The optimal cutting-parameter selection of heavy cutting process in side milling for SUS304 stainless steel

This paper presents an optimal cutting-parameter design of heavy cutting in side milling for SUS304 stainless steel. The orthogonal array with grey-fuzzy logics isapplied to optimize the side milling process with multiple performance characteristics. A grey-fuzzy reasoning grade obtained from the grey-fuzzylogics analysis is used as a performance index to determine the optimal cutting parameters. The selected cutting parameters are spindle speed, feed per tooth,axial depth of cut and radial depth of cut, while the considered performance characteristics are tool life and metal removal rate. The results ofconfirmation experiments reveal that grey-fuzzy logics can effectively acquire an optimal combination of the cutting parameters. Hence, performance in theside milling process for heavy cutting can be significantly improved through this approach.

[1]  Liangchi Zhang,et al.  Surface roughness prediction of ground components using a fuzzy logic approach , 1999 .

[2]  M. Alauddin,et al.  Optimization of surface finish in end milling Inconel 718 , 1996 .

[3]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[4]  Bean Yin Lee,et al.  The optimal cutting-parameter selection of production cost in HSM for SKD61 tool steels , 2003 .

[5]  M Tolouei-Rad,et al.  On the optimization of machining parameters for milling operations , 1997 .

[6]  Qiang Liu,et al.  Fuzzy pattern recognition of AE signals for grinding burn , 2005 .

[7]  G. D'Errico,et al.  A study of coatings for end mills in high speed metal cutting , 1999 .

[8]  Imtiaz Ahmed Choudhury,et al.  Application of Taguchi method in the optimization of end milling parameters , 2004 .

[9]  Y. S. Tarng,et al.  Optimization of the electrical discharge machining process based on the Taguchi method with fuzzy logics , 2000 .

[10]  P.Narender Singh,et al.  Optimization by Grey relational analysis of EDM parameters on machining Al–10%SiCP composites , 2004 .

[11]  Janez Kopac,et al.  Optimal machining parameters for achieving the desired surface roughness in fine turning of cold pre-formed steel workpieces , 2002 .

[12]  P. S. Kao,et al.  Optimization of electrochemical polishing of stainless steel by grey relational analysis , 2003 .

[13]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[14]  Y. S. Tarng,et al.  Determination of optimal cutting parameters in wire electrical discharge machining , 1995 .

[15]  C. L. Lin,et al.  Optimisation of the EDM Process Based on the Orthogonal Array with Fuzzy Logic and Grey Relational Analysis Method , 2002 .

[16]  G. P. Syrcos,et al.  Die casting process optimization using Taguchi methods , 2003 .

[17]  Y. S. Tarng,et al.  Optimisation of the weld bead geometry in gas tungsten arc welding by the Taguchi method , 1998 .

[18]  C. Fung Manufacturing process optimization for wear property of fiber-reinforced polybutylene terephthalate composites with grey relational analysis , 2003 .

[19]  P. V. Rao,et al.  Selection of optimum tool geometry and cutting conditionsusing a surface roughness prediction model for end milling , 2005 .

[20]  S. J. Lou,et al.  In-process surface recognition of a CNC milling machine using the fuzzy nets method , 1997 .