A model for predicting surface roughness in single-point diamond turning

Abstract The relative tool-work vibration is not generalized enough to represent the actual displacement between tool and workpiece in previous prediction models. This is due to the fact that the vibration was assumed as a steady simple harmonic motion and was only measured before turning process. In this study, an improved method is presented to evaluate the actual relative tool-work vibration. By using this method the vibration information obtained is more credible, as it contains the components caused by machine tool error, cutting force, material property and changing of cutting parameters. Moreover, the swelling effect is analyzed using a new evaluating method and taken into account for predicting surface roughness. On the basis of analyzing both the relative vibration and the swelling effect, a model is proposed for predicting surface roughness R a in single point diamond turning. Prediction results prove that this model is a closer approximation of the actual turning process as compared to the previous models and shows a higher predicting accuracy of surface roughness.

[1]  Pramod Kumar Jain,et al.  In-process prediction of surface roughness in turning of Ti–6Al–4V alloy using cutting parameters and vibration signals , 2013 .

[2]  Chi Fai Cheung,et al.  Modelling and simulation of surface topography in ultra-precision diamond turning , 2000 .

[3]  Habibollah Haron,et al.  Prediction of surface roughness in the end milling machining using Artificial Neural Network , 2010, Expert Syst. Appl..

[4]  C. Cheung,et al.  A multi-spectrum analysis of surface roughness formation in ultra-precision machining , 2000 .

[5]  N. M. Rao,et al.  Prediction of cutting tool wear, surface roughness and vibration of work piece in boring of AISI 316 steel with artificial neural network , 2014 .

[6]  Takashi Nishiguchi,et al.  Influence of Study Vibration with Small Amplitude Upon Surface Roughness in Diamond Machining , 1985 .

[7]  Chi Fai Cheung,et al.  A theoretical and experimental investigation of the tool-tip vibration and its influence upon surface generation in single-point diamond turning , 2010 .

[8]  George-Christopher Vosniakos,et al.  Predicting surface roughness in machining: a review , 2003 .

[9]  Durmus Karayel,et al.  Prediction and control of surface roughness in CNC lathe using artificial neural network , 2009 .

[10]  Stephen C. Veldhuis,et al.  Effect of material microstructure and tool geometry on surface generation in single point diamond turning , 2014 .

[11]  Hiroyuki Hiraoka,et al.  Analysis of Surface Roughness Generation in Turning Operation and its Applications , 1985 .

[12]  S. Melkote,et al.  Effect of plastic side flow on surface roughness in micro-turning process , 2006 .

[13]  C. Cheung,et al.  Materials induced vibration in ultra-precision machining , 1999 .

[14]  Chi Fai Cheung,et al.  A study of materials swelling and recovery in single-point diamond turning of ductile materials , 2006 .

[15]  Tarek Mabrouki,et al.  On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations , 2013 .

[16]  Chi Fai Cheung,et al.  A dynamic surface topography model for the prediction of nano-surface generation in ultra-precision machining , 2001 .