• DocumentCode
    300593
  • Title

    Multi-stage batch process monitoring

  • Author

    Dong, Dong ; McAvoy, Thomas J.

  • Author_Institution
    Dept. of Chem. Eng., Maryland Univ., College Park, MD, USA
  • Volume
    3
  • fYear
    1995
  • fDate
    21-23 Jun 1995
  • Firstpage
    1857
  • Abstract
    Batch processes are very important to the chemical and manufacturing industries. Techniques for monitoring these batch processes to ensure their safe operation and that they produce consistent high quality products are needed. Nomikos and MacGregor (1994) present a multi-way principal component analysis (MPCA) approach for monitoring batch processes, and test results show that the method is simple, powerful, and effective. However MPCA is a linear method, and most batch processes are nonlinear. In this paper a nonlinear principal component analysis (NLPCA) method (Dong-McAvoy, 1993) is used for batch process monitoring. The main focus of this paper is on multi-stage batch process monitoring. The proposed approach and special problems for multi-stage batch processes are illustrated through a detailed simulation study
  • Keywords
    batch processing (industrial); chemical industry; manufacturing industries; monitoring; process control; chemical industries; manufacturing industries; multi-stage batch process monitoring; multi-way principal component analysis; nonlinear principal component analysis; Chemical engineering; Chemical industry; Chemical processes; Costs; Ear; Educational institutions; Monitoring; Principal component analysis; Production; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, Proceedings of the 1995
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-2445-5
  • Type

    conf

  • DOI
    10.1109/ACC.1995.531208
  • Filename
    531208