Prediction of thermally induced time-variant machine tool error maps using a fuzzy artmap neural network

Journal of Manufacturing Science and Engineering, Transactions of the ASME

Volumn 119, Issue 4, 1997, Pages 623-630

  Srinivasa, N ^a,b   Ziegert, J C ^a  

^a UNIVERSITY OF FLORIDA   (United States)

^b UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION; COMPUTER SIMULATION; CUTTING TOOLS; ERROR COMPENSATION; ERRORS; FUZZY SETS; LEARNING SYSTEMS; MACHINING; NEURAL NETWORKS; ONLINE SYSTEMS;

ASSOCIATED POSITIONAL ERRORS; LASER BALL BAR; THERMAL SENSOR READINGS;

MACHINE TOOLS;

EID: 0031268776     PISSN: 10871357     EISSN: 15288935     Source Type: Journal    
DOI: 10.1115/1.2831196     Document Type: Article

References (51)

1. Bryan, J., 1980, “International Status of Thermal Research,” Annals of the CIRP, Vol. 39, No. 2.
2. Week, M., and Zangs, L., 1975, “Computing the Thermal Behavior of Machine Tools Using the Finite Element Method-Possibilities and Limitations,” Proceedings of the 16th MTDR Conference.
3. Okushima, K., et al., 1973, “An Optimal Design of Machine Tools for Thermal Deformations,” Bulletin of Japan Society of Precision Engineering, Vol. 7, No. 2.
4. Donaldson, R., 1972, “A Simple Method for Separating Spindle Error From Test Ball Roundness Error,” Annals of the CIRP, Vol. 21.
5. Woyotowitz, M. A., et al., 1989, “Tool Path Error Analysis for High Precision Milling with a Magnetic Bearing Spindle,” Transactions of the ASME, pp. 129-142.
6. Wills-Moren, W. J., et al., 1982, “Some Aspects of the Design and Development of a Large High Precision CNC Diamond Turning Machine,” Annals of the CIRP, Vol. 31, No. 1.
7. Furukawa et al., 1986, “Development of Ultra-Precision Machine Tool Made of Ceramics,” Annals of the CIRP, Vol. 35, No. 1.
8. Placek, C., 1990, “User Needs Drive CMM Evolution,” Quality, November.
9. Spur, G., et al., 1988, “Thermal Behavior Optimization of Machine Tools,” Annals of the CIRP, Vol. 37, No. 1.
10. Tlusty, J., and Mutch, G. F., 1973, “Testing and Evaluating Thermal Deformations in Machine Tools,” Proceedings of the 14th MTDR Conference.
11. Hocken, R. J., 1977, “3-Dimensional Metrology,” Annals of the CIRP, Vol. 26, No. 1.
12. Donmez, M. A., 1985, “A General Methodology for Machine Tool Accuracy Enhancement: Theory, Application and Implementation,” Ph.D. Dissertation, Purdue University.
13. Venugopal, R., and Barash, M., 1986, “Thermal Effects on the Accuracy of Numerically Controlled Machine Tools,” Annals of the CIRP, Vol. 35, No. 1. pp. 255-258.
14. Duffie, N. A., and Malmberg, S. J., 1987, “Error Diagnosis and Compensation Using Kinematic Models and Position Error Data,” Annals of the CIRP, Vol. 36, No. 1.
15. Zhang, G., et al. 1985, “Error Compensation of Coordinate Measuring Machines,” Annals of the CIRP, Vol. 34, No. 1.
16. Teeuwsen, J., Soons, J. A., and Schellekens, P., 1989, “A General Method for Error Description of CMM’s Using Polynomial Fitting Procedures,” Annals of the CIRP, Vol. 38, No. 1.
17. Kunzmann, H., Trapet, E., and Waldele, F., 1986, “An Analytical Quadratic Model for the Geometric Errors of a Machine Tool,” Journal of Manufacturing Systems.
18. Jouy, F., 1986, “Theoretical Modélisation and Experimental Identification of the Geometrical Parameters of Coordinate Machines by measuring a MultiDirected Bar,” Annals of the CIRP, Vol. 35, No. 1, pp. 393-396.
19. Ferriera, P.M., and Liu, C. R., 1986, “An Analytical Quadratic Model for Geometric Error of a Machine Tool,” Journal of Manufacturing Systems.
20. Chen, J. S., 1991, “Real-time Compensation of Time-varying Volumetric Error on a Machining Center,” Ph.D. Dissertation, University of Michigan.
21. Soons, J. A., Theuws, F. C., and Schellekens, P., 1992, “Modeling the Errors of Multi-Axis Machines: A General Methodology,” Precision Engineering, pp. 5-19.
22. Hatamura, Y., et al., 1993, “Development of an Intelligent Machining Center Incorporating Active Compensation for Thermal Distortion,” Annals of the CIRP, pp. 549-552, Vol. 42, No. 1.
23. Jedrzejewski, J., and Modrzycki, W., 1992, “A New Approach Modeling Thermal Behavior of a Machine Tool Under Service Conditions,” Annals of the CIRP, pp. 455-458, Vol. 41, No. 1.
24. Matsumura, T., et al., 1994, “An Adaptive Prediction of Machining Accuracy in Turning Operation,” Transactions of NAMRI/SME, pp. 305-312, Vol. 23.
25. Mize, C. D., 1993, “Design and Implementation of a Laser Ball-Bar Based Measurement Technique for Machine Tool Calibration,” Master’s Thesis, University of Florida.
