Comparison of Taguchi method and grey relational analysis method in process parameter optimization for shear thickening polishing of YAG crystal

The shear thickening polishing (STP) method is a gentle polishing method developed in recent years. In this work, a high-efficiency polishing of yttrium aluminum garnet (YAG) crystals with good surface quality were accomplished using this technique. Analysis was done on the impacts of four main polishing parameters on surface roughness S a and material removal rate (MRR), namely, abrasive particle size S , abrasive particle concentration C , polishing speed Vw , and workpiece polishing angle θ. The Taguchi method and grey relational analysis method were used respectively to optimize the process parameters to decrease the surface roughness S a and improve MRR in the polishing process. An orthogonal experiment with four factors and four levels was carried out. The optimal process parameter combination obtained by the Taguchi method was as follows: abrasive particle size 5000#, abrasive particle concentration 15 wt%, polishing speed 60 r/min, and polishing angle 15°. Surface roughness S a decreased from 100 ± 10 nm to 1.024 nm, with MRR 243.03 nm/min in 40 min of polishing under the optimized conditions. Principal component analysis was applied to grey relational analysis to evaluate the weight values of surface roughness S a and MRR. The optimal process parameters were obtained: abrasive particle size 3000#, abrasive particle concentration 6 wt%, polishing speed 100 r/min, and polishing angle 16.06°. Surface roughness was reduced to 0.813 nm, with MRR 377.19 nm/min in 40 min of polishing. The grey relational analysis method produced a lower surface roughness S a and higher MRR in the STP process of YAG crystal compared to the Taguchi method.