Use of the orthogonal projection approach (OPA) to monitor patch processes

被引:12
作者
Gourvénec, S
Lamotte, C
Pestiaux, P
Massart, DL
机构
[1] Free Univ Brussels, ChemoAC, Inst Pharmaceut, B-1090 Brussels, Belgium
[2] ATOFINA Res, B-7181 Feluy, Belgium
[3] TOTALFINAELF France, Ctr Rech Gonfreville, F-76700 Harfleur, France
关键词
orthogonal projection approach; OPA; multivariate curve resolution; MCR; alternating least squares; ALS; batch; process control; on-line monitoring; near infrared; NIR;
D O I
10.1366/000370203321165241
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
The orthogonal projection approach (OPA) and multivariate curve resolution (MCR) are presented as a way to monitor batch processes using spectroscopic data. Curve resolution allows one to look within a batch and predict on-line real concentration profiles of the different species appearing during reactions. Taking into account the variations of the process by using an augmented matrix of complete batches, the procedure explained here calculates some prediction coefficients that can afterwards be applied for a new batch.
引用
收藏
页码:80 / 87
页数:8
相关论文
共 25 条
[1]   Evaluation of the orthogonal projection approach (OPA) and the SIMPLISMA approach on the Windig standard spectral data sets [J].
De Braekeleer, K ;
Massart, DL .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1997, 39 (02) :127-141
[2]   Assessment of new constraints applied to the alternating least squares method [J].
deJuan, A ;
VanderHeyden, Y ;
Tauler, R ;
Massart, DL .
ANALYTICA CHIMICA ACTA, 1997, 346 (03) :307-318
[3]   Determination of the number of components during mixture analysis using the Durbin-Watson criterion in the Orthogonal Projection Approach and in the SIMPLe-to-use Interactive Self-modelling Mixture Analysis approach [J].
Gourvénec, S ;
Massart, DL ;
Rutledge, DN .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2002, 61 (1-2) :51-61
[4]   CONTROL PROCEDURES FOR RESIDUALS ASSOCIATED WITH PRINCIPAL COMPONENT ANALYSIS [J].
JACKSON, JE ;
MUDHOLKAR, GS .
TECHNOMETRICS, 1979, 21 (03) :341-349
[5]  
KETTENRING JR, 1993, J CLASSIF, V10, P131
[6]   MULTIVARIATE STATISTICAL MONITORING OF PROCESS OPERATING PERFORMANCE [J].
KRESTA, JV ;
MACGREGOR, JF ;
MARLIN, TE .
CANADIAN JOURNAL OF CHEMICAL ENGINEERING, 1991, 69 (01) :35-47
[7]   PROCESS MONITORING AND DIAGNOSIS BY MULTIBLOCK PLS METHODS [J].
MACGREGOR, JF ;
JAECKLE, C ;
KIPARISSIDES, C ;
KOUTOUDI, M .
AICHE JOURNAL, 1994, 40 (05) :826-838
[8]  
MACGREGOR JF, 1992, NATO ASI SERIES F, V143, P241
[9]  
Miller P., 1993, 37 ANN FALL C ASQC R
[10]   MONITORING BATCH PROCESSES USING MULTIWAY PRINCIPAL COMPONENT ANALYSIS [J].
NOMIKOS, P ;
MACGREGOR, JF .
AICHE JOURNAL, 1994, 40 (08) :1361-1375