Optimizing multi-requirements of surface finishing in magnetic abrasive cutting process using grey relational analysis

Abstract

Mechanical machining inevitably generates undesirable parts on the surface of workpieces. It brings adverse effects in terms of manufacturing cost, surface fineness, malfunction, and lifetime. In order to achieve precise surface with high geometric accuracy, this study proposes a magnetic abrasive cutting (MAC) process to improve surface roughness and make burr-free on the surface of STD-11. All the experiments were conducted by Taguchi’s orthogonal array method with four determined process parameters and three levels. The results analyzed by signal-to-noise (S/N) ratio and analysis of variance (ANOVA) showed that the working gap was the most contribution to the fine surface with 69.9 %, and viscosity of silicone oil affected high geometric precision with 54.1 %. In addition, to satisfy multiple requirements for improving burr removal and surface roughness simultaneously, grey relational analysis (GRA) was employed. From the analysis, the best configuration was at 1.0 mm of the working gap, 600 rpm of spindle speed, 150000 cs of silicone oil, and 1:3 of mixing ratio of abrasive grains and ferromagnetic particles. This study clearly showed that the MAC process assisted by magnetic force was useful to satisfy multi-objective optimization for surface roughness reduction and burr removal.