Development of a fuzzy-nets-based in-process surface roughness adaptive control system in turning operations

Expert Systems with Applications

Volumn 30, Issue 4, 2006, Pages 592-604

  Kirby, E Daniel ^a   Chen, Joseph C ^a   Zhang, Julie Z ^a  

^a Iowa State University of Science and Technology   (United States)

Author keywords

Adaptive control; Fuzzy nets; Surface roughness prediction; Turning

Indexed keywords

ACCELEROMETERS; DATA REDUCTION; FUZZY CONTROL; MATHEMATICAL MODELS; SURFACE ROUGHNESS; TURNING;

FEED RATE; FUZZY-NETS; FUZZY-NETS MODELS; SURFACE ROUGHNESS PREDICTION;

ADAPTIVE CONTROL SYSTEMS;

EID: 33144478321     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2005.07.005     Document Type: Article

References (25)

1. Adaptive control maximizes metal removal. (2004, June 18). Metalworking production. Retrieved October 8, 2004: http://www.e4production.net/story.aspx? uid=a9101370-7633-438d-b44d-b695990f80c3.
2. E.J.A. Armarego, and R.H. Brown The machining of metals 1969 Prentice-Hall Englewood Cliffs, NJ
3. ASME International Surface texture symbols (revision of ANSI Y14.36-1978 (R1993) 2002 ASME International Fairfield, NJ (ASME designation Y14.36M - 1996 (R 2002))
4. A.B. Badiru, and J.Y. Cheung Fuzzy engineering expert systems with neural network applications 2002 Wiley New York
5. J.C. Chen An effective fuzzy-nets training scheme for monitoring tool breakage Journal of Intelligent Manufacturing 11 1 2000 85 101
6. Clausing/Colchester Company Storm CNC A50 manual 1999 Clausing/Colchester Company Kalamazoo, MI
7. G.W. Cobb Introduction to design and analysis of experiments 1998 Springer New York
8. D.E. Dimla Sr. The correlation of vibration signal features to cutting tool wear in a metal turning operation International Journal of Advanced Manufacturing Technology 19 10 2002 705 713
9. W.E. Drews Surface texture measurement errors-stylus type instruments Quality 31 10 1992 41 44
10. C.-X. Feng, and X.-F. Wang Development of empirical models for surface roughness prediction in finish turning International Journal of Advanced Manufacturing Technology 20 2002 348 356
11. L.H. Huang, and J.C. Chen A multiple regression model to predict in-process surface roughness in turning operation via accelerometer Journal of Industrial Technology 17 2 2001 1 8
12. Industrial Automation Tool condition monitoring systems Featured products and services 2003 (Retrieved on July 15, 2004: http://www.industrialautomation. cc/modules.php?op=modload&name=News&file=article&sid= 52&POSTNUKESID=a35f8423ae2ce6d2b56b4c148845e8b6.)
13. R. Isermann, K.-H. Lachmann, and D. Matko Adaptive control systems 1992 Prentice-Hall United Kingdom
14. V. Kecman Learning and soft computing: Support vector machines, neural networks, and fuzzy logic models 2001 MIT Press Cambridge, MA
15. S.I. Kim, R.G. Landers, and A.G. Ulsoy Robust machining force control with process compensation ASME Journal of Manufacturing Science and Engineering 125 3 2003 423 430
16. Kirby, E. D. (2005). Development of a fuzzy nets-based in-process adaptive surface roughness control (FN-IP-ASRC) system for CNC turning operations. Doctoral Dissertation, Iowa State University.
17. J.F. Kreider, P.S. Curtiss, T.B. Sheridan, S.-H. Huang, and R.M. Nelson Mechanical systems control F. Kreith Mechanical engineering handbook (Section 6) 1999 CRC Press LLC Boca Raton, FL
18. H.-X. Li, C.L.P. Chen, and H.-P. Huang Fuzzy neural intelligent systems: Mathematical foundation and the applications in engineering 2001 CRC Press LLC Boca Raton, FL
19. E. Liasi, and W.P.T. North Surface roughness enhancement in a turning operation via adaptive STR control of the depth of cut ASME Journal of Manufacturing Science and Engineering 125 2 2003 289 296
20. M. Oakham Artful dodges Metalworking production 2002 (Retrieved October 8, 2004: http://www.e4production.net/story.aspx?uid=a9101370-7633-438d-b44d- b695990f80c3 )
21. K.A. Risbood, U.S. Dixit, and A.D. Sahasrabudhe Prediction of surface roughness and dimensional deviation by measuring cutting forces and vibrations in turning Journal of Materials Processing Technology 132 1-3 2003 203 214
22. M. Thomas, Y. Beauchamp, A.Y. Youssef, and J. Masounave Effect of tool vibrations on surface roughness during lathe dry turning process Computers and Industrial Engineering 31 3/4 1995 637 644
23. Vernon, A., & Özel, T. (2003). Factors affecting surface roughness in finish hard turning. Paper presented at the 17th international conference on production research, Blacksburg, VA.
24. J. Wang A. Kusiak Computational intelligence in manufacturing handbook 2001 CRC Press LLC Boca Raton, FL
25. A. Zilouchian M. Jamshidi Intelligent control systems using soft computing methodologies 2001 CRC Press LLC Boca Raton, FL