A cutting parameter optimization method based on dynamic machining features for complex structural parts

Complex structural parts are pervasive and playing an important role in the aircraft manufacturing area. In order to improve the machining efficiency, the cutting parameter optimization of complex structural parts during the machining has always been a problem in manufacturing industry. At present, the cutting parameters are usually optimized based on the final state of complex structural parts and remain unchanged during the machining process, which may not consider the cutting parameter optimization of workpiece in the intermediate machining process. Thus, a cutting parameter optimization method based on dynamic machining features for complex structural parts is proposed to improve the machining efficiency and guarantee the product quality during the machining process. The interim geometric state of each machining occasion is constructed in order to analyze the chatter stability. Then, the cutting parameters are optimized using a genetic algorithm within the limits of chatter stability.

[1]  Maghsud Solimanpur,et al.  Optimisation of cutting parameters using a multi-objective genetic algorithm , 2009 .

[2]  Y G Li,et al.  Feature recognition technology for aircraft structural parts based on a holistic attribute adjacency graph , 2010 .

[3]  Huaizhong Li,et al.  Modelling the cutting forces in micro-end-milling using a hybrid approach , 2014 .

[4]  Miloš Madić,et al.  Modeling and analysis of correlations between cutting parameters and cutting force components in turning AISI 1043 steel using ANN , 2013 .

[5]  Xin Wang,et al.  Cutting force prediction and analytical solution of regenerative chatter stability for helical milling operation , 2014 .

[6]  Xun Xu,et al.  Computer-aided process planning – A critical review of recent developments and future trends , 2011, Int. J. Comput. Integr. Manuf..

[7]  Gilles Dessein,et al.  INFLUENCE OF MATERIAL REMOVAL ON THE DYNAMIC BEHAVIOR OF THIN-WALLED STRUCTURES IN PERIPHERAL MILLING , 2004 .

[8]  Xu Liu,et al.  A dynamic feature information model for integrated manufacturing planning and optimization , 2012 .

[9]  Yusuf Altintas,et al.  Prediction of Milling Force Coefficients From Orthogonal Cutting Data , 1996 .

[10]  József Kövecses,et al.  A New Analytical Formulation for the Dynamics of Multipocket Thin-Walled Structures Considering the Fixture Constraints , 2011 .

[11]  Yusuf Altintas,et al.  Analytical Prediction of Stability Lobes in Milling , 1995 .

[12]  Li Zheng,et al.  Feedrate optimization for variant milling process based on cutting force prediction , 2004 .

[13]  Xin Zhou,et al.  Interim feature-based cutting parameter optimization for aircraft structural parts , 2015 .

[14]  Richard E. DeVor,et al.  An Investigation of Variable Spindle Speed Face Milling for Tool-Work Structures With Complex Dynamics, Part 1: Simulation Results , 1997 .

[15]  Weiming Shen,et al.  Dynamic feature modelling for closed-loop machining process control of complex parts , 2015, Int. J. Comput. Integr. Manuf..

[16]  Siti Zaiton Mohd Hashim,et al.  Evolutionary techniques in optimizing machining parameters: Review and recent applications (2007-2011) , 2012, Expert Syst. Appl..

[17]  H. Nevzat Özgüven,et al.  Structural modifications using frequency response functions , 1990 .

[18]  L. Taner Tunç,et al.  Prediction of workpiece dynamics and its effects on chatter stability in milling , 2012 .

[19]  João Paulo Davim,et al.  Optimisation of multi-pass cutting parameters in face-milling based on genetic search , 2009 .