The use of simulation as a decision tool for improvements in sawmill manufacturing
A simulation study was used to analyze the flow of products though a sawmill in order to determine where productivity improvements could be made. The sawmill analyzed is located in the interior of British Columbia, and processes a variety of species and products. The mill was selected for this reas...
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ndltd-LACETR-oai-collectionscanada.gc.ca-BVAU.-6192013-06-05T04:16:22ZThe use of simulation as a decision tool for improvements in sawmill manufacturingThoews, Steven EricSawmillSimulationDESArenaA simulation study was used to analyze the flow of products though a sawmill in order to determine where productivity improvements could be made. The sawmill analyzed is located in the interior of British Columbia, and processes a variety of species and products. The mill was selected for this reason, as it was important to determine how a change in the process will affect the piece flow and production of the various species. A simulation model of the mill was developed using the Arena 8.0 discrete event simulation software developed by Rockwell Automation. Data consisting of mill layout and flow, breakdown patterns, machine process times and downtimes, conveyor speeds, and buffer capacities were collected from the sawmill. This information was used to layout the framework in a conceptual model. The conceptual model was then used to develop the simulation model in Arena. A face validity test, combined with comparisons of model output to actual mill output was used to determine the validity of the model. After running several different scenarios processing Larch, White pine, and Ponderosa pine, it was discovered that the trimmer was the system bottleneck when both the small log and large log lines were running throughout the shift. Running under base case conditions, the model predicted an average board output of 13,147 boards. An increase in the processing capability of the trimmer resulted in the bottleneck to shift to the edger from the small log line. The OptQuest Analyzer program bundled with the Arena software was used to further analyze the shift in bottleneck to the edger from the small log line. By allowing the program to manipulate machine settings for the trimmer and edger, it was able to maximize the average board output to 17,996 boards per shift when no edger set up times were considered. If the edger setup times are used, the average board output dropped to 16,708 boards per shift. These findings were presented to the sawmill management and based on the study, they proceeded to make improvements at the trimmer. The improvements resulted in an increase of 10% to sawmill output.University of British Columbia2008-03-31T21:11:48Z2008-03-31T21:11:48Z20082008-03-31T21:11:48Z2008-05Electronic Thesis or Dissertation1492056 bytesapplication/pdfhttp://hdl.handle.net/2429/619eng |
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Sawmill Simulation DES Arena |
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Sawmill Simulation DES Arena Thoews, Steven Eric The use of simulation as a decision tool for improvements in sawmill manufacturing |
description |
A simulation study was used to analyze the flow of products though a sawmill in order to determine where productivity improvements could be made. The sawmill analyzed is located in the interior of British Columbia, and processes a variety of species and products. The mill was selected for this reason, as it was important to determine how a change in the process will affect the piece flow and production of the various species. A simulation model of the mill was developed using the Arena 8.0 discrete event simulation software developed by Rockwell Automation.
Data consisting of mill layout and flow, breakdown patterns, machine process times and downtimes, conveyor speeds, and buffer capacities were collected from the sawmill. This information was used to layout the framework in a conceptual model. The conceptual model was then used to develop the simulation model in Arena. A face validity test, combined with comparisons of model output to actual mill output was used to determine the validity of the model.
After running several different scenarios processing Larch, White pine, and Ponderosa pine, it was discovered that the trimmer was the system bottleneck when both the small log and large log lines were running throughout the shift. Running under base case conditions, the model predicted an average board output of 13,147 boards. An increase in the processing capability of the trimmer resulted in the bottleneck to shift to the edger from the small log line. The OptQuest Analyzer program bundled with the Arena software was used to further analyze the shift in bottleneck to the edger from the small log line. By allowing the program to manipulate machine settings for the trimmer and edger, it was able to maximize the average board output to 17,996 boards per shift when no edger set up times were considered. If the edger setup times are used, the average board output dropped to 16,708 boards per shift. These findings were presented to the sawmill management and based on the study, they proceeded to make improvements at the trimmer. The improvements resulted in an increase of 10% to sawmill output. |
author |
Thoews, Steven Eric |
author_facet |
Thoews, Steven Eric |
author_sort |
Thoews, Steven Eric |
title |
The use of simulation as a decision tool for improvements in sawmill manufacturing |
title_short |
The use of simulation as a decision tool for improvements in sawmill manufacturing |
title_full |
The use of simulation as a decision tool for improvements in sawmill manufacturing |
title_fullStr |
The use of simulation as a decision tool for improvements in sawmill manufacturing |
title_full_unstemmed |
The use of simulation as a decision tool for improvements in sawmill manufacturing |
title_sort |
use of simulation as a decision tool for improvements in sawmill manufacturing |
publisher |
University of British Columbia |
publishDate |
2008 |
url |
http://hdl.handle.net/2429/619 |
work_keys_str_mv |
AT thoewssteveneric theuseofsimulationasadecisiontoolforimprovementsinsawmillmanufacturing AT thoewssteveneric useofsimulationasadecisiontoolforimprovementsinsawmillmanufacturing |
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