Abstract
Data timeliness of cutting process data is so intenser under the new situation than ever .It’s especially necessary to propose the physical model on which the optimization of cutting parameters is based. In this paper the mathematical model is established by the analysis of the data measured from the cast iron experiments, then use MATLAB genetic algorithm analysis to calculate the optimum combination of cutting parameters. The results show that the optimum combination of cutting parameters could improve the production efficiency in practice.
Publisher
Trans Tech Publications, Ltd.
Reference7 articles.
1. Chen Zhitong, Zhang Baoguo. Cutting parameters optimization model of facing the unit of cutting process, [J]. Journal of mechanical engineering, 2009. 5.
2. Wen-Hsien Ho, Jinn-Tsong Tsai, Bor-Tsuen Lin, Jyh-Horng Chou. Adaptive network based fuzzy inference system for prediction of surface roughness in end milling process using hybrid Tagnchi-genetic learning algorithm, [J].Export Systems with Applications, 2009(36): 3216—3222.
3. Zhen Shaohua, Jiang Fenghua. Experimental design and data processing, [M]. Beijing: China building materials industry press, (2004).
4. Franci Cus, Joze Balic.Optimization of cutting process by GA approach, [J].Robotics and Computer Integrated Manufacturing, 2003, 19: 113—121.
5. Wang Suyu. Research of high speed milling surface quality, [D]. Shandong university PhD thesis, (2006).