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Analysing cross directional control in fine paper production
2006 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

A perfect paper machine would not need any control action. However, defects in the production process and disturbances in raw material cause instability which requires control actions. The compensations made in the controlled variables often cause variations in other properties. In order to produce a perfect product without variations in any properties, the goal must be to eliminate the defects and disturbances causing control action. By studying the actions from the control system, it is possible to identify the defects in the process. In order to further investigate the potential of studying the output from the control system a study was made for a Fine Paper machine (PM9 at Grycksbo Mill). In this thesis a number of cross profile controls were studied simultaneously. Another interesting approach to identify primary causes of disturbances is by implementing an online analysis. This thesis shows that variance component analysis can be used to identify periods when the control action is unusually high. The authors believe that the best results can be reached if the variance component analysis is applied on data from one to three hours. In order to be able to estimate alarm limits the slower variations in control activity need to be filtered out. This is done with EWMA. The usage of variance component analysis makes an implementation of an online analysis easy, since the method is based on calculations that can be performed in Excel. Furthermore, the thesis shows that PCA is a very effective method to characterize the changes in the control action. It can also be concluded that the control for basis weight is the most important variable if multiple CD-controls are analysed.

Place, publisher, year, edition, pages
Keyword [en]
Technology, paper machines, control systems
Keyword [sv]
URN: urn:nbn:se:ltu:diva-43956ISRN: LTU-EX--06/074--SELocal ID: 1c371d94-6bd2-4eaf-a7e7-a292cbaa3080OAI: diva2:1017230
Subject / course
Student thesis, at least 30 credits
Educational program
Industrial and Management Engineering, master's level
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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