Parameter Optimization of Polishing M300 Mold Steel with an Elastic Abrasive

Xiao-Jun Wu, Xin Tong, Hao Sun, Huibo Jia and Lu Zhang

Mathematical Problems in Engineering, 2018, vol. 2018, 1-9

Abstract:

In order to achieve high-quality polishing of M300 mold steel curved surface, an elastic abrasive is introduced in this paper, and its polishing parameters are optimized so that the mirror roughness can be achieved. Based on the Preston equation and Hertz contact theory, the theoretical material removal equation for surface polishing of elastic abrasives is obtained, and the polishing parameters to be optimized are as follows: particle size S, rotational speed Wt, cutting depth Ap, and feed speed Vf. The Taguchi method is applied to design the orthogonal experiment with four factors and three levels. The influence degree of various factors on the roughness of the polished surface and the combination of parameters to be optimized were obtained by the range analysis method. The particle swarm optimization algorithm optimizes the BP neural network algorithm (PSO-BP), which is used to optimize the polishing parameters. The results show that the rotational speed has the greatest influence on the roughness, the influence degree of abrasive particle size is greater than that of feed speed, and the influence of cutting depth is the least. The optimum parameters are as follows: particle size S 1200#, rotational speed Wt 4500rpm, cutting depth Ap 0.25mm, and feed speed Vf 0.8mm/min. The roughness of the surface polishing with optimum parameters is reduced to 0.021 μ m.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3965405

DOI: 10.1155/2018/3965405

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