3D Flitch Tracking for Source Log and Saw Identification
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Solution Overview
Problem
Lumber processing facilities face challenges in accurately matching flitches to their source logs due to random stacking and out-of-order arrival, making it difficult to identify problematic saws and optimize cutting patterns for different tree species, which affects efficiency and profitability.
Innovation Solution
A scanner optimizer system that includes geometric sensors and computer systems to generate 3D virtual models of logs and flitches, enabling the identification of the source log and saw used to cut a flitch, and adjusts equipment performance based on this data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If flitches are stacked randomly on a queuing deck for processing, then the system can handle high volumes of lumber efficiently, but it becomes impossible to track which flitches came from which source logs
Solution Approach 1:
The system performs preliminary scanning and identification of flitches at the queuing deck before they are processed further. Optical scanners capture images and data about each flitch's origin, and this information is stored in advance so that when flitches are later processed, their source log identification is already available without requiring physical tracking through the entire processing line.
Solution Approach 2:
A computer system acts as an intermediary between the physical flitch handling system and the tracking requirements. The computer receives data from optical scanners, correlates it with log inventory information, and maintains a digital mapping between flitches and source logs. This intermediary system enables tracking without physically restricting flitch movement or stacking.
2Adaptability or versatility
If flitches are processed through multiple stages (queuing deck, unscrambler, edger, gang saw), then comprehensive lumber production is achieved, but tracking the original source log becomes increasingly difficult
Solution Approach 1:
The system establishes source log identification at the very beginning - at the queuing deck - before flitches undergo any processing transformations. By capturing images and data early and storing them in a database, the system creates a permanent record that survives all subsequent processing stages including unscrambling, edging, and gang saw operations.
Solution Approach 2:
The computer system continuously correlates flitch data with source log information throughout the processing pipeline. Optical scanners at various stages feed data back to the computer, which updates and maintains the tracking information, ensuring that source log identification remains accurate even as flitches move through multiple processing stages.
3Device complexity
If traditional manual tracking methods are used to identify source logs, then equipment complexity is minimized, but tracking accuracy and efficiency deteriorate
Solution Approach 1:
The system replaces manual mechanical tracking methods with an automated optical and computational system. Optical scanners capture flitch images and characteristics, while a computer system automatically processes this data, compares it with log inventory records, and identifies source logs. This substitution of mechanical/manual processes with optical-electronic systems dramatically improves tracking accuracy while maintaining reasonable system complexity.
Solution Approach 2:
The system creates digital copies of flitch characteristics through optical scanning. Instead of physically tracking the actual flitch through the processing line, the system works with digital images and data copies that contain all necessary identification information. This copying approach enables accurate source log matching without requiring complex physical tracking mechanisms.
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
Enhances the ability to match flitches to their source logs, optimizes cutting patterns, and improves equipment performance, leading to increased efficiency and profitability by reducing waste and optimizing cutting strategies for multiple species.
Implementation Method 1
A scan zone upstream of the edger includes a plurality of geometric sensors arranged to scan the flitch and measure its three-dimensional (3D) geometry
Data Source
AI summary
In various embodiments, a scanner optimizer system may generate a virtual model of a predicted flitch based on a 3D model of a log/cant and a cut solution for the log/cant. The scanner optimizer system may compare a virtual model of an actual flitch to virtual models of predicted flitches by comparing data points at a fixed elevation relative to one or both faces of the models. Based on the comparisons, the scanner optimizer system may identify the source log from which the actual flitch was cut. In addition, the scanner optimizer system may identify the saw used to cut the actual flitch, and/or other relevant information, and use the additional information to monitor and adjust the saws and other equipment. Embodiments of corresponding apparatuses and methods are also described.