Least squares approximated stability boundaries of milling process

Abstract First and second order least squares methods are used in generating simple approximation polynomials for the state term of the model for regenerative chatter in the milling process. The least squares approximation of delayed state term and periodic term of the model does not go beyond first order. The resulting discrete maps are demonstrated to have same convergence rate as the discrete maps in other works that are based on the interpolation theory. The presented discrete maps are illustrated to be beneficial in terms of computational time (CT) savings that derive from reduction in the number of calculation needed for generation system monodromy matrix. This benefit is so much that computational time of second order least squares-based discrete map is noticeably shorter than that of first order interpolation-based discrete map. It is expected from analysis then verified numerically that savings in CT due to use of least squares theory relative to use of interpolation theory of same order rises with rise in order of approximation. The experimentally determined model parameters used for numerical calculations are extracted from literature.

[1]  Gábor Stépán,et al.  On stability prediction for milling , 2005 .

[2]  Gábor Stépán,et al.  Stability of up-milling and down-milling, part 1: alternative analytical methods , 2003 .

[3]  E. Govekar,et al.  ON STABILITY PREDICTION FOR LOW RADIAL IMMERSION MILLING , 2005 .

[4]  Gábor Stépán,et al.  Semi‐discretization method for delayed systems , 2002 .

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

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

[7]  Han Ding,et al.  Second-order full-discretization method for milling stability prediction , 2010 .

[8]  Han Ding,et al.  A full-discretization method for prediction of milling stability , 2010 .

[9]  R. Jain,et al.  Numerical Methods for Scientific and Engineering Computation , 1985 .

[10]  B. Mann,et al.  Stability of Interrupted Cutting by Temporal Finite Element Analysis , 2003 .

[11]  Gábor Stépán,et al.  Updated semi‐discretization method for periodic delay‐differential equations with discrete delay , 2004 .

[12]  Tamás Insperger,et al.  Full-discretization and semi-discretization for milling stability prediction: Some comments , 2010 .

[13]  Henk Nijmeijer,et al.  Prediction of regenerative chatter by modelling and analysis of high-speed milling , 2003 .

[14]  Peter Eberhard,et al.  Improving the computational efficiency and accuracy of the semi-discretization method for periodic delay-differential equations , 2008 .

[15]  C. G. Ozoegwu,et al.  Time Finite Element Chatter Stability Characterization of a Three Tooth Plastic End-Milling Cnc Machine , 2013 .

[16]  Firas A. Khasawneh,et al.  Analysis of milling dynamics for simultaneously engaged cutting teeth , 2010 .

[17]  Gábor Stépán,et al.  Approximate stability charts for milling processes using semi-discretization , 2006, Appl. Math. Comput..

[18]  Yusuf Altintas,et al.  Analytical Prediction of Three Dimensional Chatter Stability in Milling , 2001 .

[19]  David Levin,et al.  The approximation power of moving least-squares , 1998, Math. Comput..

[20]  Tony L. Schmitz,et al.  Effects of Radial Immersion and Cutting Direction on Chatter Instability in End-Milling , 2002 .

[21]  Tamás Insperger,et al.  Stability analysis of periodic delay-differential equations modeling machine tool chatter , 2002 .

[22]  Marian Wiercigroch,et al.  Sources of nonlinearities, chatter generation and suppression in metal cutting , 2001, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.