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A R T I C L E I N F O A B S T R A C T Article history: Received: 10 August, 2020 Accepted: 11 September, 2020 Online: 21 September, 2020 In this paper, the multi-objective optimization process was applied for the surface grinding process of 3X13 steel using an aluminum oxide grinding wheel (WA46J7V1A). For each experiment, three cutting parameters, including the workpiece velocity, feed rate, and the depth of cut, were controlled to change according to the experimental matrix. At each experiment, surface roughness and vibrations of the technology system in three directions (X, Y, and Z) were measured and analyzed. The surface roughness and vibration amplitudes were modeled as a quadratic function of workpiece velocity, feed rate, and the depth of cut. The General Reduced Gradient (GRG) algorithm and Harmonic Mean (HM) method were combined to solve the multi-objective optimization problem about the surface grinding process of 3X13. The optimized values of surface roughness and vibration amplitudes (in X, Y, Z directions) were 0.901 μm, 0.815 μm, 1.594 μm, and 0.599 μm, respectively. These results that were determined at the cutting conditions were workpiece velocity of 14.428 m/min, the feed rate of 5.789 mm/stroke, and cutting depth of 0.013 mm. By conducting the grinding process at the optimal values of grinding conditions, the experimental results of surface roughness and system vibration amplitudes were quite close to that one of the predicted results. This proposed approach can be applied to improve the machining quality of the surface grinding process of 3X13 steel.

Multi-Objective Optimization when Surface Grinding the 3X13 Steel by Combining the General Reduced Gradient Algorithm and Harmonic Mean Method