Detection of chatter vibration in a drilling process using multivariate control charts

Computational Statistics and Data Analysis

Volumn 52, Issue 6, 2008, Pages 3208-3219

  Messaoud, Amor ^a   Weihs, Claus ^a   Hering, Franz ^a  

^a TU DORTMUND UNIVERSITY   (Germany)

Author keywords

Data depth; Drilling process; Multivariate control charts; Time series

Indexed keywords

CLASSIFICATION (OF INFORMATION); DYNAMIC PROGRAMMING; MULTIVARIABLE CONTROL SYSTEMS; REAL TIME SYSTEMS; TIME SERIES ANALYSIS;

MULTIVARIATE CONTROL CHARTS; NONPARAMETRIC CONTROL CHART;

DRILLING;

EID: 39049149938     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2007.09.029     Document Type: Article

References (16)

1. Alwan L.C., and Roberts H.V. Time series modeling for statistical process control. J. Business Econom. Statist. 6 (1988) 87-95
2. Berismis S., Psarakis S., and Panaretos J. Multivariate statistical process control charts: an overview. Qual. Reliab. Eng. Internat. 23 (2005) 517-543
3. Burr M.A., Rafalin E., and Souvaine D.L. Simplicial depth: an improved definition, analysis, and effeciency for the finite sample case. Proceedings of the 16th Canadian Conference on Computation Geometry (2004) 136-139
4. Cheng, A.Y., Ouyang, M., 2001. On algorithms for simplicial depth. In: Proceedings of the 13th Canadian Conference on Computation Geometry. pp. 53-56.
5. Gibbons J.D., and Chakraborti S. Nonparametric Statistical Inference. third ed (1992), Marcel Dekker, New York, NY
6. Hackl P., and Ledolter J. A new nonparametric quality control technique. Commun. Statist. Simulation Comput. 21 (1992) 423-443
7. Jarrett J.E., and Pan X. The quality control chart for monitoring multivariate autocorrelated processes. Comput. Statist. Data Anal. 51 (2007) 3862-3870
8. Liu R.Y. On a notion of data depth based on random simplices. Ann. Statist. 18 (1990) 405-414
9. Liu R.Y. Control charts for multivariate processes. J. Amer. Statist. Assoc. 90 (1995) 1380-1387
10. Liu R.Y., Parelius J.M., and Singh K. Multivariate analysis by data depth: descriptive statistics, graphics and inference (with discussion). Ann. Statist. 27 (1999) 783-858
11. Messaoud, A., 2006. Monitoring strategies for chatter detection in a drilling process. Ph.D. dissertation, Department of Statistics, University of Dortmund.
12. Montgomery D.C., and Mastrangelo C.M. Some statistical process control methods for autocorrelated data. J. Qual. Technol. 23 (1991) 179-193
13. Rousseeuw P.J., and Ruts I. AS 307: Bivariate location depth. Appl. Statist. 45 (1996) 516-526
14. Teräsvirta T., Lin C.-F., and Granger C.W.J. Power of the neural network linearity test. J. Time Series Anal. 14 (1993) 209-220
15. Theis, W., 2004. Modelling varying amplitudes. Ph.D. dissertation, Department of Statistics, University of Dortmund.
16. Weinert K., Webber O., Geppreth A., Zhang Y., and Theis W. Time varying dynamics in BTA deep hole drilling. In: Teti R. (Ed). Proceedings of the 4th CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (2004), Naples, Italy 297-302