3D Log Cutting Pattern Optimization Using Cross-Section Value Maps
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Solution Overview
Problem
The computational complexity of optimizing cutting patterns for tree logs using computed tomography scans is high, leading to significant computation time and potential inconsistencies in the optimised cutting patterns.
Innovation Solution
A computer-implemented method that provides a cutting pattern by generating value maps for cross-sections of a three-dimensional log model, which summarize the quality of virtual boards, allowing for faster optimization of cutting patterns using a convolutional neural network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computed tomography scanning and detailed defect analysis are used to optimize cutting patterns, then the quality and accuracy of the optimisation improves, but the computational complexity and time required increase significantly
Solution Approach 1:
The patent performs computed tomography scanning and creates a three-dimensional model of the log's internal structure before the cutting optimization process. By pre-acquiring detailed defect information and storing it in a digital model, the system eliminates the need for time-consuming defect analysis during the optimization phase, allowing rapid evaluation of cutting patterns while maintaining high defect detection accuracy
Solution Approach 2:
The patent creates a digital three-dimensional copy of the log's internal structure through tomography scanning. This virtual model serves as a replica that can be repeatedly analyzed and used for optimization simulations without requiring additional physical inspection or re-scanning of the actual log, significantly reducing computational time while preserving defect information
2Productivity
If millions of virtual boards are evaluated to optimize the cutting pattern, then the optimisation quality improves, but the computational effort and complexity increase significantly
Solution Approach 1:
The patent pre-processes the three-dimensional log model to identify and catalog all defects with their precise spatial coordinates and dimensions before optimization. By preparing defect data in advance and organizing it in an accessible format, the system enables rapid evaluation of virtual boards during optimization without requiring complex real-time defect analysis, thus reducing computational complexity while maintaining thorough evaluation of millions of cutting patterns
Solution Approach 2:
The patent replaces complex mechanical defect analysis procedures with automated digital image processing and computational algorithms. The three-dimensional model allows virtual cutting patterns to be evaluated through computer-based intersection calculations and defect proximity assessments, eliminating the need for manual or iterative physical analysis methods and enabling efficient processing of millions of optimization candidates
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 reduces computational effort and time required to optimize cutting patterns, providing a more efficient and accurate alternative to existing methods, while ensuring compatibility with sawmill processing requirements.
Implementation Method 1
performing a computed tomography scanning of the log to obtain a three-dimensional model of the log
Data Source
AI summary
A computer-implemented method to provide a cutting pattern for a tree log to obtain wooden boards including a step of obtaining a three-dimensional model 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 to compute the value of a virtual board having a minor face with set orientation and set dimensions, at a cross-section 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 at that point and having the set orientation and set dimensions.