26. Ziegert, J. C., and Mize, C. D., 1994, “Laser Ball-Bar: A New Instrument for Machine Tool Metrology,” Precision Engineering, pp. 259-267, Vol. 16, No. 4.
27. Lau, K., Haynes, L., and Hocken, R., 1985, “Robot and Point Sensing Using Laser Tracking System,” Proceedings of Workshop on Robot Standards, Detroit, MI, pp. 104-111.
28. Bryan, J. B., 1982, “A Simple Method for Testing Measuring Machines and Machine Tools. Part I: Principles and applications,” Precision Engineering, Vol. 4, pp. 61-69.
29. Bryan, J. B., 1982, “A Simple Method for Testing Measuring Machines and Machine Tools. Part II: Construction Details,” Precision Engineering, Vol. pp. 125-138.
30. Rumelhart, D. E., Hinton, G.E., and Williams, R. J., 1, “Learning Internal Representations by Error Propagation,” Parallel Distributed Processing, MIT Press, Cambridge, MA, Vol. 1, pp. 318-362.
31. Pao, Y. H., 1989, Adaptive Pattern Recognition and Neural networks, Addison Wesley Publishers, Reading, MA.
32. Aarts, E. H. L., and Korst, J. H. M., 1988, Simulated Annealing and Boltzmann Machines, New York, Wiley.
33. Barto, A. G., Sutton, R. S., and Anderson, C. W., 1983, “Neuron-like Adaptive Elements that can Solve Difficult Learning Control Problems,” IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-13, pp. 834-846, 1993.
34. Lippmann, R. P., 1987, “An Introduction to Computing with Neural Networks,” IEEE ASSP Magazine, pp. 4-22.
35. Mendel, J. M., and McLaren, R. W., 1970, “Reinforcenment Learning Control and Pattern Recognition Systems,” Adaptive Learning and Pattern Recog nition Systems: Theory and Applications, Academic Press, New York, pp. 287-318.
36. Gullapalli, V., 1990, “A Stochastic Reinforcement Learning Algorithm for Learning Real-Valued Functions,” Neural Networks, Vol. 3, pp. 671-692.
37. Berenji, H. R., 1992, “Learning and Tuning Fuzzy Logic Controllers Through Reinforcements,” IEEE Transactions on Neural Networks, Vol. 3, No.5 pp. 724-739.
38. Carpenter, G. A., and Grossberg, S., 1988, “The ART of Adaptive Pattern Recognition by a Self-Organizing Neural Network,” Computer, Vol. 21, pp. 7788.
39. Kohonen, T., 1982, “Self-Organized Formation of Topologically Correct Maps,” Biological Cybernetics, Vol. 43, pp. 56-69.
40. Anderson, J., 1972, “A Simple Neural Network Generating an Interactive Memory,” Mathematical Sciences, Vol. 14, pp. 197-220.
41. Kosko, B., 1972, “Adaptive Bidirectional Associative Memories,” Applied Optics, Vol. 26, pp. 4947-4960.
42. Zadeh, L. A., 1973, “Outline of New Approach to the Analysis of Complex Systems and Decision Processes,” IEEE Transactions on Systems, Man and Cybernetics, SMC-3, Vol. 1, pp. 28-44.
43. Carpenter, G. A., Grossberg, S., and Rosen, D. B., 1991, “Fuzzy ART: Fast Stable Learning and Categorization of Analog Patterns by an Adaptive Resonance System,” Neural Networks, Vol. 4, pp. 759-771.
44. Carpenter, G. A., Grossberg, S., Markuzon, N., Reynolds, J. H., and Rosen, D. B., 1992, “Fuzzy ARTMAP: A Neural Network Architecture For Incremental Supervised Learning of Analog Multidimensional Maps,” IEEE Transactions on Neural Networks, Vol. 3, No. 5, pp. 698-712.
45. Rangwala, S., and Dornfeld, D., 1990, “Sensor Integration Using Neural Networks for Intelligent Tool Condition Monitoring,” ASME Journal of Engineering for Industry, Vol. 112, pp. 219-228.
46. Chryssolouris, G., Domroese, M., and Beaulieu, P., 1992, “Sensor Synthesis for Control of Manufacturing Processes,” ASME Journal of Engineering for Industry, Vol. 114, pp. 158-174.
47. Teshima, T., Shibasaka, T., Takuma, M., and Yamamoto, A., 1993, “Estimation of Cutting Tool Life by Processing Tool Image Data with Neural Network,” Annals of the CIRP, pp. 59-62.
48. Jammu, V. B., and Danai, K., 1993, “Unsupervised Neural Network for Tool Breakage Detection in Turning,” Annals of the CIRP.
49. Monostori, L., 1993, “A Step Towards Intelligent Manufacturing: Modelling and Monitoring of Manufacturing Processes Through Artificial Neural Networks,” Annals of the CIRP, pp. 485-488.
50. Srinivasa, N., and Jouaneh, M., 1991, “An Investigation of Surface Roughness Characterization Using an ART2 Neural Network,” in Sensors, Controls, and Quality Issues in Manufacturing, PED Vol. 55, Metals Park, OH, ASME Winter Annual Meeting, pp. 307-318.
51. Srinivasa, N., Ziegert, J. C., and Smith, S., 1993, “Prediction of Thermal Errors in Machine Tools Using Artificial Neural Networks,” Proceedings of NSF Design and Manufacturing Systems Conference, Charlotte, NC, pp. 1725-1732.