A Two-stage Optimization System for Cutting Parameters
Liu Bing-hui
Jiang Xiao-yun
Abstract：Based on the fine boring of the bearing holes of the auto bearing support , Taguchi experiments , grey relational analysis , the back-propagation neural network and particle swarm optimization are employed to optimize the cutting parameters .The two-stage optimization system can rapidly obtain the best cutting parameter settings to improve the quality of components and the stability of processing .The result demon-strates the feasibility and effectiveness of the proposed approach .It provides a novel approach and pathway for mechanical processing enterprises to enhance their competitiveness .
Keywords：cutting parametersTaguchi methodgrey relationback-propagation neural networkparti-cle swarm optimization
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 30-35 )