Design of artificial neural networks for tool wear monitoring

Journal of Intelligent Manufacturing

Volumn 8, Issue 3, 1997, Pages 215-226

  Venkatesh, Kurapati ^a   Zhou, Mengchu ^b   Caudill, Reggie J ^b  

^a New Jersey Institute of Technology ^*  (United States)

^b NEW JERSEY INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Flexible manufacturing systems; Neural networks; Tool wear monitoring

Indexed keywords

CUTTING TOOLS; FLEXIBLE MANUFACTURING SYSTEMS; MACHINING; WEAR OF MATERIALS;

CUTTING FORCE; CUTTING VELOCITY; FLANK WEAR; TOOL WEAR MONITORING;

NEURAL NETWORKS;

EID: 0031169083     PISSN: 09565515     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1018573224739     Document Type: Article

References (39)

1. Billatos, S. B., Bayoumi, A. E., Alden Kendall, L. and Saunders, S. C. (1986) A statistical wear model for certain tool materials with applications to machining Wear, 112(2-3), 257-271.
2. Blum, T. and Inasaki, T. (1990) A study of acoustic emission from the orthogonal cutting process. Transactions of the ASME, Journal of Engineering for Industry, 112(3), 203-211.
3. Burke, L. I. (1992) Competitive learning based approaches to tool-wear identification. IEEE Transactions on Systems, Manufacturing and Cybernetics, 22(3), 559-563.
4. Chryssolouris, G. and Guillot, M. (1990) A comparison of statistical and AI approaches to the selection of process parameters in intelligent machining. Transactions of the ASME, Journal of Engineering for Industry, 112(2), 122-131.
5. Constantinides, N. and Bennett, S. (1987) An investigation of methods for the on-line estimation of tool wear. International Journal of Machine Tools Manufacturing, 27(2), 225-237.
6. Danai, K. and Ulsoy, A. G. (1987) A dynamic model for on-line tool wear estimation in turning. Transactions of the ASME, Journal of Engineering for Industry, 109(4), 396-399.
7. El Gomayel, J. I. and Bregger, K. D. (1988) On-line tool wear sensing for turning operations. Transactions of the ASME, Journal of Engineering for Industry, 108(1), 44-47.
8. Emel, E. and Kannatey-Asibu, E. (1988) Tool failure monitoring in turning by pattern recognition analysis of AE signals. Transactions of the ASME, Journal of Engineering for Industry, 110(2), 137-145.
9. Floyd, T. (1992) Diagnose insert failure. Manufacturing Engineering, 109(4), 37-38.
10. Guisti, F., Santochi, M. and Tantussi, G. (1984) A flexible tool wear sensor for NC lathes. Annals of CIRP, 33(1) 229-232.
11. Jetly, S. (1984) Measuring cutting tool wear on line: some practical considerations. Manufacturing Engineering, 93, 55-60.
12. Koren, Y. (1978) Flank wear model of cutting tools using control theory. Transactions of the ASME, Journal of Engineering for Industry, 100(1), 103-109.
13. Leem, C. S., Dornfeld, D. A. and Dreyfus, S. E. (1995) A customized neural network for sensor fusion in on line monitoring of cutting tool wear. Transactions of the ASME, Journal of Engineering for Industry, 117, 152-159.
14. Levy, N., Zhou, M. C. and Quan, Y. (1994) Real-time tool wear identification using neural networks, in Proceedings 1994 IEEE Conference on Decision and Control, Orlando, FL, pp. 1050-1051.
15. Li, P. G. and Wu, S. M. (1988) Monitoring drilling wear states by a fuzzy pattern recognition technique. Transactions of the ASME, Journal of Engineering for Industry, 110(2), 297-300.
16. Liang, S. Y. and Dornfield, D. A. (1989) Tool wear detection using time series analysis of acoustic emission. Transactions of the ASME, Journal of Engineering for Industry, 111(3), 199-205.
17. Lister, P. M. and Barrow, G. (1986) Tool condition monitoring systems, in Proceedings of 27th MTDR Conference, pp. 271-288.
