Tool Wear Optimization for General CNC Turning Using Fuzzy Deduction

Tian-Syung Lan

.

DOI: 10.4236/eng.2010.212128                

Abstract

Tool wear is frequently considered in the modern CNC (computer numerical control) turning industry. Most existing optimization researches for CNC finish turning were either accomplished within certain manufacturing circumstances, or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme proposed is deemed to be necessary for the industry. In this paper, four parameters (cutting depth, feed rate, speed, tool nose runoff) with three levels (low, medium, high) are considered to optimize the tool wear for finish turning based on orthogonal array. Additionally, nine fuzzy control rules using triangle membership function with respective to five linguistic grades for tool wear are constructed. Considering four input and twenty output intervals, the defuzzification using center of gravity is then completed and introduced as the S/N (signal-to-noise) ratio. Thus, the optimum general deduction parameters can then be received. The confirmation experiment for optimum general deduction parameters is furthermore performed on an ECOCA-3807 CNC lathe. It is shown that the tool wear ratio from the fuzzy deduction optimization parameters is significantly advanced comparing to those from benchmark. This paper not only proposes a general deduction optimization scheme using orthogonal array, but also contributes the satisfactory fuzzy linguistic approach to tool wear in CNC turning with profound insight.

Keywords

CNC, General Optimization, Fuzzy Deduction, Tool Wear Ratio

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	R. R. Venkata, “Machinability Evaluation of Work Materials Using a Combined Multiple Attribute Decision- making Me-thod,” International Journal of Advanced. Manufacturing Technology, Vol. 28, No. 3-4, 2006, pp. 221-227.
[2]	J. P. Davim and A. Conceicao, “Optimization of Cutting Conditions in Machining of Aluminium Matrix Composites Using a Nu-merical and Experimental Model,” Journal Materials Processing Technology, Vol. 112, No. 1, 2001, pp. 78-82.
[3]	W. S. Lin, B. Y. Lee, C. L. Wu, “Modeling the Surface Roughness and Cutting Force for Turning,” Journal Materials Processing Technology, Vol. 108, No. 3, 2001, pp. 286-293.
[4]	W. S. Lin, 1998“The Study of Machining Accuracy and Tool Wear Reliability,” Ph. D. Thesis, National Central University, Taoyuan, Tai wan, 1998.
[5]	Q., Meng, J. A. Arsecularatne and P. Mathew,(2000) “Calculation of Optimum Cutting Conditions for Turning Operations Using a Machining Theory,” International Journal of Advanced. Manufacturing Technology, Vol. 40, No. 4, 2000, pp. 1709-1733.
[6]	J. Kopac, “Optimal Machining for Achieving the Desired Surface Roughness in Fine Turning of Cold Preformed Steel Work Piece,” International Journal of Machine Tools and Manufacture, Vol. 42, No. 10, 2002, pp. 707-716.
[7]	N. Tosun and L. Ozler, “Optimisation for Hot Turning Operations with Multiple Performance Characteristics,” International Journal of Advanced. Manufacturing Technology, Vol. 23, No. 11-12, 2004, pp. 777-782.
[8]	L. J. Yeh, “A Study on the Monitoring and Suppression System for Turning Slender Workpieces,” Ph. D. Thesis, Tatung University, Taibei, Taiwan, 1994.
[9]	H. Huh, J. H. Heo and H. W. Lee, “Optimization of a Roller Leveling Process for Al7001T9 Pipes with Finite Element Analysis and Taguchi Method,”., International Journal of Machine Tools and Manufacture, Vol. 43, No. 4, 2003, pp. 345-350.
[10]	K. S. Anastasiou, “Optimi-zation of the Aluminium Die Casting Process Based on the Taguchi Method,” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 216, No. 7, 2002, pp. 969-977.
[11]	M. N. Dhavlikar, M. S. Kulkarni and V. Mariappan, (2003) “Combined Taguchi and Dual Response Method for Optimization of a Centerless Grinding Operation,” Journal Materials Processing Technology, Vol. 132, No. 1-3, 2003, pp. 90-94.
[12]	S. J. Kim, K. S. Kim and H. Jang, “Optimization of Manufacturing Parameters for a Brake Lining Using Taguchi Method”. Journal Materials Processing Technology, Vol. 136, No. 1-3, 2003, pp. 202-208.
[13]	L. A. Zadeh, “Fuzzy sets,” Information and Control, Vol. 8, No. 3, 1965, pp. 338-353.
[14]	H. J. Zimmer-man, “Fuzzy Sets THeory and Its Applications,” Kluwer Aca-demic Publisher, Boston, 1992.
[15]	J. Wanga, C. Yao and Z. Zhang, “A fuzzy-AHP Comprehensive Evaluation Method for Optimization Design of Machine Tool,” Mechanic Automation and Control Engineering, Wuhan, 26-28 June 2010, pp. 2652-2656.
[16]	G. Chai, C. Lu and D. Wen, “Study on the Multiple Objective Parameter Optimization Method for NC Turning,” Advanced Materials Research, Vol. 102-104, 2010, pp. 705-709.
[17]	J. Mao, Y. Cao, H. Ching and R. Du, “Fuzzy Tolerancing Based on Available Manufacturing Resources,” Computer-Aided Design and Applications, Vol. 6, No. 2, 2009, pp. 253-261.
[18]	H. Gao, M. Xu, Y. Su, P. Fu and Q. Liu, “Experimental Study of Tool Wear Monitoring Based on Neural Networks,” Intelligent Control and Automation, Chongqing, 25-27 June, pp. 6906-6910.
[19]	Z. Güng?r and F. Ar?kan, “Using Fuzzy Decision Making System to Improve Quali-ty-based Investment,” Journal of Intelligent Manufacturing, Vol. 18, No. 2, 2007, pp. 197-207.
[20]	A. Kaufmann and M. M. Gupta, “Introduction to Fuzzy Arithmetic Theory and Applica-tions,” Van Nostrand Reinhold, New York, 1991.
[21]	K. Palanikumar, “Application of Taguchi and Response Surface Methodologies for Surface Roughness in Machining Glass Fiber Reinforced Plastics by PCD Tooling,” International Journal of Advanced. Manufacturing Technology, Vol. 36, No. 1-2, 2008, PP. 19-27.
[22]	P. J. Ross, “Taguchi Techniques for Quality Engineering,” McGraw-Hill Publication, New York, 1998.
[23]	J. C. Chang, “The Application of Taguchi Method in the Finite Element Analysis for the Optimal Structural Design of Compressed Sheet in Huge Extended Plate,” Master’s Thesis, National Chung Hsing University, Taichung, Taiwan, 2000.
[24]	H. S. Wei, S. C. Hwang, S. J. Liu, “Analysis for the Optimum Conditions in Derrick Hook by Using Taguchi Me-thod,” Master’s Thesis, Nation Pingtung University of Science and Technology, Pingtung, Taiwan, 2002.
[25]	J. H. Park, K. M. Yang and K. S. Kang, “A Quality Function Deployment Methodology with Signal and Noise Ratio for Improvement of Wasserman’s Weights,” International Journal of Advanced. Manufacturing Technology, Vol. 26, No. 5-6, 2005, pp. 631-637.
[26]	F. C. Wu and C. C. Chyu, “A Comparative Study on Taguchi’s SN Ratio, Minimising MSD and Variance for Nominal-the-best Characteristic Experiment,” International Journal of Advanced. Manufacturing Technology, Vol. 20, No. 9, 2002, pp. 655-659.
[27]	T. S. Lan and M. Y. Wang, “Com-petitive parameter optimization of multi-quality CNC turning,” International Journal of Advanced. Manufacturing Technology, Vol. 41, No. 7-8, 2009, pp. 820-826.
[28]	J. L. Lin and J. F. Lin, “Grey Theory Applied to Evaluate the Tribological Per-formances of The a-CH(N) Coating Films Prepared by Differing the Nitrogen Content and The Film Thickness,” International Journal of Advanced. Manufacturing Technology, Vol. 27, No. 9-10, 2006, pp. 845-853.