Reconstruction-based contribution for process monitoring

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 41, Issue 2 PART 1, 2008, Pages 7889-7894

  Alcala, Carlos ^a   Qin, S Joe ^a  

^a NONE

Author keywords

Fault detection and diagnosis

Indexed keywords

AUTOMATION; MONTE CARLO METHODS; PROCESS CONTROL; PROCESS MONITORING;

COMBINED INDICES; CONTRIBUTION PLOTS; DATA CORRELATIONS; DIAGNOSABILITY; FAULT DETECTION AND DIAGNOSIS; FAULT MAGNITUDES; SINGLE SENSOR;

FAULT DETECTION;

EID: 79961018913     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20080706-5-KR-1001.01333     Document Type: Conference Paper

References (12)

1. G.E.P. Box. Some theorems on quadratic forms applied in the study of analysis of variance problems, I. effect of inequality of variance in the one-way classification. Ann. Math. Statistics, 25:290-302, 1954.
2. G. Cherry and S. J. Qin. Multiblock principal component analysis based on a combined index for semiconductor fault detection and diagnosis. IEEE Trans. on Semiconductor Manufacturing, 19(2):159-172, 2006.
3. R. Dunia and S. J. Qin. A unified geometric approach to process and sensor fault identification: the unidimensional fault case. Comput. Chem. Eng., 22:927-943,1998.
4. P. Miller, R.E. Swanson, and C.F. Heckler. Contribution plots: the missing link in multivariate quality control. In Fall Conf. of the ASQC and ASA, 1993. Milwaukee,WI.
5. P. Nomikos. Statistical monitoring of batch processes. In Preprints of Joint Statistical Meeting, Anaheim, CA, August 1997.
6. P. Nomikos and J.F. MacGregor. Multivariate SPC charts for monitoring batch processes. Technometrics, 37(1):41-59, 1995.
7. S. J. Qin. Statistical process monitoring: Basics and beyond. J. Chemometrics, 17:480-502, 2003.
8. S. J. Qin, S. Valle-Cervantes, and M. Piovoso. On unifying multi-block analysis with applications to decentralized process monitoring. J. Chemometrics, 15:715-742, 2001.
9. J. A. Westerhuis, S.P. Gurden, and A.K. Smilde. Generalized contribution plots in multivariate statistical process monitoring. Chemometrics Intell. Lab. Syst., 51:95-114, 2000.
10. B. M. Wise, N. B Gallagher, R. Bro, J. M. Shaver, W. Winding, and R. S. Koch. PLS Toolbox User Manual. Eigenvector Research Inc., 2006.
11. B.M. Wise and N.B. Gallagher. The process chemometrics approach to process monitoring and fault detection. J. Proc. Cont., 6:329-348, 1996.
12. H. Yue and S. Joe Qin. Reconstruction based fault identification using a combined index. Ind. Eng. Chem. Res., 40:4403-4414, 2001.