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Quality control methods for monitoring the variability of moisture content in kiln-dried lumber

University of British Columbia

Monitoring the variability of moisture content in lumber is a problem of utmost importance in kiln-drying. This thesis focused on determining the distribution of moisture content in lumber, and on the application of statistical process control principles to monitor the drying process through the use of quality control charts. Specific parameters of the charts for monitoring the process average and process dispersion were determined. The charts were developed on the assumption that the data under analysis has a Lognormal distribution. To test whether this assumption is valid or not for moisture content, graphical and numerical tests were employed as goodness of fit methods. Graphical methods utilized in this research were symmetry and probability plots, and empirical cumulative distribution function graphs. Numerical methods employed in this study were goodness of fit tests based on empirical distribution function statistics. Procedures were developed for both graphical and numerical goodness-of-fit methods, and also for construction of control charts for Lognormal variables. The methods presented were tested on a data set of actual Douglas-Fir (Pseudotsuga menziesii) lumber collected from a production facility in British Columbia, Canada. It was determined that the Lognormal distribution provided a good fit for the experimental data. Therefore, the proposed control charts for Lognormal data are to be used instead of the customary charts based on the Normality assumption.

Thesis/Dissertation

application/pdf

2009-08-06

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http://hdl.handle.net/2429/11801

Forestry

University of British Columbia

UBCV

DSpace