Research on Optimization of Cutting Parameters Based on Genetic Algorithm

Abstract:

Three elements of Cutting dosages have a great effect on parts surface quality and working efficiency, the best organization of cutting three elements for parts surface quality must be found before machining, in order to surface roughness and machining cost of parts, multi-objective optimization model is established in this paper, model is solved by using genetic algorithm. Based on the BP neural network of three layers, forecasting model of surface roughness is established. According to existing experiment data and optimized cutting dosages, analysis and prediction of surface roughness is done. Machining experiment is done by using optimized data. The experiment result verifies feasibility of this optimistic method and prediction method of surface roughness.

• Periodical: Applied Mechanics and Materials (Volumes 121-126)
• Pages: 4640-4645
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.121-126.4640
• Online since: October 2011
• Authors: Shu Ren Zhang, Xue Guang Li, Jun Wang, Hui Wei Wang
• Keywords: BP Neural Network (BPNN), Cutting Dosages, Genetic Algorithm (GA), Multi-Objective Optimization (MOP)

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