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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2022, Vol. 43 ›› Issue (4): 525467.doi: 10.7527/S1000-6893.2021.25467

• Reviews • Previous Articles     Next Articles

Review and prospects of feedrate optimization in CNC machining

WU Baohai1,2, ZHANG Yang1,2, ZHENG Zhiyang1,2, ZHANG Ying1,2, ZHANG Siqi1,2   

  1. 1. Key Laboratory of High Performance Manufacturing for Aero Engine, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi'an 710072, China;
    2. Engineering Research Center of Advanced Manufacturing Technology for Aero Engine, Ministry of Education, Northwestern Polytechnical University, Xi'an 710072, China
  • Received:2021-03-09 Revised:2021-03-29 Published:2021-04-29
  • Supported by:
    National Key R & D Program of China (2020YFB1710400)

Abstract: Feedrate optimization is an most important link in the realization of Computer Numerical Control(CNC) intelligent machining, and is also a key issue that needs to be solved urgently in the field of intelligent manufacturing in the future. In this paper, three optimization methods are discussed, which are off-line feedrate optimization with the goal of machining efficiency, machining quality, machine stability and constant cutting force, on-line adaptive feedrate optimization with constant cutting force and cutting power, and the integration of the two method. The current research status and theoretical achievements at home and abroad are summarized. The application effects, advantages and disadvantages of various optimization methods are reviewed. Then, several representative breakthrough research directions and future development trends are proposed for intelligent optimization of process parameters. We expect to better realize the independent decision-making and intelligent optimization of the CNC system, improve the processing efficiency and quality, improve the application performance of the CNC system, and promote the independent development and intelligent manufacturing.

Key words: CNC machining, feedrate, parameter optimization, adaptive control, intelligent optimization algorithm

CLC Number: