Batch process monitoring using on-line MIR spectroscopy

被引:5
|
作者
van Sprang, ENM [1 ]
Ramaker, HJ [1 ]
Boelens, HFM [1 ]
Westerhuis, JA [1 ]
Whiteman, D [1 ]
Baines, D [1 ]
Weaver, I [1 ]
机构
[1] Univ Amsterdam, Dept Chem Engn, NL-1018 WV Amsterdam, Netherlands
关键词
D O I
10.1039/b209826c
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Many high quality products are produced in a batch wise manner. One of the characteristics of a batch process is the recipe driven nature. By repeating the recipe in an identical manner a desired end-product is obtained. However, in spite of repeating the recipe in an identical manner, process differences occur. These differences can be caused by a change of feed stock supplier or impurities in the process. Because of this, differences might occur in the end-product quality or unsafe process situations arise. Therefore, the need to monitor an industrial batch process exists. An industrial process is usually monitored by process measurements such as pressures and temperatures. Nowadays, due to technical developments, spectroscopy is more and more used for process monitoring. Spectroscopic measurements have the advantage of giving a direct chemical insight in the process. Multivariate statistical process control (MSPC) is a statistical way of monitoring the behaviour of a process. Combining spectroscopic measurements with MSPC will notice process perturbations or process deviations from normal operating conditions in a very simple manner. In the following an application is given of batch process monitoring. It is shown how a calibration model is developed and used with the principles of MSPC. Statistical control charts are developed and used to detect batches with a process upset.
引用
收藏
页码:98 / 102
页数:5
相关论文
共 50 条
  • [41] Stormwater monitoring using on-line UV-Vis spectroscopy
    Huang, Jianyin
    Chow, Christopher W. K.
    Shi, Zhining
    Fabris, Rolando
    Mussared, Amanda
    Hallas, Gary
    Monis, Paul
    Jin, Bo
    Saint, Christopher P.
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (13) : 19530 - 19539
  • [42] On-line monitoring of biogenic isoprene emissions using photoacoustic spectroscopy
    Dahnke, H
    Kahl, J
    Schüler, G
    Boland, W
    Urban, W
    Kühnemann, F
    APPLIED PHYSICS B-LASERS AND OPTICS, 2000, 70 (02): : 275 - 280
  • [43] On-line monitoring of biogenic isoprene emissions using photoacoustic spectroscopy
    H. Dahnke
    J. Kahl
    G. Schüler
    W. Boland
    W. Urban
    F. Kühnemann
    Applied Physics B, 2000, 70 : 275 - 280
  • [44] On-line Batch Process Monitoring with Improved Multi-way Independent Component Analysis
    Guo Hui
    Li Hongguang
    CHINESE JOURNAL OF CHEMICAL ENGINEERING, 2013, 21 (03) : 263 - 270
  • [45] On-Line Adaptive and Nonlinear Process Monitoring of a Pilot-Scale Sequencing Batch Reactor
    Chang Kyoo Yoo
    In-Beum Lee
    Peter A. Vanrolleghem
    Environmental Monitoring and Assessment, 2006, 119 : 349 - 366
  • [46] On-line infrared spectroscopy for bioprocess monitoring
    Landgrebe, Daniel
    Haake, Claas
    Hoepfner, Tim
    Beutel, Sascha
    Hitzmann, Bernd
    Scheper, Thomas
    Rhiel, Martin
    Reardon, Kenneth F.
    APPLIED MICROBIOLOGY AND BIOTECHNOLOGY, 2010, 88 (01) : 11 - 22
  • [47] On-line infrared spectroscopy for bioprocess monitoring
    Daniel Landgrebe
    Claas Haake
    Tim Höpfner
    Sascha Beutel
    Bernd Hitzmann
    Thomas Scheper
    Martin Rhiel
    Kenneth F. Reardon
    Applied Microbiology and Biotechnology, 2010, 88 : 11 - 22
  • [48] On-line multivariate statistical monitoring of batch processes using Gaussian mixture model
    Chen, Tao
    Zhang, Jie
    COMPUTERS & CHEMICAL ENGINEERING, 2010, 34 (04) : 500 - 507
  • [49] On-line Monitoring of Batch Processes Using Additive Kernel Partial Least Square
    Ma, Ziang
    Wang, Huangang
    Zhou, Junwu
    PROCEEDINGS OF 2017 CHINESE INTELLIGENT AUTOMATION CONFERENCE, 2018, 458 : 263 - 271
  • [50] On-line monitoring of batch processes using Kalman filter and multivariate statistical methods
    Di, Liqing
    Xiong, Zhihua
    Cao, Yujin
    Yang, Xianhui
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 5511 - +