Parameters optimization in belt polishing process of blade based on grey relational analysis

In polishing process of blade and blisk, the minimum of Surface Roughness (SR) and the maximization of Material Removal Rate (MRR) were determined by different process parameters, which could not obtain the optimal result under the condition of empirical parameters. To solve this multi-objective optimization problem, 4-factor and 3-level orthogonal polishing experiments for titanium specimens were designed. Based on the grey relational analysis, the multi-objective optimization problem was converted to single objective problem, and the influence weight of SR and MRR on Grey Relational Analysis (GRA) were calculated. By means of regression analysis of the experimental data, the second order prediction model of GRA was developed. Accordingly, the variation of SR, MRR and GRA resulted from the various polishing parameters such as abrasive size, belt speed, workpiece feed rate and polishing depth were researched. Furtherly, the optimization scheme of polishing parameters was put forward. The polishing process parameters were optimized with response surface methodology, and the polishing experiments of blade were carried out. The experimental results showed that the MRR could be improved significantly under the condition of meeting the SR request.