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As an efficient and fast developing surface finishing technique, polishing processes have been widely used in the machining of aero-engine blisk blade. Since a number of processing input variables will influence surface quality and production time, controlling surface finish and machining efficiency require a carefully designed combination of various processing parameters. Therefore, this paper presented a comprehensive multi-objective parameter optimization method that integrates grey relational analysis (GRA), radial basis function (RBF), as well as firefly algorithm (FA). The purpose is to simultaneously obtain the optimal parameter combination for minimum surface roughness and the greatest material removal rate by optimizing rotational speed, feed rate and polishing force in Ti-6Al-4V blisk blade polishing. The hybrid experiments were carried out by combining the orthogonal experimental design with the single-factor experimental design. GRA was run for converting multi-objective response into the single-objective response. Then, RBF was applied to build the relationship between the grey correlation degree and the control variables. Finally, FA was utilized to obtain the optimal grey correlation degree in the range of control variables. The verification tests showed the highest material removal rate of 5.370Formula: see textmm 2 /s and surface quality of 0.374Formula: see textFormula: see textm have been successfully achieved.
Chen et al. (Mon,) studied this question.
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