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Volumn 17, Issue 8-9, 2003, Pages 480-502

Statistical process monitoring: Basics and beyond

Author keywords

Contribution plots; Fault analysis; Fault detection; Fault identification; Fault reconstruction; Process chemometrics; Process monitoring; Sensor validation

Indexed keywords

PROCESS MONITORING; STATISTICAL PROCESS CONTROL;

EID: 0242354134     PISSN: 08869383     EISSN: None     Source Type: Journal    
DOI: 10.1002/cem.800     Document Type: Conference Paper
Times cited : (1510)

References (87)
  • 2
    • 0013069053 scopus 로고
    • Multivariate statistical methods for monitoring large datasets from chemical processes
    • San Francisco, CA
    • MacGregor JF. Multivariate statistical methods for monitoring large datasets from chemical processes. AIChE Meet., San Francisco, CA, 1989.
    • (1989) AIChE Meet.
    • MacGregor, J.F.1
  • 6
    • 0002878789 scopus 로고
    • Recent advances in multivariate statistical process control: Improving robustness and sensitivity
    • Wise BM, Ricker NL. Recent advances in multivariate statistical process control: improving robustness and sensitivity. Proc. IFAC ADCHEM Symp., 1991; 125-130.
    • (1991) Proc. IFAC ADCHEM Symp. , pp. 125-130
    • Wise, B.M.1    Ricker, N.L.2
  • 8
    • 0003198394 scopus 로고
    • Contribution plots: The missing link in multivariate quality control
    • Milwaukee, WI
    • Miller P, Swanson RE, Heckler CF. Contribution plots: the missing link in multivariate quality control. Fall Conf. of ASQC and ASA, Milwaukee, WI, 1993.
    • (1993) Fall Conf. of ASQC and ASA
    • Miller, P.1    Swanson, R.E.2    Heckler, C.F.3
  • 10
    • 0030269512 scopus 로고    scopus 로고
    • Identification of faulty sensors using principal component analysis
    • Dunia R, Qin SJ, Edgar TF, McAvoy TJ. Identification of faulty sensors using principal component analysis. AIChE J. 1996; 42: 2797-2812.
    • (1996) AIChE J. , vol.42 , pp. 2797-2812
    • Dunia, R.1    Qin, S.J.2    Edgar, T.F.3    McAvoy, T.J.4
  • 11
    • 0002776103 scopus 로고    scopus 로고
    • Process disturbance diagnosis by statistical distance and angle measures
    • San Francisco, CA
    • Raich AC, Cinar A. Process disturbance diagnosis by statistical distance and angle measures. Proc. IFAC Congr., vol. N, San Francisco, CA, 1996; 283-288.
    • (1996) Proc. IFAC Congr. , vol.N , pp. 283-288
    • Raich, A.C.1    Cinar, A.2
  • 12
    • 0031644999 scopus 로고    scopus 로고
    • A unified geometric approach to process and sensor fault identification: The unidimensional fault case
    • Dunia R, Qin SJ. A unified geometric approach to process and sensor fault identification: the unidimensional fault case. Comput. Chem. Eng. 1998; 22: 927-943.
    • (1998) Comput. Chem. Eng. , vol.22 , pp. 927-943
    • Dunia, R.1    Qin, S.J.2
  • 13
    • 0032144398 scopus 로고    scopus 로고
    • Subspace approach to multidimensional fault identification and reconstruction
    • Dunia R, Qin SJ. Subspace approach to multidimensional fault identification and reconstruction. AIChE J. 1998; 44: 1813-1831.
    • (1998) AIChE J. , vol.44 , pp. 1813-1831
    • Dunia, R.1    Qin, S.J.2
  • 14
    • 79960898828 scopus 로고    scopus 로고
    • Fault reconstruction and identification for industrial processes
    • Miami, FL
    • Yue H, Qin SJ. Fault reconstruction and identification for industrial processes. AIChE Ann. Meet., Miami, FL, 1998.
    • (1998) AIChE Ann. Meet.
    • Yue, H.1    Qin, S.J.2
  • 15
    • 0033198809 scopus 로고    scopus 로고
    • Detection, identification and reconstruction of faulty sensors with maximized sensitivity
    • Qin SJ, Li W. Detection, identification and reconstruction of faulty sensors with maximized sensitivity. AIChE J. 1999; 45: 1963-1976.
    • (1999) AIChE J. , vol.45 , pp. 1963-1976
    • Qin, S.J.1    Li, W.2
  • 16
    • 0033083952 scopus 로고    scopus 로고
    • Isolation-enhanced principal component analysis
    • Gertler J, Li W, Huang Y, McAvoy TJ. Isolation-enhanced principal component analysis. AIChE J. 1999; 45(2): 323-334.
    • (1999) AIChE J. , vol.45 , Issue.2 , pp. 323-334
    • Gertler, J.1    Li, W.2    Huang, Y.3    McAvoy, T.J.4
  • 17
    • 0033559979 scopus 로고    scopus 로고
    • Distinguishing between process upsets and sensor malfunctions using sensor redundancy
    • Stork CL, Kowalski BR. Distinguishing between process upsets and sensor malfunctions using sensor redundancy. Chemometrics Intell. Lab. Syst. 1999; 46: 117-131.
    • (1999) Chemometrics Intell. Lab. Syst. , vol.46 , pp. 117-131
    • Stork, C.L.1    Kowalski, B.R.2
  • 18
    • 0242369385 scopus 로고    scopus 로고
    • Development and benchmarking of multivariate statistical process control tools for a semiconductor etch process: Impact of measurement selection and data treatment on sensitivity
    • Hull
    • Wise BM, Gallagher NB, Butler SW, White D, Barna GG. Development and benchmarking of multivariate statistical process control tools for a semiconductor etch process: impact of measurement selection and data treatment on sensitivity. IFAC SAFEPROCESS '97, Hull, 1997.
    • (1997) IFAC SAFEPROCESS '97
    • Wise, B.M.1    Gallagher, N.B.2    Butler, S.W.3    White, D.4    Barna, G.G.5
  • 19
    • 0032118892 scopus 로고    scopus 로고
    • Multiscale PCA with application to multivariate statistical process monitoring
    • Bakshi BR. Multiscale PCA with application to multivariate statistical process monitoring. AIChE J. 1998; 44: 1596-1610.
    • (1998) AIChE J. , vol.44 , pp. 1596-1610
    • Bakshi, B.R.1
  • 20
    • 0031168001 scopus 로고    scopus 로고
    • Recursive exponentially weighted PLS and its applications to adaptive control and prediction
    • Dayal BS, MacGregor JF. Recursive exponentially weighted PLS and its applications to adaptive control and prediction. J. Process Control 1997; 7: 169-179.
    • (1997) J. Process Control , vol.7 , pp. 169-179
    • Dayal, B.S.1    MacGregor, J.F.2
  • 21
    • 0032044750 scopus 로고    scopus 로고
    • Recursive PLS algorithms for adaptive data modeling
    • Qin SJ. Recursive PLS algorithms for adaptive data modeling. Comput. Chem. Eng. 1998; 23: 503-514.
    • (1998) Comput. Chem. Eng. , vol.23 , pp. 503-514
    • Qin, S.J.1
  • 23
    • 0028892168 scopus 로고
    • Disturbance detection and isolation by dynamic principal component analysis
    • Ku W, Storer RH, Georgakis C. Disturbance detection and isolation by dynamic principal component analysis. Chemometrics Intell. Lab. Syst. 1995; 30: 179.
    • (1995) Chemometrics Intell. Lab. Syst. , vol.30 , pp. 179
    • Ku, W.1    Storer, R.H.2    Georgakis, C.3
  • 24
    • 0031208457 scopus 로고    scopus 로고
    • Statistical monitoring of multivariate dynamic processes with state space models
    • Negiz A, Cinar A. Statistical monitoring of multivariate dynamic processes with state space models. AIChE J. 1997; 43: 2002-2020.
    • (1997) AIChE J. , vol.43 , pp. 2002-2020
    • Negiz, A.1    Cinar, A.2
  • 25
    • 0037106519 scopus 로고    scopus 로고
    • Multivariate process monitoring and fault identification using multi-scale PCA
    • Misra M, Qin SJ, Yue H, Ling C. Multivariate process monitoring and fault identification using multi-scale PCA. Comput. Chem. Eng. 2002; 26: 1281-1293.
    • (2002) Comput. Chem. Eng. , vol.26 , pp. 1281-1293
    • Misra, M.1    Qin, S.J.2    Yue, H.3    Ling, C.4
  • 26
    • 0029252734 scopus 로고
    • Multivariate SPC charts for monitoring batch processes
    • Nomikos P, MacGregor JF. Multivariate SPC charts for monitoring batch processes. Technometrics 1995; 37: 41-59.
    • (1995) Technometrics , vol.37 , pp. 41-59
    • Nomikos, P.1    MacGregor, J.F.2
  • 28
    • 0019702744 scopus 로고
    • Rectification of process measurement data in the presence of gross errors
    • Romagnoli JA, Stephanopoulos G. Rectification of process measurement data in the presence of gross errors. Chem. Eng. Sci. 1981; 36: 1849-1863.
    • (1981) Chem. Eng. Sci. , vol.36 , pp. 1849-1863
    • Romagnoli, J.A.1    Stephanopoulos, G.2
  • 29
    • 0023422691 scopus 로고
    • Generalized likelihood ratios for gross error identification
    • Narasimhan S, Mah RSH. Generalized likelihood ratios for gross error identification. AIChE J. 1987; 33: 1514-1521.
    • (1987) AIChE J. , vol.33 , pp. 1514-1521
    • Narasimhan, S.1    Mah, R.S.H.2
  • 30
    • 0024065779 scopus 로고
    • Generalized likelihood ratios for gross error identification in dynamic processes
    • Narasimhan S, Mah RSH. Generalized likelihood ratios for gross error identification in dynamic processes. AIChE J. 1988; 34: 1321-1331.
    • (1988) AIChE J. , vol.34 , pp. 1321-1331
    • Narasimhan, S.1    Mah, R.S.H.2
  • 31
    • 0021455782 scopus 로고
    • Analytical redundancy and the design of robust failure detection systems
    • Chow EY, Willsky AS. Analytical redundancy and the design of robust failure detection systems. IEEE Trans. Automatic Control 1984; 29: 603-614.
    • (1984) IEEE Trans. Automatic Control , vol.29 , pp. 603-614
    • Chow, E.Y.1    Willsky, A.S.2
  • 32
    • 0021468997 scopus 로고
    • Process fault detection based on modeling and estimation methods - A survey
    • Isermann R. Process fault detection based on modeling and estimation methods - a survey. Automatica 1984; 20: 387-404.
    • (1984) Automatica , vol.20 , pp. 387-404
    • Isermann, R.1
  • 33
    • 0024122587 scopus 로고
    • Survey of model-based failure detection and isolation in complex plants
    • Gertler J. Survey of model-based failure detection and isolation in complex plants. IEEE Control Syst. Mag. 1988; 12: 3-11.
    • (1988) IEEE Control Syst. Mag. , vol.12 , pp. 3-11
    • Gertler, J.1
  • 35
    • 0025421966 scopus 로고
    • Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy - A survey and some new results
    • Frank PM. Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy - a survey and some new results. Automatica 1990; 26: 459-474.
    • (1990) Automatica , vol.26 , pp. 459-474
    • Frank, P.M.1
  • 36
    • 0345929238 scopus 로고    scopus 로고
    • Analytical and qualitative model-based fault diagnosis - A survey and some new results
    • Frank PM. Analytical and qualitative model-based fault diagnosis - a survey and some new results. Eur. J. Control 1996; 2: 6-28.
    • (1996) Eur. J. Control , vol.2 , pp. 6-28
    • Frank, P.M.1
  • 37
    • 0001194903 scopus 로고
    • A proposal for handling missing data
    • Cleason TC, Staelin R. A proposal for handling missing data. Psychometrika 1975; 40: 229-252.
    • (1975) Psychometrika , vol.40 , pp. 229-252
    • Cleason, T.C.1    Staelin, R.2
  • 39
    • 0030296884 scopus 로고    scopus 로고
    • Missing data methods in PCA and PLS: Score calculations with incomplete observations
    • Nelson PRC, Taylor PA, MacGregor JF. Missing data methods in PCA and PLS: score calculations with incomplete observations. Chemometrics Intell. Lab. Syst. 1996; 35: 45-65.
    • (1996) Chemometrics Intell. Lab. Syst. , vol.35 , pp. 45-65
    • Nelson, P.R.C.1    Taylor, P.A.2    MacGregor, J.F.3
  • 40
    • 0242274629 scopus 로고
    • Multivariate SPC methods for monitoring and diagnosing of process performance
    • Kourti T, MacGregor JF. Multivariate SPC methods for monitoring and diagnosing of process performance. Proc. PSE, 1994; 739-746.
    • (1994) Proc. PSE , pp. 739-746
    • Kourti, T.1    MacGregor, J.F.2
  • 41
    • 0029342346 scopus 로고
    • Detection of gross errors in data reconciliation by principal component analysis
    • Tong H, Crowe CM. Detection of gross errors in data reconciliation by principal component analysis. AIChE J. 1995; 41: 1712-1722.
    • (1995) AIChE J. , vol.41 , pp. 1712-1722
    • Tong, H.1    Crowe, C.M.2
  • 42
    • 0026849990 scopus 로고
    • Autoassociative neural networks
    • Kramer MA. Autoassociative neural networks. Comput. Chem. Eng. 1992; 16: 313-328.
    • (1992) Comput. Chem. Eng. , vol.16 , pp. 313-328
    • Kramer, M.A.1
  • 43
    • 0343325877 scopus 로고
    • Statistical process control of multivariate processes
    • MacGregor JF. Statistical process control of multivariate processes. Prepr. IFAC ADCHEM, 1994.
    • (1994) Prepr. IFAC ADCHEM
    • MacGregor, J.F.1
  • 44
    • 0029267381 scopus 로고
    • Statistical process control of multivariate processes
    • MacGregor JF, Kourti T. Statistical process control of multivariate processes. Control Eng. Pract. 1995; 3: 403-414.
    • (1995) Control Eng. Pract. , vol.3 , pp. 403-414
    • MacGregor, J.F.1    Kourti, T.2
  • 45
    • 0030530039 scopus 로고    scopus 로고
    • The process chemometrics approach to process monitoring and fault detection
    • Wise BM, Gallagher NB. The process chemometrics approach to process monitoring and fault detection. J. Process Control 1996; 6: 329-348.
    • (1996) J. Process Control , vol.6 , pp. 329-348
    • Wise, B.M.1    Gallagher, N.B.2
  • 47
    • 0025514444 scopus 로고
    • A theoretical basis for the use of principal component models for monitoring multivariate processes
    • Wise BM, Ricker NL, Veltkamp DF, Kowalski BR. A theoretical basis for the use of principal component models for monitoring multivariate processes. Process Control Qual. 1990; 1: 41-51.
    • (1990) Process Control Qual. , vol.1 , pp. 41-51
    • Wise, B.M.1    Ricker, N.L.2    Veltkamp, D.F.3    Kowalski, B.R.4
  • 49
    • 0035427805 scopus 로고    scopus 로고
    • Fault diagnosis with multivariate statistical models. Part I: Using steady state fault signatures
    • Yoon S, MacGregor JF. Fault diagnosis with multivariate statistical models. Part I: using steady state fault signatures. J. Process Control 2001; 11: 387-400.
    • (2001) J. Process Control , vol.11 , pp. 387-400
    • Yoon, S.1    MacGregor, J.F.2
  • 50
    • 0034842247 scopus 로고    scopus 로고
    • Extracting fault subspaces for fault identification of a polyester film process
    • Arlington, VA
    • Valle-Cervantes S, Qin SJ, Piovoso MJ, Bachmann M, Mandakoro N. Extracting fault subspaces for fault identification of a polyester film process. Proc. ACC, Arlington, VA, 2001; 4466-4471.
    • (2001) Proc. ACC , pp. 4466-4471
    • Valle-Cervantes, S.1    Qin, S.J.2    Piovoso, M.J.3    Bachmann, M.4    Mandakoro, N.5
  • 51
    • 0035802262 scopus 로고    scopus 로고
    • Reconstruction based fault identification using a combined index
    • Yue H, Qin SJ. Reconstruction based fault identification using a combined index. Ind. Eng. Chem. Res. 2001; 40: 4403-4414.
