On-line cutting force coefficients identification for bull-end milling process with vibration

Abstract The foundation of newest cutting forces models still is cutting force coefficients that represent material behaviors. They are combined with cutter-workpiece contact algorithms, material properties and so on in the model to accomplish the prediction. Even though cutting force coefficients are significant, identification methods are still involved with onerous experiments, over-idealized measurement conditions, serious results fluctuation caused by many unquantifiable factors. To enlarge cutting database for the optimization of cutting process, utilizing the abundant real-time process monitoring data is a possible choice, in which novel identification methods are needed. To settle this problem, this paper proposed an online identification method considering stiffness property of cutter-holder-spindle system. This investigation considers the fluctuation of cutting forces caused by cutter vibration in two steps: First, a cutting force model that is combined with dynamic undeformed chip thickness is built for bull-end milling. Second, on the foundation of previous step, a corresponding identification method is developed, in which the dynamic undeformed chip thickness is obtained using measured data and utilized in cutting force coefficient identification. The comparison of experimental results and predicting results proves the reliability of cutting force model. Under different conditions, the application of identification method output promising results. In this section, the results show that it is possible to use new method in realizing real-time identification and eliminating machine tool stiffness effect. Also, the shortcomings of the method and the potential improvements are discussed.

[1]  Ahmed A. D. Sarhan,et al.  Cutting force analysis to estimate the friction force in linear guideways of CNC machine , 2016 .

[2]  Ming Luo,et al.  A wireless instrumented milling cutter system with embedded PVDF sensors , 2018, Mechanical Systems and Signal Processing.

[3]  Yu Guo,et al.  Modeling of cutting forces in end milling based on oblique cutting analysis , 2016 .

[4]  Roger Fales,et al.  Identification of cutting force coefficients for the linear and nonlinear force models in end milling process using average forces and optimization technique methods , 2015 .

[5]  Chang-Ho Lee,et al.  An integrated prediction model including the cutting process for virtual product development of machine tools , 2015 .

[6]  Dinghua Zhang,et al.  Identification of cutting force coefficients in machining process considering cutter vibration , 2018 .

[7]  M. S. Uddin,et al.  On the design and analysis of an octagonal–ellipse ring based cutting force measuring transducer , 2016 .

[8]  Xing Zhang,et al.  An accurate prediction method of cutting forces in 5-axis flank milling of sculptured surface , 2016 .

[9]  Jun Hu,et al.  A chatter free calibration method for determining cutter runout and cutting force coefficients in ball-end milling , 2013 .

[10]  Dinghua Zhang,et al.  Improving tool life in multi-axis milling of Ni-based superalloy with ball-end cutter based on the active cutting edge shift strategy , 2018 .

[11]  O. B. Adetoro,et al.  Prediction of mechanistic cutting force coefficients using ALE formulation , 2010 .

[12]  Zhenyuan Jia,et al.  A new cutting force prediction method in ball-end milling based on material properties for difficult-to-machine materials , 2016 .

[13]  Yusuf Altintas,et al.  Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design , 2000 .

[14]  J. Butcher.  The numerical analysis of ordinary differential equations: Runge-Kutta and general linear methods , 1987 .

[15]  Tarek Mabrouki,et al.  Analysis of surface roughness and cutting force components in hard turning with CBN tool: Prediction model and cutting conditions optimization , 2012 .

[16]  Andrew P. Longstaff,et al.  Improved dynamic cutting force model in ball-end milling. Part I: theoretical modelling and experimental calibration , 2005 .

[17]  A. C. Okafor,et al.  Effects of geometric parameters of wavy-edge bull-nose helical end-mill on cutting force prediction in end-milling of Inconel 718 under MQL cooling strategy , 2016 .

[18]  Jianguang Li,et al.  Development and testing of an integrated smart tool holder for four-component cutting force measurement , 2017 .

[19]  A. Chukwujekwu Okafor,et al.  Development of a mechanistic cutting force model for wavy-edge bull-nose helical end-milling of inconel 718 under emulsion cooling strategy , 2016 .

[20]  Gianni Campatelli,et al.  Speed-varying cutting force coefficient identification in milling , 2015 .

[21]  A. Sarhan,et al.  Optimization of cutting conditions for minimum residual stress, cutting force and surface roughness in end milling of S50C medium carbon steel , 2016 .

[22]  Min Wan,et al.  A novel cutting force modelling method for cylindrical end mill , 2010 .

[23]  Tunç Lütfi Taner,et al.  Generalized cutting force model in multi-axis milling using a new engagement boundary determination approach , 2015 .

[24]  Hsi-Yung Feng,et al.  Prediction of cutting forces in three- and five-axis ball-end milling with tool indentation effect , 2013 .