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A software system for variables comparison of a paper machine for improved performance
Dalarna University, School of Technology and Business Studies, Energy Technology.
Dalarna University, School of Technology and Business Studies, Energy Technology.
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Today paper is to find everywhere, and the production factories always need to increase the

productivity if they want to stay competitive. Stora Enso Kvarnsveden has one of the biggest

magazine paper machines in the world, which produces around 1900 meters of paper per

minute. The production process is highly automatized, which reduces the number of operators

that work on the machine. Still, process variations can cause brakes in the paper web and lead

to loss of income, energy and paper production. It may also have a direct impact on the paper

quality. This report is focusing the following question:

How to keep the Paper Machine production process under controlled conditions?

To make a data analysis fully relevant, we need to use the most important variables of the

machine. By analyzing these data some unexpected behavior and variation of process values

can be pointed out. The analyzing tool needs to be fast and portable, and therefore a software

system has been developed. By comparing process data with reference data this software can

make a powerful analysis.

The created software is intended to be used either by operators or engineers. The most

important results are collected in a file. In this text file, the comparison function gives the

results which are stored in a CSV-format. Furthermore, an auto-update function allows the

users to run it automatically. Graphical presentations are supporting the interpretation of the

results.

Place, publisher, year, edition, pages
2018.
Keywords [en]
Comparison Software, Database, Data analysis, Paper machine settings, Production management, Failures detection
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:du-28781OAI: oai:DiVA.org:du-28781DiVA, id: diva2:1257153
Available from: 2018-10-19 Created: 2018-10-19

Open Access in DiVA

fulltext(3050 kB)26 downloads
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File name FULLTEXT01.pdfFile size 3050 kBChecksum SHA-512
9bd4154625ca389ffa43b937245db89cae1b1faf93e282eb9c3359be4d110074ee62f7f1cb946a9084b4b2a5cbd3a19dbcc9074ef844cbd4657a48a40a80a7a8
Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf