Prediction of surface roughness in end milling using swarm intelligence

2003 IEEE Swarm Intelligence Symposium, SIS 2003 - Proceedings

Volumn , Issue , 2003, Pages 220-227

  El Mounayri, H ^a   Dugla, Z ^a   Deng, Haiyan ^a  

^a Indiana University Purdue University Indianapolis   (United States)

Author keywords

Calibration; Computer numerical control; Evolutionary computation; Feeds; Milling; Particle swarm optimization; Predictive models; Rough surfaces; Surface roughness; US Department of Energy

Indexed keywords

CALIBRATION; COMPUTER CONTROL SYSTEMS; EVOLUTIONARY ALGORITHMS; FEEDING; MILLING (MACHINING); PARTICLE SWARM OPTIMIZATION (PSO); SWARM INTELLIGENCE;

COMPUTER NUMERICAL CONTROL; END-MILLING PROCESS; EXPERIMENTAL VALUES; MODEL CALIBRATION AND VALIDATION; PREDICTIVE MODELS; PSO(PARTICLE SWARM OPTIMIZATION); ROUGH SURFACES; US DEPARTMENT OF ENERGY;

SURFACE ROUGHNESS;

EID: 84897703593     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SIS.2003.1202272     Document Type: Conference Paper

References (24)

1. Alique A., Haber R,, Ros, S. and Gonzalez C., (2000), "Neural network-based model for the prediction of cutting force in milling process. A progress study on a real case," IEEE International Symposium on Intelligent Control - Proceedings of the 2000 IEEE International Symposium on Intelligent Control, pp. 121-125
2. Briceno, J., El-Mounayri, H., Mukhopadhyay, S., (2001), "Selecting a Artificial neural Network for Efficient Modeling and Accurate Simulation of the Milling Process," accepted for publication at the International Journal of Machine Tools and Manufacturing, 2002.
3. Cook, D. and Chiu, C., (1995), "Combining a radial basis neural network with time series analysis techniques to predict manufacturing process parameters," Applied Artificial Intelligence, vol. 9, pp. 623-631.
4. Elanayar, S. and Shin, Y.C. (1995), "Design and implementation of tool wear monitoring with radial basis function neural networks," Proceedings of the American Control Conference, Proceedings of the 1995 American Control Conference. Part 3 (of 6), pp.1722-1726
5. Liu Q. and Altintas Y., (1999), "On-line monitoring of flank wear in turning with multi-layered feed-forward neural network," International Journal of Machine Tools & Manufacturing, vol. 39, pp. 1945-1959
6. Liu Y. and Wang C., (1999), "Neural network based adaptive control and optimization in the milling process," International Journal of Advanced Manufacturing Technology, vol. 15, pp. 791-795
7. Tansel I.N., Bao W.Y., Arkan T.T, Shisler B., Mccool M. and Smith D., (1997), "Neural network based cutting force estimator for micro-end milling operations," I.E.S. through ANNs Proceedings of the 1997 Artificial Neural Networks in Engineering Conference, vol. 7, pp. 885-890
8. Vipul T. and Hazim El-Mounayri, (2000), "A novel Artificial Neural Network Force Model for End Milling," International Journal of Advanced Manufacturing Technology.
9. Luo T., Lu W., Krishnamurthy, and McMillan B; 1988, "A neural network approach for force and contour error control in multi-dimensional end milling operations; International Journal of Machine Tool & Manufacture, vol. 38, pp 1343-1359.
10. Hanna, M., Buck, A., and Smith, R. "Fuzzy Petri nets with neural networks to model products quality from a CNC-milling machining center"; IEEE Transactions on systems, man and cybernetics; Part A: Systems and humans, September 1996, pp 638-645.
11. Eberhart, R. C., and Shi, Y. (2001) (a). Tracking and optimizing dynamic systems with particle swarm. Proc. Congress on Evolutionary Computation 2001, Seoul, Korea. Piscataway, NJ: IEEE Service Center.
12. Eberhart, R. C., and Shi, Y. (2001)(b). Particle swarm optimization: developments, applications and resources. Proc. Congress on Evolutionary Computation 2001, Seoul, Korea. Piscataway, NJ: IEEE Service Center.
13. J. Kennedy and R. C. Eberhart, Swarm Intelligence. San Diego, Caliornia: Academic Pres, 2001.
14. Altintas, Y, (1994) "Direct adaptive control of end milling process," International Journal of Machine tool & manufacture, Vol.34 (4) pp 461-472-1994
15. Kline, W. A., DeVor, R. E., Shareef, I. A., (1982)"The Prediction of surface accuracy in end milling," Journal of engineering for industry, vol. 104, pp 272-279.
16. Sutherland, J., DeVor, R. E., (1986) "An improved method for cutting force and surface error prediction in flexible end milling system," Journal of engineering for industry, vol. 108, pp 269-279.
17. Babin, T. S., Lee, J. M., Sutherland, J., and Kapoor, S. G.,(1985) "Model for end milled surface topography," Manufacturing Engineering Transactions, 1985, 13th NAMRC, p 362-368.
18. Melkote, S. N., Sutherland J. W., Thangaraj A., (1995) "End milled surface texture: The effect of tool flexibility on back cutting," ASME, Manufacturing engineering division, MED, vol. 1, p-201-211.
19. Melkote, S. N., Thangaraj, A. R., (1994), "Enhanced end milling surface texture model including the effects of radial rake and primary relief angles," Journal of Engineering for Industry, Transactions of the ASME, vol. 116, no. 2, pp 166-174.
20. R. C. Eberhart, P. K. Simpson, and R. W. Dobbins, Computational Intelligence PC Tools. Boston, Massachusetts: Academic Press, 1996.
21. R. C. Eberhart and J. Kennedy, "A New Optimizer using Particle Swarm Theory," Proc. 6th Intl. Symp. On Micro Machine and Human Science (Nagoya, Japan), Piscataway, New Jersey: IEEE Service Center, 1995, pp. 39-43.
22. J. Kennedy and R. C. Eberhart, "Particle Swarm Optimization," Proc. IEE Intl. Conf. on Neural Networks, Piscataway, New Jersey: IEE Service Center, 1995, pp. IV:1942-1948.
23. Y. Shi and R. C. Eberhart, "Parameter Selection in Particle Swarm Optimization," Proc. 7th Ann. Conf. on Evolutionary Programming, San Diego, California, 1998
24. R. Sagherian and M. A. Elbestawi, "A simulation system for improving machining accuracy in milling," Computers in Industry, v14, 1990, pp, 293-305.