Achieving quality control during veneer drying by using big data statistics

Veneer drying has traditionally been done using a qualitative approach. Although it is effective in assessing how any modification in parameters impacts veneer quality, it often yields a significant loss in quality due to delays involved in reaching the kiln's steady state following parameter modification. However, kilns are now being equipped with various sensors that allow the tracking of many parameters related to both the kiln and the veneers. The research objective is to link raw material characteristics with the veneer drying process. The intern will use big data statistics to identify what process parameter have the most impact on product quality and how those significant parameters should be controlled. TO BE CONT'D

Intern: 
Suborna Shekhor Ahmed
Faculty Supervisor: 
Julie Cool
Province: 
British Columbia
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