Moisture Variability Quantification in Wood Drying
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Solution Overview
Problem
The lumber industry faces challenges in ensuring consistent moisture content in wood products, leading to variability that affects product quality, value, and efficiency in drying processes, as existing methods struggle to accurately quantify and manage sources of moisture content variability.
Innovation Solution
A method is developed to quantify the contribution of various sources of moisture content variability in wood products, using data analysis and statistical models to identify and prioritize opportunities for reducing variability, which includes obtaining moisture content data, identifying sources of variability, and implementing executable steps to impact these sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If controlled drying processes are used in kilns, then moisture content is reduced, but variability in moisture content remains due to differences in drying conditions between and within kiln charges
Solution Approach 1:
The patent segments the drying process into distinct hierarchical levels (kiln charges, packages, courses, and pieces) to systematically identify and quantify variability sources at each level. This segmentation allows targeted intervention at specific stages rather than treating the entire drying process as a uniform system.
Solution Approach 2:
The patent implements feedback through statistical analysis of moisture content data collected at multiple hierarchical levels. By quantifying variability contributions from each level, the system provides feedback on which stages require process adjustments, enabling continuous improvement of drying consistency.
2Manufacturing precision
If moisture content is reduced to improve product value, then dimensional stability and durability improve, but variability in moisture content leads to over- or under-drying losses
Solution Approach 1:
The patent performs preliminary statistical analysis of variability sources before final drying decisions are made. By identifying which hierarchical levels contribute most to variability, the system enables proactive process adjustments that prevent over- or under-drying, thereby preserving product value.
Solution Approach 2:
The patent changes the parameter being controlled from simply average moisture content to the distribution of moisture content across multiple hierarchical levels. This parameter transformation allows detection and correction of variability issues that would be invisible if only mean moisture content were monitored.
Data Source
AI summary
The present disclosure includes a method for quantifying contribution to overall variability of moisture content in wood products and associated computer software. The method comprises the steps of obtaining moisture content data for the wood products and identifying one or more sources of variability in the moisture content data. A contribution to overall variability from each of the one or more sources of variability is then quantified. One or more opportunities to impact the overall variability are then quantified, each of the one or more opportunities being associated with one or more executable steps.