18. Liu, T. I. and Wu, S. M. (1990) On-line detection of drill wear. Transactions of the ASME, Journal of Engineering for Industry, 112(3), 299-302.
19. Martin, K. F., Brandon, J. A., Grosvenor, K. L. and Owen, A. (1986) A comparison of in-process tool wear measurement methods in tuning, in Proceedings of the 26th Machine Tool Design and Research Conference, pp. 289-296.
20. Masory, O. (1991) Monitoring machining processes using multisensor readings fused by artificial ANN. Journal of Materials Processing and Technology, 28(1), 231-240.
21. Moriwaki, T. and Hino, R. (1991) Application of neural network to AE signal processing for automatic detection of cutting tool life. Journal of the Japan Society of Precision Engineering, 57(7), 1259-1264.
22. Moriwaki, T. and Mori, Y. (1993) Recognition of cutting state based on neural network sensor fusion. Journal of the Japan Society of Precision Engineering, 59(5), 779-784.
23. Pandit, S. M. and Kashou, S. (1982) A data dependent systems strategy of on-line tool wear sensing. Transactions of the ASME, Journal of Engineering for Industry, 104(3), 217-223.
24. Pearce, D. F. and Richardson, D. B. (1986) A technique for monitoring the health of cutting tools in interrupted cutting processes, in Proceedings of the 26th Machine Tool Design and Research Conference, pp. 297-303.
25. Raghunandan, M. (1991) Multi-sensory approaches to in-process monitoring of turning, MS Thesis, Department of Mechanical Engineering, Indian Institute of Technology, Madras, India.
26. Rangawala, S. and Dornfeld, D. (1990) Sensor integration using neural networks for intelligent tool condition monitoring. Transactions of the ASME, Journal of Engineering for Industry, 112(3), 219-228.
27. Ranky, P. G. (1986) Computer Integrated Manufacturing, Prentice-Hall, Englewood Cliffs, NJ.
28. Rao, S. B. (1986) Tool wear monitoring through the dynamics of stable turning. Transactions of the ASME, Journal of Engineering in Industry, 108(3), 183-190.
29. Rossetto, S. and Zompi, A. (1983) A stochastic tool-life model. Transactions of the ASME, Journal of Engineering for Industry, 103(1), 126-130.
30. Shunsherauddin, A. and Lawrence, J. C. (1983) In-process prediction of milling tool wear, in Proceedings of the Machine Tool Design and Research Conference, pp. 201-214.
31. Stevenson, F. and Greenwood, D. (1987) Tool Wear Estimation Using ANNs, Technical report by Netrologic Inc., San Diego, CA.
32. Taylor, F. W. (1906) On the art of cutting metals. Transactions of the ASME, Journal of Engineering for Industry, 28, 31-350.
33. Tlusty, J. and Andrews, G. C. (1983) A critical review of sensors for unmanned machining. Annals of CIRP, 32(2), 563-572.
34. Trent, E. M. (1977) Metal Cutting, Butterworth, London.
35. Venkatesh, K. (1992) Monitoring of tool wear using artificial neural networks, Master's Thesis, Florida Atlantic University, Boca Raton, FL.
36. Venkatesh, K., Zhou, M. C. and Caudill, R. (1994) Monitoring of tool wear using artificial neural networks, in Proceedings of American Control Conference, Baltimore, MD, pp. 2565-2570.
37. Uematsu, T. and Mohri, N. (1986) Prediction and detection of cutting tool failure by modified group method of data handling. International Journal of Machine Tools Design and Research, 26(1), 69-80.
38. Yao, Y., Fang, X. D. and Arndt, G. (1990) Comprehensive tool wear estimation in finish-machining via multi-variate time series analysis of 3-D cutting forces. Annals of CIRP, 39(1), 57-60.
39. Yee, K. W., Blomquist, D. S., Dornfeld, D. A. and Pan, C. S. (1986) An acoustic emission chip-form monitor for single point turning, in Proceedings of the 26th Machine Tool Design and Research Conference, pp. 305-312.