Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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
Discrete Event Simulation-based optimization of Sawmill Production: A Study on Advanced Automation and Digitization performed at Stora Enso, Grums.
University West, Department of Engineering Science.
2023 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The purpose of this thesis is to examine the feasibility of automation and digitalization in the Swedish sawmill sector, with a particular emphasis on the Stora Enso Gruvön sawmill. Maintaining a high standard of quality while increasing sawmill productivity is the goal. To examine potential outcomes and pinpoint optimization opportunities, a Discrete Event Simulation (DES) model in Tecnomatix Plant Simulation is built. Historical data supports the conclusion that the simulation model faithfully represents the actual industrial layout and processes. Production flow, throughput, and efficiency are all boosted by the model, as shown experimentally and via simulation. Waste and bottlenecks like long setup periods and insufficient dryer capacity may be found with the model's assistance as well. Three possible scenarios for a sawmill are evaluated, and the third, which incorporates the findings from the other two, has the greatest potential for improving production and efficiency. The research found that DES models accurately portray production systems, which improved decision-making and allowed for more manufacturing process optimization. Though beneficial, DES implementation calls for skilled personnel and ready access to data. Overall, the thesis shows how automation and digitalization may boost sawmill efficiency, and it provides real-world applications for simulation modeling in industrial optimization

Place, publisher, year, edition, pages
2023. , p. 51
Keywords [en]
Simulation, Sawmill, DES, Optimization, Digitization
National Category
Robotics and automation
Identifiers
URN: urn:nbn:se:hv:diva-20373Local ID: EXC915OAI: oai:DiVA.org:hv-20373DiVA, id: diva2:1780025
Subject / course
Robotics
Educational program
Master i robotik och automation
Supervisors
Examiners
Available from: 2023-07-17 Created: 2023-07-05 Last updated: 2025-09-30Bibliographically approved

Open Access in DiVA

No full text in DiVA

By organisation
Department of Engineering Science
Robotics and automation

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 259 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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