    • (2001) Ind. Eng. Chem. Res. , vol.40 , pp. 4403-4414
    • Yue, H.1    Qin, S.J.2
  • 53
    • 0034282185 scopus 로고    scopus 로고
    • Statistical and causal model-based approaches to fault detection and isolation
    • Yoon S, MacGregor JF. Statistical and causal model-based approaches to fault detection and isolation. AIChE J. 2000; 46: 1813-1824.
    • (2000) AIChE J. , vol.46 , pp. 1813-1824
    • Yoon, S.1    MacGregor, J.F.2
  • 54
    • 0035546347 scopus 로고    scopus 로고
    • Consistent dynamic PCA based on errors-in-variables subspace identification
    • Li W, Qin SJ. Consistent dynamic PCA based on errors-in-variables subspace identification. J. Process Control 2001; 11: 661-678.
    • (2001) J. Process Control , vol.11 , pp. 661-678
    • Li, W.1    Qin, S.J.2
  • 55
    • 0030127409 scopus 로고    scopus 로고
    • Statistical process monitoring and disturbance diagnosis in multivariate continuous processes
    • Raich A, Cinar A. Statistical process monitoring and disturbance diagnosis in multivariate continuous processes. AIChE J. 1996; 42: 995-1009.
    • (1996) AIChE J. , vol.42 , pp. 995-1009
    • Raich, A.1    Cinar, A.2
  • 56
    • 0018503842 scopus 로고
    • Control procedures for residuals associated with principal component analysis
    • Jackson JE, Mudholkar G. Control procedures for residuals associated with principal component analysis. Technometrics 1979; 21: 341-349.
    • (1979) Technometrics , vol.21 , pp. 341-349
    • Jackson, J.E.1    Mudholkar, G.2
  • 57
    • 0000235653 scopus 로고
    • 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
    • Box GEP. 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. Statist. 1954; 25: 290-302.
    • (1954) Ann. Math. Statist. , vol.25 , pp. 290-302
    • Box, G.E.P.1
  • 58
    • 0001925804 scopus 로고
    • Multivariate control charts for individual observations
    • Tracy ND, Young JC, Mason RL. Multivariate control charts for individual observations. J. Qual. Technol. 1992; 24: 88-95.
    • (1992) J. Qual. Technol. , vol.24 , pp. 88-95
    • Tracy, N.D.1    Young, J.C.2    Mason, R.L.3
  • 59
    • 0009928479 scopus 로고
    • The detection of errors in multivariate data using principal components
    • Hawkins DM. The detection of errors in multivariate data using principal components. J. Am. Statist. Assoc. 1974; 69: 340-344.
    • (1974) J. Am. Statist. Assoc. , vol.69 , pp. 340-344
    • Hawkins, D.M.1
  • 60
    • 0002336320 scopus 로고
    • Mahalanobis distances and angles
    • Krishnaiah PR (ed.). North-Holland: Amsterdam
    • Mardia KV. Mahalanobis distances and angles. In Multivariate Analysis - IV, Krishnaiah PR (ed.). North-Holland: Amsterdam, 1977; 495-511.
    • (1977) Multivariate Analysis - IV , pp. 495-511
    • Mardia, K.V.1
  • 61
    • 0003038150 scopus 로고
    • 2 statistic
    • Krishnaiah PR (ed.). North-Holland: Amsterdam
    • 2 statistic. In Multivariate Analysis - VI, Krishnaiah PR (ed.). North-Holland: Amsterdam, 1985; 583-597.
    • (1985) Multivariate Analysis - VI , pp. 583-597
    • Takemura, A.1
  • 62
    • 0003000612 scopus 로고
    • Nonlinear estimation by iterative least squares procedures
    • David F (ed.). Wiley: New York
    • Wold H. Nonlinear estimation by iterative least squares procedures. In Research Papers in Statistics, David F (ed.). Wiley: New York, 1966.
    • (1966) Research Papers in Statistics
    • Wold, H.1
  • 63
    • 0004202872 scopus 로고    scopus 로고
    • Determining the number of principal components for best reconstruction
    • Corfu
    • Qin SJ, Dunia R. Determining the number of principal components for best reconstruction. Proc. 5th IFAC DYCOPS, Corfu, 1998; 359-364.
    • (1998) Proc. 5th IFAC DYCOPS , pp. 359-364
    • Qin, S.J.1    Dunia, R.2
  • 64
    • 84951601886 scopus 로고
    • Cross validatory estimation of the number of components in factor and principal component analysis
    • Wold S. Cross validatory estimation of the number of components in factor and principal component analysis. Technometrics 1978; 20: 397-406.
    • (1978) Technometrics , vol.20 , pp. 397-406
    • Wold, S.1
  • 65
    • 0036628052 scopus 로고    scopus 로고
    • Statistical process monitoring based on dissimilarity of process data
    • Kano M, Nagao K, Hasebe S, Hashimoto I, Ohno H. Statistical process monitoring based on dissimilarity of process data. AIChE J. 2002; 48: 1231-1240.
    • (2002) AIChE J. , vol.48 , pp. 1231-1240
    • Kano, M.1    Nagao, K.2    Hasebe, S.3    Hashimoto, I.4    Ohno, H.5
  • 66
    • 0034643075 scopus 로고    scopus 로고
    • Fault diagnosis and Fisher discriminant analysis, discriminant partial least squares, and principal component analysis
    • Chiang LH, Russell EL, Braatz RD. Fault diagnosis and Fisher discriminant analysis, discriminant partial least squares, and principal component analysis. Chemometrics Intell. Lab. Syst. 2000; 50: 243-252.
    • (2000) Chemometrics Intell. Lab. Syst. , vol.50 , pp. 243-252
    • Chiang, L.H.1    Russell, E.L.2    Braatz, R.D.3
  • 67
    • 0030262558 scopus 로고    scopus 로고
    • Multivariate SPC methods for process and product monitoring
    • Kourti T, MacGregor JF. Multivariate SPC methods for process and product monitoring. J. Qual. Technol. 1996; 28: 409-428.
    • (1996) J. Qual. Technol. , vol.28 , pp. 409-428
    • Kourti, T.1    MacGregor, J.F.2
  • 68
    • 85153994181 scopus 로고    scopus 로고
    • Method of controlling a manufacturing process using multivariate analysis. US Patent 5442562, 1995
    • Hopkins RW, Miller P, Swanson RE, Scheible JJ. Method of controlling a manufacturing process using multivariate analysis. US Patent 5442562, 1995.
    • Hopkins, R.W.1    Miller, P.2    Swanson, R.E.3    Scheible, J.J.4
  • 69
    • 0002970413 scopus 로고    scopus 로고
    • Statistical monitoring of batch processes
    • Anaheim, CA
    • Nomikos P. Statistical monitoring of batch processes. Prepr. Joint Statistical Meet., Anaheim, CA, 1997.
    • (1997) Prepr. Joint Statistical Meet.
    • Nomikos, P.1
  • 70
    • 0001282938 scopus 로고    scopus 로고
    • On unifying multiblock analysis with applications to decentralized process monitoring
    • Qin SJ, Valle-Cervantes S, Piovoso M. On unifying multiblock analysis with applications to decentralized process monitoring. J. Chemometrics 2001; 15: 715-742.
    • (2001) J. Chemometrics , vol.15 , pp. 715-742
    • Qin, S.J.1    Valle-Cervantes, S.2    Piovoso, M.3
  • 71
  • 74
    • 64149085513 scopus 로고    scopus 로고
    • Semiconductor process monitoring and fault detection with recursive multiway PCA based on a combined index
    • Salt Lake City, UT
    • Cherry G, Good R, Qin SJ. Semiconductor process monitoring and fault detection with recursive multiway PCA based on a combined index. AEC/APC Symp. XIV, Salt Lake City, UT, 2002.
