Optimization of precision grinding parameters of silicon for surface roughness based on taguchi method

Silicon being a typical hard-brittle material is difficult to machine to a good surface finish. Although ductile-mode machining (DMM) is often employed to machine this advanced material but this technique requires the use of expensive ultra-precision machine tools therefore limiting its applicability. However, by proper selection of grinding parameters, precision grinding which can be performed on conventional machine tools can be used to generate massive ductile surfaces thereby reducing the polishing time and improving the surface quality. Precision grinding should be planned with reliability in advance and the process has to be performed with high rates of reproducibility. Therefore, this study investigated the effect and optimization of grinding parameters using Taguchi optimization technique during precision grinding of silicon. Experimental studies were conducted under varying depths of cut, feed rates and spindle speeds. An orthogonal array (OA), signal-to-noise (S/N) ratio and the analysis of variance (ANOVA) were employed to find the minimum surface roughness value and to analyze the effect of the grinding parameters on the surface roughness. Confirmation tests were carried out in order to illustrate the effectiveness of the Taguchi method. The results show that feed rate mostly affected the surface roughness. The predicted roughness (Ra) of 34 nm was in agreement with the confirmation tests. Massive ductilestreaked surface was also found corresponding to the minimal surface finish determined from the optimal levels