Tree Log Cutting Patterns Using Cross-Sectional Value Maps
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Solution Overview
Problem
Existing methods for optimizing cutting patterns in tree logs require significant computational effort, leading to long computation times and potential inconsistencies due to the complexity of evaluating millions of virtual boards, which is not compatible with manufacturing requirements in sawmills.
Innovation Solution
A computer-implemented method using value maps derived from three-dimensional models of logs, generated through computed tomography or alternative measurement systems, to simplify the optimization process by correlating defect and structural information, reducing computational complexity and enabling faster determination of optimal cutting patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If computed tomography scanning is used to obtain three-dimensional model of log, then information on internal structure and defects is improved, but computational complexity increases significantly
Solution Approach 1:
The patent segments the continuous three-dimensional model into discrete cross-sectional slices at predetermined intervals along the longitudinal axis. Each slice is processed independently to generate defect maps and value maps, reducing the overall computational burden by dividing the complex 3D analysis into manageable 2D sections that can be evaluated separately and efficiently.
Solution Approach 2:
The patent performs preliminary processing by generating defect maps from cross-sectional slices before the final optimization stage. The defect maps pre-identify and characterize defects in each slice, and value maps pre-calculate quality metrics for potential board positions. This preliminary action prepares the data structure in advance, avoiding repeated complex calculations during the optimization phase.
2Manufacturing precision
If millions of virtual boards are evaluated for optimization, then cutting pattern optimization accuracy is improved, but computation time increases significantly
Solution Approach 1:
The patent segments the evaluation process by generating value maps for discrete cross-sectional slices rather than evaluating every possible virtual board position continuously. This segmentation reduces the number of evaluations from millions to a manageable set of representative slice positions, maintaining optimization accuracy while dramatically reducing computation time to levels compatible with sawmill manufacturing requirements.
Solution Approach 2:
The patent creates simplified two-dimensional representations (defect maps and value maps) that copy the essential defect information from the three-dimensional model. These 2D copies retain the critical quality characteristics needed for optimization decisions while requiring far less computational power to process than full 3D virtual board evaluations, enabling rapid assessment of cutting patterns.
3Loss of time
If approximations of evaluation rules are used to speed up optimization, then computation time is reduced, but cutting pattern optimization accuracy deteriorates
Solution Approach 1:
The patent replaces complex mechanical evaluation processes with image processing techniques. Instead of physically evaluating each virtual board against detailed quality criteria, the system uses computer-generated defect maps and value maps that visually represent defect locations and quality metrics. This substitution enables accurate optimization evaluation through automated image analysis, maintaining precision while achieving computation speeds suitable for real-time sawmill operations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method significantly reduces computational effort and time required to optimize cutting patterns, providing accurate and efficient cutting solutions compatible with sawmill manufacturing timelines.
Implementation Method 1
a computer is configured to obtain a three-dimensional model of a log, in particular by performing a computed tomography scanning of the log
Data Source
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AI summary
A computer-implemented method to provide a cutting pattern for a tree log (1) to obtain wooden boards (2) comprises a step of obtaining (for instance, by computed tomography scanning of the log) a three-dimensional model (19) containing information about features of a structure of the log and/or about defects of the log. A step of computer-processing of the three-dimensional model, to determine the cutting pattern by optimisation of an objective function, comprises the use of a value map (3) to compute the value of a virtual board (25) having a minor face (26), with set orientation and set dimensions, at a cross-section (12) of the three-dimensional model. The value map, which correlates to the information about the features and/or the defects of the log, assigns to each point of the cross-section a value of a virtual board having its minor face centred (or having another predetermined positional relationship) at that point and having the set orientation and set dimensions.