Modeling Surface Finish in End Milling Using Fuzzy Subtractive Clustering-Based System Identification Method

8.0. References

• Black , J.T. 1979 . Flow stress model in metal cutting . Journal of Engineering for Industry , 101 ( 4 ) : 403 – 415 .
   Google Scholar
• Chen , J.C. and Smith , R.A. 1997 . Experimental design and analysis in understanding machining mechanisms . Journal of Industrial Technology , 13 ( 3 ) : 15 – 19 .
   Google Scholar
• Oxley , P.L.B. 1989 . The Mechanics of Machining: An Analytical Approach to Assessing Machinability Chichester West Sussex, , England : Ellins Horwood Ltd. .
   Google Scholar
• Trent , E.M. 1991 . Metal Cutting Oxford, , England : Butterworth-Heinemann Ltd. .
   Google Scholar
• Astakhov , V.P. and Osman , M.O. 1996 . Journal of Materials Processing Technology , 62 ( 3 ) : 175 – 179 .
   Google Scholar
• Astakhov , V.P. 1999 . Metal Cutting Mechanics CRC press .
   Google Scholar
• Armarego , E.J. 1996 . “ A Predictive modeling of machine operations—a means of bridging the gap between theory and practice ” . In CSME Forum SCGM A Manufacturing Science and Engineering 18 – 27 . Canada : Hamilton .
   Google Scholar
• Armarege , E.J. and Brown , R.H. 1969 . The Machining of Metals Prentice Hall .
   Google Scholar
• Boothroyd , G. and Knight , W.A. 1989 . Fundamentals of Machining and Machine Tools , 2 New York : Marcel Dekker Inc. .
   Google Scholar
• Huynh , V.M. and Fan , Y. 1992 . Surface-texture measurement and characterization with applications to machine-tool monitoring . The International Journal of Advanced Manufacturing Technology , 7 : 2 – 10 .
   Google Scholar
• Zadeh , L. 1973 . Outline of a new approach to the analysis of complex systems and decision processes . IEEE Transactions on Systems, Man, and Cybernetics , : 28 – 44 . SMC-3
   Web of Science ®Google Scholar
• Chiu , S. 1994 . Fuzzy model identification based on cluster estimation . Journal of Intelligent and Fuzzy Systems , 2 : 267 – 278 .
   Web of Science ®Google Scholar
• Jang , J. 1993 . ANFIS: adaptive-network-based fuzzy inference system . IEEE Transactions on Systems Man and Cybernetics , 23 ( 3 ) : 665 – 685 .
   Web of Science ®Google Scholar
• Takagi , T. and Sugeno , M. 1985 . Fuzzy identification of systems and its applications to modeling and control . EEE Transactions on Systems Man and Cybernetics , 15 : 116 – 132 .
   Web of Science ®Google Scholar
• Tsai , P. , Jang , S. and Shieh , S. 2001 . Predictive control of batch processes using principal surface/space analysis and fuzzy clustering empirical models . Proceedings of the American Control Conference , 2 : 1005 – 1009 .
   Google Scholar
• Bai , G. and Liang , Z. 2000 . The application of fuzzy clustering analysis in the choice of fabric . Journal- Northwest Institute of Textile Science and Technology , 14 ( 2 ) : 128 – 132 .
   Google Scholar
• Xiaoli , L. and Zhejun , Y. 1998 . Wear , 219 ( 2 ) : 145
   Web of Science ®Google Scholar
• Talaie , A. , Taguchi , T. and Romagnoli , J. 1997 . Towards an on-line conducting polymer composite based chemical sensor using a behavioral fuzzy clustering modeling technique . Smart Materials & Structures , 6 ( 5 ) : 601
   Web of Science ®Google Scholar
• Demirli , K. and Muthukumaran , P. 2000 . Journal of Intelligent and Fuzzy Systems , 9 ( 3 ) : 129 – 158 .
   Web of Science ®Google Scholar
• Mamdani , H. and Assilian , S. 1975 . International Journal of Man-Machine studies , 7 : 1 – 13 .
   Google Scholar
• Jang , J.S.R. , Chuen-Tsai , S. and Mizutani , E. 1997 . Neuro Fuzzy Modeling and Soft Computing Prentice Hall International Inc. .
   Google Scholar