    • (2002) AEC/APC Symp. XIV
    • Cherry, G.1    Good, R.2    Qin, S.J.3
  • 76
    • 0000736392 scopus 로고    scopus 로고
    • Analysis of multiblock and hierarchical PCA and PLS models
    • Westerhuis JA, Kourti T, MacGregor JF. Analysis of multiblock and hierarchical PCA and PLS models. J. Chemometrics 1998; 12: 301-321.
    • (1998) J. Chemometrics , vol.12 , pp. 301-321
    • Westerhuis, J.A.1    Kourti, T.2    MacGregor, J.F.3
  • 77
    • 0035142851 scopus 로고    scopus 로고
    • Comments on three-way analyses used for batch process data
    • Smilde A. Comments on three-way analyses used for batch process data. J. Chemometrics 2001; 15: 15-27.
    • (2001) J. Chemometrics , vol.15 , pp. 15-27
    • Smilde, A.1
  • 78
    • 8744317826 scopus 로고    scopus 로고
    • Process monitoring based on canonical variate analysis
    • Banff
    • Wang Y, Seborg D, Larimore W. Process monitoring based on canonical variate analysis. Proc. ADCHEM 97, Banff, 1997; 523-528.
    • (1997) Proc. ADCHEM 97 , pp. 523-528
    • Wang, Y.1    Seborg, D.2    Larimore, W.3
  • 79
    • 0001212550 scopus 로고    scopus 로고
    • Detection and identification of faulty sensors in dynamic processes
    • Qin SJ, Li W. Detection and identification of faulty sensors in dynamic processes. AIChE J. 2001; 47: 1581-1593.
    • (2001) AIChE J. , vol.47 , pp. 1581-1593
    • Qin, S.J.1    Li, W.2
  • 80
    • 0001648555 scopus 로고    scopus 로고
    • Research issues and ideas in statistical process control
    • Woodall WH, Montgomery DC. Research issues and ideas in statistical process control. J. Qual. Technol. 1999; 31: 376-386.
    • (1999) J. Qual. Technol. , vol.31 , pp. 376-386
    • Woodall, W.H.1    Montgomery, D.C.2
  • 82
    • 0035421343 scopus 로고    scopus 로고
    • Sensor validation and process fault diagnosis for FCC units under MPC feedback
    • Pranatyasto TN, Qin SJ. Sensor validation and process fault diagnosis for FCC units under MPC feedback. Control Eng. Pract. 2001; 9: 877-888.
    • (2001) Control Eng. Pract. , vol.9 , pp. 877-888
    • Pranatyasto, T.N.1    Qin, S.J.2
  • 84
    • 0032469932 scopus 로고    scopus 로고
    • Control performance monitoring - A review and assessment
    • Qin SJ. Control performance monitoring - a review and assessment. Comput. Chem. Eng. 1998; 23: 178-186.
    • (1998) Comput. Chem. Eng. , vol.23 , pp. 178-186
    • Qin, S.J.1
  • 85
    • 0141836624 scopus 로고    scopus 로고
    • Recent developments in controller performance monitoring and assessment techniques
    • Tuscon, AZ
    • Harris TJ, Seppala CT. Recent developments in controller performance monitoring and assessment techniques. Chemical Process Control - CPC VI, Tuscon, AZ, 2002; 208-222.
    • (2002) Chemical Process Control - CPC VI , pp. 208-222
    • Harris, T.J.1    Seppala, C.T.2
  • 86
    • 0002171478 scopus 로고    scopus 로고
    • Controller performance monitoring and diagnosis: Experiences and challenges
    • Tahoe, CA
    • Kozub DJ. Controller performance monitoring and diagnosis: experiences and challenges. Fifth Int. Conf. on Chemical Process Control, Tahoe, CA, 1996; 83-96.
    • (1996) Fifth Int. Conf. on Chemical Process Control , pp. 83-96
    • Kozub, D.J.1
  • 87
    • 0033080258 scopus 로고    scopus 로고
    • A review of performance monitoring and assessment techniques for univariate and multivariate control systems
    • Harris TJ, Seppala CT, Desborough LD. A review of performance monitoring and assessment techniques for univariate and multivariate control systems. J. Process Control 1999; 9: 1-17.
    • (1999) J. Process Control , vol.9 , pp. 1-17
    • Harris, T.J.1    Seppala, C.T.2    Desborough, L.D.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.