on frequency analysis of sensor signals , 2010 .

[12]  Tamás Insperger,et al.  Analysis of directional factors in milling: importance of multi-frequency calculation and of the inclusion of the effect of the helix angle , 2010 .

[13]  K. Ravishankar,et al.  Mechanical properties of fly ash reinforced aluminium alloy (Al6061) composites , 2011 .

[14]  P. S. Sivasakthivel,et al.  Prediction of vibration amplitude from machining parameters by response surface methodology in end milling , 2011 .

[15]  Tarek Mabrouki,et al.  Modeling and optimization of hard turning of X38CrMoV5-1 steel with CBN tool: Machining parameters effects on flank wear and surface roughness , 2011 .

[16]  Sudhir Kumar,et al.  Effect of turning parameters on surface roughness of A356/5% SiC composite produced by electromagnetic stir casting , 2012 .

[17]  Nouredine Ouelaa,et al.  Analysis and prediction of tool wear, surface roughness and cutting forces in hard turning with CBN tool , 2012 .